Skip to main content
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2025 Sep 30;38(50):e12919. doi: 10.1002/adma.202512919

Skin Relevant Biomaterials from Wound Healing, Medical Aesthetics, Flexible Electronics to Artificial Intelligence and Beyond

Yanshuang Zhang 1, Ye Fu 1, Tao Sun 1, Wenqian Li 1, Lin Yu 1, Jiandong Ding 1,✉
PMCID: PMC13549263  PMID: 41025745

Abstract

Recent advancements in biomaterials have profoundly transformed the fields of dermatology and tissue engineering, etc., offering innovative solutions that markedly improve skin treatment outcomes. This review provides a comprehensive overview of the latest developments in natural, synthetic, and composite biomaterials tailored for skin treatments and skin‐related medical devices, including wound healing, tissue engineering, drug delivery, dermatological therapies, medical aesthetics, e‐skin, and skin‐related surgery‐assistant devices. The incorporation of artificial intelligence (AI) into biomaterial design has facilitated the development of adaptive and predictive systems capable of responding dynamically to the skin's physiological needs. Moreover, an in‐depth understanding of the interactions between biomaterials and cells, as well as the activation of biological pathways and regulation of cellular processes is pivotal for enhancing skin health and function. Looking forward, the main efforts toward future in this field are suggested as follows: 1) Development of novel materials remains central; 2) Responsive biomaterials enable precise therapy; 3) Integration with cell therapy is pivotal in regenerative medicine; 4) In‐depth investigations into material‐driven biological mechanisms are critical for innovative design of skin‐related materials; 5) Interdisciplinary collaboration is vital for the rapid evolution of biomaterials; 6) Enhanced applications of AI is driving the development of adaptive and predictive biomaterials.

Keywords: artificial intelligence, biomaterial, flexible electronics, machine learning, medical aesthetics, skin, wound healing


This review offers a comprehensive overview of recent advances in natural, synthetic, and composite biomaterials for skin applications, ranging from wound healing and tissue engineering to drug delivery, dermatological therapies, medical aesthetics, and e‐skin. It also highlights the biomaterial‐cell interaction and the revolutionary role of artificial intelligence in research and development of the innovative materials.

graphic file with name ADMA-38-e12919-g019.webp

1. Introduction

Biomaterials are, at the intersection of modern medicine and materials science, driving transformative advancements in medical technologies.[ 1 , 2 , 3 , 4 , 5 , 6 ] In recent years, research on skin‐related biomaterials has been well developed from the bioinspired design of natural materials to the intelligent responsiveness of synthetic materials,[ 7 , 8 , 9 ] and further extended to the multifunctional integration of composite materials.[ 10 , 11 ] These developments have enabled precision‐engineered solutions across the full spectrum of cutaneous health management strategies. In advanced skin intervention strategies, functional biomaterial engineering has emerged as a key driver of therapeutic innovation. Natural materials such as proteins, polysaccharides, and lipid‐based compounds exhibit remarkable potential in promoting wound healing and tissue regeneration owing to their superior biocompatibility and biomimetic characteristics.[ 12 , 13 , 14 , 15 ] Synthetic biomaterials, by contrast, exploit precise control over physicochemical properties to achieve functionalities like sustained drug delivery, mechanical adaptability, and stimuli‐response.[ 16 , 17 ] Hybrid systems that combine natural and synthetic components leverage multiscale structural designs to synergistically integrate bioactivity with mechanical robustness, providing advanced therapeutic strategies for complex skin disorder.[ 18 , 19 ] These materials not only replicate the native skin microenvironment but also dynamically interact with physiological cues to modulate cellular activities and enhance skin treatment outcomes.

The increasing complexity of these advanced biomaterials, which encompasses intricate designs, multifunctional integration, and the need to dynamically interact with biological systems, poses significant challenges for their rational development using traditional trial‐and‐error approaches. To address this, computational methods capable of synthesizing data across multiple scales, uncovering complex non‐linear patterns, and enabling predictive, knowledge‐driven material development are now essential. In this context, artificial intelligence (AI), particularly machine learning (ML), has emerged as a transformative force in biomaterials research, revolutionizing how new materials are discovered, optimized, and applied.[ 20 , 21 ] AI‐driven strategies such as high‐throughput virtual screening, dynamic response modeling, and predictive algorithms have significantly accelerated the development of innovative biomaterials.[ 22 ] For instance, ML has streamlined the discovery and optimization of critical components like ionizable lipids by combining virtual screening with high‐throughput experimentation, thereby shifting material development from experience‐based to data‐driven paradigms.[ 23 ] Additionally, AI has significantly expanded the scope of skin‐related biomaterials into more advanced and cutting‐edge applications such as 3D electronic skin (e‐skin).[ 24 ] The integration of real‐time sensing and intelligent decision‐making enables biomaterials to not only detect biological signals but also adapt their behavior accordingly, forming a smart feedback loop between detection and action, offering a transformative platform for personalized medicine and precision healthcare. Furthermore, the progress in skin‐related biomaterials reciprocally enhances the application of AI technologies in medical domains, fostering interdisciplinary collaboration and innovation.[ 25 ]

The ultimate success of these AI‐informed and intricately designed biomaterials hinges on a deep understanding of their biological interactions. Consequently, emerging research further highlights the critical interplay between biomaterial properties and cutaneous microenvironments. The surface topography, chemical signaling, and mechanical properties of materials can modulate key cellular behaviors including migration, proliferation, and differentiation by activating specific biological pathways.[ 26 , 27 , 28 ] These interactions can even reprogram the immune microenvironment, and thereby offer new insights into therapeutic strategies.[ 29 , 30 ] The material‐driven biology paradigm not only underscores the active regulatory role of biomaterials in treatment but also provides a theoretical foundation for advancements in regenerative medicine and precision healthcare, generating crucial data to further refine AI models in a virtuous cycle of innovation.

It is worthy of noting that the topic of this paper “skin relevant biomaterials” is not limited to skin repair, but from wound healing, medical aesthetics, flexible electronics to artificial intelligence and beyond. This review aims to provide a comprehensive overview of the latest developments in skin‐related biomaterials, first encompassing innovative designs of natural, synthetic, and composite materials, and then their applications in wound healing, tissue engineering, drug delivery, dermatological therapies, medical aesthetics, sensing, monitoring, and surgical interventions. We also delve into the underlying mechanisms through which these biomaterials exert their effects by modulating the cellular microenvironment and activating biological pathways. Furthermore, we analyze the growing integration of AI technologies in the development of skin‐related biomaterials, showcasing how it addresses the complexity of material design and leverages insights from biological mechanisms. The main contents are schematically presented in Figure 1 . In the end of this review article, we highlight key challenges that warrant further attention to in the research and development (R&D) of skin‐related biomaterials and related fields in the future.

Figure 1.

Figure 1

Sources and applications of skin biomaterials, powered by AI‐driven discovery and a fundamental understanding of biomaterial‐cell interactions. This schematic illustrates the sources and key applications of skin‐relevant biomaterials, and highlights that the integration of AI with fundamental biological understanding accelerates the development and optimization of next‐generation materials.

2. Biomaterial Types for Skin Applications

Skin‐related biomaterials are, like most of materials, basically classified into three principal categories according to their material origins and design frameworks: natural, synthetic, and composite systems. Natural biomaterials, derived from biological sources, are primarily classified into protein‐based, polysaccharide‐based, and lipid‐based systems etc. These materials inherently mimic the skin's biochemical and structural properties, offering high biocompatibility and dynamic interactions with the skin microenvironment. Their molecular diversity enables versatile biological functions such as supporting cellular activities and modulating physiological responses. Synthetic biomaterials provide tunable mechanical properties and programmable functionalities. Through chemical modifications and structural optimization, they address limitations of natural materials, such as durability and adaptability, while enabling precise control over degradation rates and stimulus‐responsive behaviors. Bio‐composite materials integrate natural and synthetic components, combining bioactive elements with engineered architectures. This hybrid approach leverages biomimetic designs and multifunctional strategies to create adaptive systems capable of interacting synergistically with skin tissues.[ 31 ]

2.1. Natural Biomaterials

Naturally derived skin‐related biomaterials are, owing to their biocompatibility and adaptability to the skin microenvironment, widely utilized across various aspects of skin health. Protein‐based materials leverage their unique molecular structures and functionalized designs to demonstrate remarkable advantages in promoting cell proliferation, modulating immune responses and facilitating drug delivery.[ 13 , 32 ] Polysaccharide‐based materials are effective in tissue regeneration, anti‐aging treatments, and the reconstruction of skin barriers.[ 12 , 33 , 34 ] Some lipid‐based materials not only replicate the skin's barrier functions but also contribute to hydration and inflammation modulation.[ 14 ] Additionally, other natural materials, such as nucleic acid‐based carriers and minerals, further enhance the potential of these materials in personalized medicine and intelligent response systems.[ 35 , 36 , 37 ] Despite their advantages, naturally derived biomaterials face several challenges. Protein‐based systems may suffer from batch‐to‐batch variability, potential immunogenicity, and relatively poor mechanical stability. Polysaccharide‐based materials often exhibit low mechanical strength, limited elasticity, and may occasionally trigger unpredictable inflammatory responses. Lipid‐based formulations, while effective in barrier protection and drug encapsulation, can be hindered by low water solubility, oxidative instability, and formulation complexity. Therefore, understanding and leveraging these inherent properties is critical for optimizing the performance and clinical translation of natural biomaterials in dermatological applications (Table 1 ).

Table 1.

Comparative analysis of protein‐based, polysaccharide‐based, and lipid‐based natural biomaterials for skin applications.

Material type Key advantages Main disadvantages Primary applications
Protein‐based
  • High bioactivity

  • Excellent cell adhesion and migration

  • Promotes proliferation

  • Inherent biochemical cues

  • Batch‐to‐batch variability

  • Potential immunogenicity

  • Relatively poor mechanical stability

  • Rapid degradation

  • Tissue‐engineered scaffolds

  • Wound dressings

  • Drug delivery systems (DDSs)

  • Hemostatic agents

  • Anti‐aging & cosmetic formulations

  • 3D bioprinting bioinks

Polysaccharide‐based
  • Excellent hydrophilicity and biocompatibility

  • Tunable degradation

  • Gelation capacity

  • Low immunogenicity

  • Abundant reactive sites for modification

  • Sometimes lack mechanical robustness

  • Limited elasticity

  • May elicit unpredictable inflammatory responses

  • Hydrogel dressings

  • Moisture retention & barrier repair creams

  • Anti‐inflammatory & immunomodulatory treatments

  • Transdermal DDSs

  • Antimicrobial coatings & films

  • Injectable fillers & dermal substitutes

  • Hemostatic agents & wound sealing materials

Lipid‐based
  • Superior barrier function

  • Mimics stratum corneum structure,

  • Encapsulates hydrophobic/hydrophilic compounds

  • Enhances skin hydration

  • Low water solubility

  • Oxidative instability

  • Formulation complexity

  • Limited structural strength

  • Transdermal & topical drug delivery

  • Nanostructured lipid carriers

  • Barrier repair creams & ointments

  • Moisturizers & emollients

  • Sunscreen formulations

  • Cosmetic & skincare products

Natural proteins, sourced from diverse biological origins such as animals, plants, and other organisms, are regarded as ideal candidates for developing skin‐related biomaterials owing to their rich functionalities and unique biological characteristics.[ 13 , 32 ] For example, animal‐ and plant‐derived proteins, serving as core materials, have been leading options in wound repair, tissue regeneration, and the development of antibacterial dressings through structural optimization and functional modifications.[ 38 , 39 ] Among them, collagen stands as one of the most extensively studied and applied protein materials in skin tissue engineering, valued for its excellent biocompatibility, biodegradability, and its capacity to support cell attachment and proliferation by mimicking the native extracellular matrix (ECM).[ 40 ] Notably, keratin, with its cysteine‐rich molecular composition, could form stable cross‐linked networks, imparting materials with antioxidant, pro‐angiogenic, and multi‐responsive properties, which excel in moist wound healing applications.[ 39 , 41 ] Nevertheless, extraction and purification complexities pose challenges for clinical translation. Leveraging its inherent antibacterial and antioxidant traits, sericin has been employed to create dressings for infected wounds, significantly expediting epidermal regeneration.[ 42 ] Yet, its potential to elicit immune reactions in certain individuals cannot be overlooked. Hydrogels formed by crosslinking silk fibroin and gelatin exhibit remarkable mechanical adaptability and drug‐loading capacity, enabling localized delivery of antimicrobial peptides or growth factors to address complex wound environments.[ 43 ] The trade‐off between mechanical enhancement and biocompatibility remains a critical consideration. In particular, decellularized extracellular matrix (dECM) bioink has recently emerged as a superior biomaterial that closely mimics the native skin microenvironment. As demonstrated by Kim et al., skin‐derived dECM preserves critical ECM components and bioactive factors, enabling the fabrication of stable, functional skin constructs with minimal shrinkage and enhanced epidermal barrier function.[ 44 ] Unlike single‐component materials such as collagen, dECM‐based bioinks provide a tissue‐specific niche that supports robust cell viability, ECM secretion, and accelerated wound healing through improved vascularization and re‐epithelialization, offering a transformative platform for advanced skin tissue engineering.[ 44 ] Despite these advantages, the risk of pathogen transmission, variability in decellularization efficiency, and high processing costs should been taken into consideration in clinical translations.

Technological advancements in genetic code expansion and modular protein engineering have created new opportunities for enhancing the functionality of natural proteins.[ 45 , 46 ] For instance, the site‐specific incorporation of non‐canonical amino acids allows precise modulation of antibacterial activity, antioxidant ability, and cell adhesion property in protein‐based materials.[ 47 , 48 ] Furthermore, biomimetic designs, such as hierarchical self‐assembly and heterocomposite engineering, have markedly improved the mechanical strength and ionic conductivity of protein‐based hydrogels, enabling them to replicate skin barrier functions while meeting the demands of flexible electronic sensors.[ 8 , 9 ] Still, the complexity and high cost of these technologies, along with regulatory hurdles for genetically modified biomaterials, may delay clinical adoption.

Functionally, recent advancements have evolved from monofunctional designs to multifunctional integrated systems. For example, scaffolds combining keratin and sericin can simultaneously achieve hemostasis, anti‐inflammation, epithelialization promotion, and antibacterial cascade effects.[ 39 , 42 ] However, the integration of multiple components increases the risk of unpredictable immune responses and complicates manufacturing standardization. Self‐assembling systems based on insect proteins, for instance, nanofibrils achieved via salt‐induced controlled shaping, provide innovative solutions that combine dynamic adaptability and bioactivity for infected wounds.[ 49 ] Yet, scalability and stability under physiological conditions remain challenging. By integrating interdisciplinary technologies such as ECM mimicry, nano‐topographical control, and dynamic release system design, the overall performance of these materials in promoting healing, combating infections, and facilitating tissue remodeling has been greatly enhanced.[ 50 , 51 ] These developments not only expand the application scope of natural proteins in skin regenerative medicine but also lay a strong foundation for the advancement of next‐generation multifunctional intelligent biomaterials.

Polysaccharide‐based biomaterials have, among the most abundant biopolymers in nature, recently gained significant attention for their unique biological properties and functional diversity, demonstrating immense value in applications such as wound repair, anti‐aging therapies, and skin barrier reconstruction.[ 12 , 33 , 34 ] Natural polysaccharides, such as chitosan, hyaluronic acid (HA), and alginate, mimic the native ECM, and facilitate superior cell adhesion and proliferation.[ 52 ] However, their high hydrophilicity and swelling behavior may lead to premature dissolution and reduced mechanical integrity in wet environments. Modified cellulose‐based materials have further expanded their utility as 3D scaffolds. By aligning nanofibers to replicate the topological cues of the skin's ECM, these materials facilitate directional migration of keratinocytes.[ 53 ] Moreover, their tunable rheological properties, low immunogenicity, and controllable degradation profiles make them candidates for developing advanced skin dressings.[ 54 , 55 ] For instance, a hexasaccharide (OG6) was derived from glucomannan (GM) through controlled enzymatic hydrolysis, highlighting the tunable degradation of polysaccharide‐based biomaterials. This process yielded well‐defined oligosaccharides with specific bioactivity, demonstrating how precise structural modification can enhance material function (Figure 2 ).[ 56 ] Although the original work focused on immunomodulation‐driven hair regeneration, the approach exemplifies key features of polysaccharides such as controllable breakdown, gelation capacity, and potential to support cellular processes, properties highly relevant to applications like wound dressings for hemostasis and tissue repair, where modulated biodegradation and bioactivity are essential.[ 56 , 57 ] Xu group further discovers that the optimal amount of cationic grafts plays a key role of functionalization of polysaccharide in achieving balanced plasma‐protein adhesion, platelet adhesion and blood coagulation system of advanced wound dressings.[ 57 ] The reproducibility of enzymatic degradation products and their precise bioactivity should be controlled across batches. Additionally, polysaccharides sourced from plants or marine algae, such as carrageenan and fucoidan, can be chemically modified to impart antibacterial, antioxidant, and anti‐inflammatory functionalities. Such multifunctional capabilities make them valuable for managing complex chronic wounds, including diabetic foot ulcers, where they simultaneously address infection control and tissue reconstruction, achieving synergistic therapeutic outcomes.[ 58 , 59 , 60 ] Nevertheless, chemical modification may alter natural biocompatibility and introduce unintended cytotoxic effects.

Figure 2.

Figure 2

Polysaccharide‐based biomaterials utilized for enhancing hair growth. Controlled degradation of glucomannan (GM) yields a hexasaccharide fraction (OG6) with specific immunomodulatory function, illustrating the potential of structurally defined glycans to regulate cellular behavior and promote regeneration. Reproduced from Ref. [56] with permission of Wiley, 2023.

A breakthrough in polysaccharide‐based skin‐related biomaterials lies in the development of multifunctional responsive systems. For example, thermosensitive or photoresponsive dressings based on the dynamic cross‐linking techniques can accelerate skin repair by adjusting microenvironmental humidity and enable sustained release of active compounds.[ 61 , 62 ] Multifunctional composite dressings incorporating metal nanoparticles or gas‐releasing components exhibit substantial clinical potential in inhibiting biofilm formation and enhancing angiogenesis.[ 63 , 64 ] Yet, the potential nanoparticle toxicity and burst release of gases require careful dose control and safety evaluation. Quaternized chitosan combined with pH‐responsive drug release systems significantly enhanced antibacterial efficacy and wound healing efficiency.[ 65 , 66 ]

Furthermore, the surfaces of polysaccharide molecules are rich in inherently reactive functional groups such as hydroxyl and carboxyl moieties, which offer a versatile chemical platform for further functionalization. While these native groups alone are generally insufficient to confer specific binding or precisely controlled drug release, they serve as key modification sites for introducing advanced functional moieties (such as targeting ligands, stimuli‐responsive linkers, or molecular recognition elements) that significantly enhance the specificity and precision of DDSs. Through such rational functionalization, polysaccharide‐based drug carriers can achieve improved controlled release of antibiotics or growth factors, thereby enhancing treatment efficacy.[ 55 , 67 , 68 ] It should be noted, however, that extensive chemical modification might lead to loss of biodegradability, increased immunogenicity, and potential environmental persistence.

Lipids are essential components of the skin barrier, and biomimetic lipids designed to replicate the characteristic architecture of the stratum corneum lipids are uniquely suited as foundational materials for biomimetic skin applications. This suitability is rooted in their unique physicochemical and structural properties, including ability to self‐assemble into ordered bilayers or multilayers, and composition‐dependent phase behavior, which are critical for forming a functional barrier that mimics natural skin.[ 14 , 69 ] Their molecular structure, which often contains ceramides, fatty acids, and cholesterol, closely resembles the lipid composition in the stratum corneum.[ 70 , 71 ] This similarity enables the reconstruction of a continuous, lamellar lipid matrix with high barrier efficacy against water loss and the penetration of external agents. Additionally, lipids offer biocompatibility, biodegradability, and the capacity to encapsulate both hydrophilic and hydrophobic compounds, making them ideal for dermatological applications.[ 69 ] This structural resemblance enables lipids to effectively replicate the functions of the natural skin barrier, supporting the repair and regeneration of damaged skin tissues while offering new opportunities for the development of advanced skin repair materials and DDSs.[ 14 ] Nevertheless, lipid‐based systems are often prone to oxidation, instability during storage, and may require stringent temperature control, limiting their shelf life and ease of handling. Drawing on biomimetic design principles, scientists have engineered multifunctional lipid nanoparticles through precise modulation of lipid matrix composition. These materials closely mimic the behavior of skin lipids, and by optimizing the ratio of solid to liquid lipids, they significantly enhance transdermal drug delivery efficiency and improve skin hydration. These formulations ensure the physicochemical stability of the materials.[ 72 ] Nonetheless, issues such as batch reproducibility, scalability, and potential irritation from certain lipid compositions need to be addressed. Multilamellar vesicle systems, engineered to optimize lipid packing density and hydrophilic‐lipophilic balance, not only boost the moisturizing capabilities of the materials but also enhance their mechanical robustness.[ 73 ] Yet, their preparation often involves complex processes and high production costs.

Recent advancements in drug delivery have been achieved through innovations in lipid‐based carrier technology. For example, novel lipid‐based nanoparticles can extend the release duration of active compounds and deliver antimicrobial peptides or anti‐inflammatory agents directly to the dermis, achieving a synergistic effect in combating infections and promoting wound healing.[ 74 ] In spite of it, encapsulation efficiency and drug loading capacity remain limited for many hydrophilic agents. Encapsulating siRNA within ionizable lipid nanoparticles enabled efficient penetration of the epidermal barrier for targeted gene editing. This approach provides a promising precision therapy for immune‐related skin disorders such as psoriasis.[ 75 ] Still, immunogenicity, off‐target effects, and long‐term safety of lipid‐nanoparticle complexes are major concerns. Additionally, researchers have leveraged AI and combinatorial chemistry techniques to accelerate the rational design of ionizable lipids for mRNA delivery.[ 76 ]

In addition to the aforementioned primary materials, natural skin‐related biomaterials increasingly utilize nucleic acid‐based systems and mineral components for distinct functional applications. Nucleic acid platforms focus on oligonucleotide delivery and cellular modulation through structures like enzyme‐responsive hydrogels and framework nucleic acids.[ 35 , 77 ] In parallel, mineral‐based systems address physical protection, drug carrier design, and tissue‐engineered scaffolds via inorganic‐organic hybrids such as clay‐polymer composites.[ 78 , 79 , 80 , 81 , 82 , 83 , 84 ] Nucleic acid‐based biomaterials have emerged as powerful platforms for targeted delivery. For example, hydrogels engineered with specific enzyme‐responsive sites enable the controlled, cascaded release of siRNA‐aptamer complexes.[ 35 ] Framework nucleic acids are capable of addressing the difficulty of oligonucleotide penetration across the skin barrier. The tetrahedral DNA structure serves as an efficient delivery system for miRNA, modulating the proliferation of keratinocytes.[ 77 ] Nucleic acid‐based materials, however, face challenges including nuclease degradation, limited cellular uptake, and potential immunogenicity. Their high cost and complex synthesis also pose barriers to widespread use.

As abundant inorganic components in nature, minerals exhibit excellent physicochemical stability and support the design of multifunctional skin treatment platforms attributed to their unique biological roles.[ 78 ] Minerals can influence the skin microenvironment in various ways. For example, mineral‐based sunscreens such as zinc oxide and titanium dioxide protect by reflecting ultraviolet light.[ 79 ] Mineral carriers loaded with active ingredients, like apatite particles used for localized drug delivery, can promote skin therapeutic efficacy.[ 80 ] Some specialized mineral blends, such as those from the Dead Sea, have been shown clinically to improve skin conditions. These improvements involve key processes like regulating skin redox balance and enhancing barrier function.[ 81 , 82 ] In tissue engineering, combining clay minerals with natural polymers such as montmorillonite with chitosan, improves the mechanical properties and biocompatibility of scaffold materials, aiding in the creation of biomimetic skin substitutes.[ 83 , 84 ] Mineral‐based materials, while stable and multifunctional, often lack biodegradability and may accumulate in tissues. Their rigidity and brittleness can limit applicability in flexible skin interfaces, and some metal oxides may generate reactive oxygen species (ROS) under certain conditions, leading to unintended cytotoxicity.

2.2. Synthetic Biomaterials

Advances in synthetic materials are facilitating more progress from foundational research to clinical practice. By employing strategies such as biomimetic design, hierarchical structural tuning, and multifunctional integration, these materials effectively tackle critical issues in skin treatment, including mechanical compatibility, dynamic responsiveness, and bioactivity modulation.[ 16 , 85 ] Notably, polymer‐based systems have advanced significantly in precisely engineered viscoelasticity, interfacial biocompatibility, and molecular‐level customization. This allows tailored adjustment of mechanical parameters to match native tissue characteristics while enhancing structural innovation, mechanical robustness, and in vivo durability – achieving functional integration without compromising therapeutic performance.[ 16 , 86 , 87 , 88 ] Synthetic nanomaterials exhibit several beneficial properties for skin‐related applications, such as a high surface‐area‐to‐volume ratio, the ability to tailor surface functionalities, and minimal disruption to the skin's natural barrier function. Their unique capabilities have proven particularly advantageous in transdermal DDSs and the development of advanced functional skin substitutes.[ 89 ] Moreover, novel synthetic material systems that combine multiple functionalities are broadening the application landscape of skin‐related biomaterials.[ 90 , 91 ] Despite their tunability and reproducibility, synthetic biomaterials often exhibit limited bioactivity and may provoke foreign body responses or chronic inflammation. Their degradation byproducts can sometimes cause adverse reactions, and it remains challenging to achieve optimal integration with dynamic biological environments.

Research on innovative polymer materials has advanced mechanical adaptability, dynamic responsiveness, and biocompatibility. By integrating structural design across molecular and macroscopic scales, these materials enhance functionality for skin tissue repair and regeneration. For example, interpenetrating polymer networks that integrate fibrin networks with mechanically enhanced polymers, such as poly(ethylene glycol) (PEG) derivatives, creates structures with both high elasticity and the ability to deliver bioactive signals.[ 92 ] The architecture of these materials closely mimic the layered structure of natural skin, thus promoting cell infiltration and angiogenesis. This design enables precise microenvironment modulation in deep wounds, overcoming the mechanical mismatch issues that frequently limit traditional materials and preventing secondary damage. Still, the complexity of fabrication and the risk of delamination under dynamic mechanical loads pose challenges to their practical use.

Regarding functional innovation, a key trend involves combining conductive polymers with bioactive molecules. Hierarchical polymer systems, developed by combining conductive polymers with elastomers, have enabled the creation of e‐skin that are not only pressure‐sensitive but also possess antibacterial properties. This design replicates the multi‐layered sensory mechanisms of human skin while enhancing sensitivity to external stimuli through nano‐scale surface patterning.[ 93 ] However, many conductive polymers exhibit limited biostability and may release toxic monomers or oligomers under prolonged physiological conditions. Additionally, polylactic acid (PLA), poly(lactide‐co‐glycolide) (PLGA), and polycaprolactone (PCL) have long been under investigation for skin regeneration due to their excellent mechanical stability and processability.[ 94 , 95 , 96 ] Nonetheless, their acidic degradation products can also drop local pH, leading to inflammatory responses and impaired tissue regeneration.

Structural optimization enables polymer materials to achieve tailored performance characteristics. For instance, an elastic and wearable crosslinked polymer layer based on polysiloxane exhibits tailored elasticity, contractility, adhesion, tensile strength, and bite resistance. It can rapidly cure at the skin interface without thermal or light‐mediated activation, providing advanced solutions for restoring compromised skin barrier function, drug delivery, and wound dressing applications.[ 16 ] Supramolecular polymer nanogels, which utilize host‐guest interactions, significantly enhance drug permeability. Compared to traditional cream formulations, these nanogels can increase drug penetration into the skin by up to ninefold.[ 97 ] Yet, their stability in complex biological milieus and the potential for premature dissociation before reaching the target site require further improvement.

Hydrogels have been widely adopted in skin‐related biomaterials owing to their tunable physicochemical properties and tissue‐like characteristics.[ 17 , 98 ] Their distinctive 3D network architecture and high water content endow them with properties resembling human soft tissues, showcasing exceptional biocompatibility and adaptability. However, many hydrogels suffer from poor mechanical strength, rapid erosion, and limited capacity to adhere firmly to wet and moving skin surfaces. By fine‐tuning intermolecular interactions and microstructural features, hydrogels not only replicate the physical attributes of human tissues, but also enhance mechanical toughness and extend their residence time within the body.[ 99 , 100 ] Even so, achieving a balance between enhanced mechanics and desired porosity or degradation rate remains difficult. Recent innovations in hydrogel design have enhanced their biocompatibility, biointegration, and mechanical properties. For example, hydrogels containing polylysine, leveraging its cationic characteristics and multifunctional designs, achieve synergistic enhancements in antibacterial activity, gene delivery, and mechanical properties, underscoring its promise in skin regeneration.[ 101 ] However, cationic polymers can also exhibit dose‐dependent cytotoxicity and may interfere with normal cellular functions.

Notably, an injectable thermogelling system (T‐gel) composed of poly(D,L‐lactide‐co‐glycolide)‐b‐poly(ethylene glycol)‐b‐poly(D,L‐lactide‐co‐glycolide) (PLGA‐PEG‐PLGA) triblock copolymers has been developed, which undergoes sol–gel transition upon heating and can be administered via ultra‐fine microneedles.[ 102 ] This system forms a physical hydrogel in situ after intradermal injection and degrades over weeks, releasing lactic acid that stimulates collagen I and III synthesis via the transforming growth factor beta (TGF‐β)/Smad pathway, promoting moderate and balanced collagen regeneration without scarring risk (Figure 3 ).[ 102 ] The development of dynamic hydrogels has facilitated interactions between materials and human tissues. Inspired by natural systems, dynamic hydrogels incorporating reversible hydrogen bonds, host‐guest interactions, or enzyme‐responsive crosslinking mechanisms enable functions such as stress relaxation, self‐healing, and controlled degradation.[ 85 ] Functional integration strategies have further expanded the application potential of hydrogels. Antibacterial functionality has evolved beyond simple antimicrobial agent loading to encompass synergistic combinations of multiple antimicrobial strategies.[ 103 , 104 ] Nonetheless, the overuse of antimicrobial components raises concerns about microbial resistance and disruption of the native skin microbiome. Responsive hydrogels, designed with pH‐sensitive groups or temperature‐responsive block copolymers, enable precise on‐demand drug delivery and modulation of inflammatory microenvironments.[ 105 ] Yet, the reliability of these responses under the complex and fluctuating conditions of real wounds requires further validation.

Figure 3.

Figure 3

An injectable thermogel (T‐gel) for enhancing skin appearance. The polymeric block blend solution is delivered into the dermal layer using microneedles, undergoing a swift transition into a physical gel at the site. In the following weeks, as the gel degrades, it steadily releases lactic acid (LA), eliciting biological responses that stimulate fibroblast activity and drive moderate collagen regeneration. Reproduced from Ref. [102] with permission of Wiley, 2025.

Nanoparticle‐based biomaterials, owing to their high specific surface area, tunable surface functionalization capabilities, and compatibility with the skin tissue microenvironment, demonstrate unique advantages in the development of skin wound repair systems, transdermal drug delivery platforms, and functional skin substitutes (Figure 4 ).[ 106 , 107 ] By precisely controlling parameters such as charge distribution and mechanical modulus, nanomaterials can effectively mimic key physical and chemical properties of the skin microenvironment.[ 108 , 109 ] This capability promotes cell adhesion, proliferation, and differentiation while enhancing the efficiency of localized therapeutic agent delivery and enabling controlled release. For instance, through active modulation of mechanical properties, nanomaterials facilitate cellular reprogramming, enabling scar‐free tissue regeneration.[ 110 ] Optimization of nanoparticle's physicochemical parameters (size/charge/topology) directly enhances drug targeting in diseased skin.[ 111 , 112 ] Nonetheless, the dynamic nature of skin physiology, such as varying pH, moisture, and enzyme activity, can alter nanoparticle behavior and reduce targeting efficacy. Additionally, a Pickering foam system stabilized by nanoparticles achieves spatiotemporal control over drug release rates via interfacial tension modulation, contributing to the maintenance of skin barrier stability.[ 113 ]

Figure 4.

Figure 4

Nanomaterial‐based approaches for preventing and reducing scar formation. Reproduced from Ref. [106] with permission of Springer Nature, 2023.

Beyond conventional protective and therapeutic functions, nanotechnology innovations have propelled the emergence of stimuli‐responsive nanobiomaterial systems capable of autonomously modulating their functionality according to pathophysiological cues. These intelligent systems achieve spatiotemporal control over therapeutic actions through precisely engineered responses to biological signals. A representative example involves melanin‐mimetic nanomaterials that harness photothermal conversion efficiency and dynamic ultraviolet absorption/radical scavenging capacities, enabling the creation of bioinspired epidermal interfaces with adaptive photoprotection.[ 7 ] Yet, long‐term exposure to photothermal agents could potentially lead to skin sensitivity or thermal damage under certain conditions. In targeted drug delivery for melanoma, pH‐responsive nanocarriers overcome the systemic toxicity limitations of conventional chemotherapy, significantly increasing local drug concentrations and expanding the therapeutic window.[ 114 ]

In the field of skin‐inspired electronic devices, nanomaterials have shown exceptional promise. For instance, combination of carbon nanotubes and microstructured elastomers enables the development of flexible e‐skin with high sensitivity and a broad strain‐response range. Their piezoresistive properties allow real‐time monitoring of physiological signals such as pulse and joint movement.[ 115 ] Nanomaterials based on conductive polymers and 2D materials achieve conductivity and stretchability comparable to natural skin, enabling these biomimetic materials to sense mechanical stress and respond to electrophysiological signals.[ 116 , 117 ]

A novel class of synthetic material systems has been developed through biomimetic design, hierarchical structural modulation, and multifunctional integration strategies. These materials offer novel solutions to address critical challenges in skin‐related applications, such as mechanical adaptability, dynamic degradability, precise control of bioactivity, and antimicrobial performance.[ 90 , 91 , 118 , 119 ] For instance, synthetic clay‐based dressings utilizing laponite leverage the cation‐exchange capabilities of their layered structure to dynamically adsorb wound exudates while enabling sustained release of growth factors, making them ideal in skin surface therapy.[ 118 ] Nevertheless, synthetic clay and other inorganic composites may exhibit poor biodegradability and limited biological activity. Their integration with organic tissues remains elusive, and long‐term safety profiles are often not well established. Additionally, some inorganic particles may accumulate in the skin or regional lymph nodes, leading to unforeseen complications.

2.3. Composite Biomaterials

Composite biomaterials designed for skin‐related applications are among the most extensively investigated areas in biomaterials research in recent years. By integrating bioactive components, biomimetic structural designs, and intelligent functionalization strategies, these materials achieve a multi‐level replication of the natural skin microenvironment. They not only facilitate the regulation of cell behavior and tissue regeneration but also exhibit outstanding mechanical properties and dynamic responsiveness, offering innovative platforms for skin repair, disease monitoring, and therapeutic interventions.[ 120 , 121 ] Various compositing approaches have significantly enhanced the adaptability and functionality of these materials in complex physiological settings, underscoring their vast potential for future applications.[ 122 , 123 ] Nevertheless, the complexity of these systems also complicates regulatory approval pathways and scale‐up manufacturing processes.

Bioactive composites integrate components of bioactivity, such as some natural or synthetic polymers and growth factors, with functional carriers to replicate the skin microenvironment for therapeutic purposes. For instance, composite systems incorporating porous hydrogels and antimicrobial nanoparticles support cell migration and suppress infections through controlled drug release, achieving an integrated approach to treatment and regeneration.[ 124 ] However, the burst release of antimicrobial agents or growth factors from such composites can lead to transient overdosing or premature depletion of bioactivity. Bioactive glass composites containing gold nanoparticles accelerate angiogenesis in skin defect models by modulating vascular signaling pathways.[ 125 ] Yet, the potential migration and accumulation of non‐degradable nanoparticles in surrounding tissues raise concerns about long‐term safety. A particulate hydrogel derived from decellularized tilapia skin addresses the limitation of traditional hydrogels' nanopores restricting cell infiltration, promoting directional migration of fibroblasts and enhancing angiogenesis.[ 126 ] Despite this, immune responses to residual xenogeneic antigens, though reduced by decellularization, cannot be entirely ruled out.

Biomimetic structural composites, inspired by the multi‐layered architecture and mechanical characteristics of natural skin, achieve optimized mechanical performance and biological functionality through hierarchical structural engineering. For example, composite materials mimicking the “brick‐and‐mortar” structure of nacre maintain high strength while enhancing toughness through interfacial slip mechanisms, providing a robust substrate for flexible e‐skin applications.[ 127 ] Layered composites formed by hybridizing nanocellulose with graphene replicate the nano‐gradient structure of the epidermal‐dermal interface, offering flexibility while providing excellent electrical conductivity. This design is particularly well‐suited for the development of e‐skin devices with integrated pressure‐sensing functionality and high breathability.[ 90 ] A significant drawback, however, is the potential for graphene layers to fracture under extreme bending, compromising conductivity and device integrity. 3D printed fiber reinforced composites emulate natural fibrous architectures by engineering a hierarchical structure. This design leverages strong fiber‐matrix adhesion combined with inherently weak interfaces between intermediate filaments to synergistically enhance both strength and toughness through localized heterogeneity.[ 128 ] However, achieving precise alignment and distribution of fibers in large‐scale manufacturing remains a significant technical hurdle.

Functionalized intelligent composites integrate dynamic response units, such as conductive nanomaterials and stimuli‐responsive polymers, endowing skin substitutes with sensing, self‐healing, and adaptive capabilities. For instance, a supramolecular biomimetic skin material achieves multisensory perception of external stimuli, including temperature, strain, and stress via ion conduction, while its dynamic network structure supports for self‐healing and environmental adaptability.[ 129 ] Composite materials based on porous covalent organic frameworks, loaded with metal nanoparticles or enzyme molecules, enable highly sensitive biomarker detection, offering real‐time feedback for chronic wound management.[ 130 ] The main limitations include the potential leaching of metal ions and the susceptibility of enzymes to denaturation under wound pH and temperature fluctuations. Ionogel composites featuring rigid skeletons and ionogel matrix precisely replicate the mechanical anisotropy and nonlinear mechanical responses of human skin, while exhibiting room‐temperature self‐healing properties, making them ideal for wearable health monitoring applications.[ 10 ] Nevertheless, the long‐term stability of the ionic liquid components and their potential skin irritation effects require thorough investigation before clinical use.

Furthermore, functionalized intelligent composites based on active bio‐integrated electronic devices integrate bioactive hydrogels, bioelectronic components, and bacteria to achieve synergy among bioactivity, biomechanical performance, and bioelectrical functions. This advanced composite material can monitor electrophysiological signals and environmental parameters in real time while modulating the immune environment of inflammatory skin conditions through bioactive bacteria, demonstrating significant potential for disease diagnosis and treatment (Figure 5 ).[ 11 ] However, the incorporation of live bacteria introduces significant regulatory and safety challenges. Despite their advanced functionalities, intelligent composites often face challenges because combining multiple advanced functionalities can result in trade‐offs, where optimizing one property (e.g., electrical conductivity) may compromise another (e.g., biodegradability or biocompatibility).

Figure 5.

Figure 5

Composite biomaterials used in bioelectronics devices. A) A schematic representation shows the capability of living bioelectronics in facilitating the gathering of information, diagnosing diseases, and delivering therapeutic treatments. B) The interplay among bioelectronics, hydrogel, and bacteria across three key dimensions is crucial for the functionality of biointegrated living electronics. The basic procedure is as follows: 1) Biopolymers enhance bacterial survival; 2) Bacteria regulate the skin's immune microenvironment; 3) Bioelectronics gather skin‐related information via electrical sensing (e‐sensing); 4) Bioelectronics ensure bacterial safety through electrical stimulation (e‐stimulation); 5) Hydrogel encapsulation supports long‐term bacterial storage and viability; 6) The viscoelastic properties of the living hydrogel ensure stable integration with skin tissue; 7) The hydrogel's viscoelasticity aids in efficient data collection from the skin; 8) The biomechanical characteristics of the hydrogel assist in managing potential biohazards; 9) The hydrogel's skin‐adhesive properties enhance prolonged data acquisition. C) In contrast to traditional bioelectronics interfaces, active biointegrated living electronics integrates functionalities spanning bioelectrical, biomechanical, and biogenic domains. Reproduced from Ref. [11] with permission of the American Association for the Advancement of Science, 2024.

Composite biomaterials also face challenges that have limited their clinical translation. The interface between natural and synthetic components often represents a weak point, leading to delamination or unpredictable degradation profiles. The manufacturing processes for composites are typically more complex and expensive than for single‐material systems, creating barriers to scalability and commercialization. Additionally, the biological response to composite materials is difficult to predict, as the body may respond differently to each component, potentially leading to conflicting immune reactions or uneven tissue integration. Some composite systems that showed excellent performance in laboratory settings have failed in clinical trials due to these interface issues, manufacturing inconsistencies, or unexpected biological responses.[ 131 , 132 , 133 ] These failures underscore the need for better interface engineering, more reproducible fabrication methods, and improved predictive models for biological responses.

3. Applications of Biomaterials in Skin‐Relevant Cases

The application of biomaterials in skin treatment has transitioned from basic physical support and passive repair to advanced multifunctional platforms that incorporate dynamic responsiveness, intelligent modulation, and precise intervention.[ 119 , 134 , 135 ] By leveraging the bioactivity of natural materials, the programmability of synthetic materials, and the synergistic effects of composite systems, biomaterials have found widespread use in wound healing,[ 136 , 137 , 138 ] tissue engineering,[ 139 , 140 , 141 ] drug delivery,[ 142 , 143 , 144 ] dermatological therapies,[ 145 , 146 ] medical aesthetics,[ 147 , 148 ] sensing and monitoring,[ 149 , 150 ] and surgical applications.[ 151 ] These multidimensional advancements have not only significantly improved treatment efficacy but also facilitated a shift toward personalized, minimally invasive, and functionalized approaches in skin care.[ 152 , 153 ] This evolution highlights how biomaterials are overcoming the limitations of conventional therapies and enabling proactive, long‐term management of skin health through interdisciplinary collaboration and technological breakthroughs.

3.1. Wound Healing

Modern wound management faces two central challenges: 1) the dynamic regulation of complex pathological microenvironments such as infection, ischemia, and excessive inflammation;[ 154 , 155 , 156 ] 2) the precise orchestration of tissue regeneration and functional restoration.[ 110 , 155 , 157 , 158 ] Biomaterials have enabled active modulation of the wound microenvironment via multifunctional synergistic design.[ 159 , 160 , 161 , 162 , 163 , 164 ] Their role has evolved from merely providing physical barriers to forming comprehensive therapeutic systems that integrate multiple functionalities,[ 19 , 165 , 166 ] as schematically indicated in Figure 6 .

Figure 6.

Figure 6

Biomaterials for wound healing applications. A) Different types of materials (such as nanoparticles/microparticles, bioscaffolds, bioelectronic materials, and stimuli‐responsive materials), used in chronic wound healing. B) Key material properties (such as strong tissue adhesion and on‐demand, gentle removal (i.e., easy adhesion/removal)), that play critical roles in regulating cellular functions and therapeutic outcomes. C) Materials engineered to achieve specific functionalities. D) Different therapeutic approaches currently in use. FBR, foreign body response. Reproduced from Ref. [19] with permission of Springer Nature, 2024.

Smart dynamic dressings deliver on‐demand treatment by responding to changes in the wound microenvironment. Multifunctional hydrogel‐based dressings achieve controlled drug release, self‐adaptive mechanical properties, and antibacterial‐anti‐inflammatory synergy through photopolymerization, dynamic covalent bonds, or stimuli‐responsive components (e.g., temperature/pH‐sensitive materials), etc.[ 167 , 168 , 169 ] For example, a self‐regulating composite hydrogel can release copper ions and antioxidants triggered by light, simultaneously suppressing infection and accelerating epithelialization.[ 167 ] Mechanically active dressings generate contractile forces via self‐shrinking hydrogels, promoting wound closure, modulating cell behavior (e.g., proliferation, differentiation, and migration), and influencing immune responses (e.g., macrophage polarization), thereby significantly reducing the healing time of chronic wounds.[ 170 ]

In order to engineer vascular networks, biomaterials are developed to promote functional angiogenesis. A dressing composed of anti‐inflammatory polycitrate‐polyethyleneimine‐ibuprofen and a multifunctional F127‐ε‐polypeptide‐alginic matrix is designed with temperature‐responsive gelation, injectability, and antibacterial properties. Here, F127 is an amphiphilic block copolymer composed of poly(ethylene oxide) and poly(propylene oxide). This dressing accelerates wound healing, minimizes scar formation, and promotes hair follicle regeneration by regulating macrophage polarization and immune cell phenotypes.[ 171 ] Silicon‐based nanocomposite scaffold materials, loaded with pro‐angiogenic factors like vascular endothelial growth factor (VEGF), reconstruct microvascular networks in wounds with insufficient angiogenesis such as ulcers.[ 172 ] The designed biomaterials enhance oxygen/nutrient delivery and tissue regeneration by modulating endothelial cell migration and ECM remodeling.[ 172 , 173 ] The spatiotemporal control of growth factor releases to mimic natural angiogenic cues and preventing off‐target effects or excessive vessel formation are critical aspects needing refinement.

Scar‐to‐regeneration transition depends upon balancing between regenerative capacity and fibrotic propensity during tissue repair. Hydrogel materials mimic the mechanical properties of skin, deliver anti‐fibrotic factors such as interleukin‐10 (IL‐10), or modulate macrophage phenotype polarization to inhibit excessive fibroblast proliferation and abnormal collagen deposition.[ 156 , 157 ] However, achieving long‐term modulation of the complex fibrotic cascade and ensuring the stability of delivered biologics in the harsh wound environment are non‐trivial tasks. Silicate‐based bioactive materials facilitate scar‐free tissue regeneration through integrin‐mediated signaling activation.[ 157 ] Citrate‐based dressings with anti‐inflammatory, antibacterial, and hemostatic properties suppress the pathway of TGF‐β/Smad to reduce hypertrophic scarring.[ 171 ] Active contraction and antioxidant hydrogels with biomimetic mechanical functions reshape the repair microenvironment through dual mechanical‐biochemical signaling, enabling near‐scarless skin regeneration.[ 156 ] A novel regeneration‐directing artificial skin system based on programmable DNA hydrogels that effectively promotes scarless wound healing and regenerates multiple skin appendages such as hair follicles, sebaceous glands, and sweat glands.[ 158 ] While highly promising, the scalability, cost, long‐term stability, and potential immunogenicity of DNA‐based hydrogels represent significant challenges for clinical translation and widespread application.

3.2. Tissue Engineering

In the field of tissue engineering, increasing specifically designed biomaterials arose for skin regeneration, particularly in the areas such as full‐thickness skin reconstruction, neural sensory restoration, and skin organoid engineering. These advanced materials, designed with biomimetic principles, not only restore the skin's barrier function but also enable dynamic sensory perception and precise regenerative control, providing innovative solutions for complex wound repair.[ 174 , 175 ]

For full‐thickness skin reconstruction, researchers have employed a stratified functionalization approach to create biomaterials that replicate the structural hierarchy of the epidermis, dermis, and subcutaneous layers. For example, an integrated engineered skin construct combining photocrosslinkable hydrogels with cell sheet technology has demonstrated the ability to promote vascular network formation while minimizing excessive fibrosis, significantly improving repair outcomes for full‐thickness defects.[ 176 ] Similarly, a polydopamine‐modified decellularized bilayer scaffold effectively mimics the dermal and basement membrane architecture, serving as an advanced implant for full‐thickness wounds.[ 177 ] Additionally, a 3D‐printed multifunctional bilayer scaffold incorporating apoptotic extracellular vesicles and antimicrobial coacervates has been developed to guide directional cell migration, facilitate ordered differentiation, and achieve synchronized regulation of collagen deposition and angiogenesis.[ 178 ]

Neural sensory interface research has developed biomimetic designs and bioengineering strategies to replicate the skin's tactile sensing capabilities.[ 179 , 180 , 181 ] A representative biomimetic device mimics the epidermal‐dermal interface's interlocking structure, utilizing triboelectric effects and multilayer neural networks to achieve low‐latency distributed tactile perception. Its sensitivity approaches natural skin mechanoreceptors.[ 181 ] Separately, engineered skin grafts incorporating Merkel cells and sensory neurons have demonstrated in vitro self‐assembly and in vivo integration capabilities.[ 179 ] The survival, functional maturation, and stable synaptic connectivity of these incorporated neural components within the dynamic wound healing environment, as well as potential immunogenicity concerns with cellular components, present significant obstacles to clinical translation.

3.3. Drug Delivery

The barrier characteristics of the skin pose challenges for the design of pertinent DDSs.[ 182 ] Recent advances in biomaterial‐based drug delivery technologies have markedly enhanced drug permeation efficiency, targeting precision, and overall safety by refining material functionality and optimizing delivery mechanisms.[ 182 , 183 ] These biomaterial platforms allow for the controlled and sustained release of therapeutics via transdermal delivery. The transdermal DDSs offer significant advantages over conventional methods such as oral administration and injections, where the former one is limited by first‐pass metabolism and the latter one can cause immense pain leading to poor patient compliance.[ 184 , 185 ] Continued development of these transdermal DDSs holds great promise for broadening the therapeutic applications of both small molecules and increasingly complex biologics.

A key area of progress lies in physical enhancement and intelligent delivery systems. Technologies such as microneedles and iontophoresis have emerged as pivotal innovations in transdermal drug delivery, enabling the penetration of the stratum corneum through minimally invasive approaches. For instance, responsive gel‐based microneedles can dynamically modulate drug release in response to skin microenvironmental factors, such as pH or ROS levels, making them particularly effective for the long‐term management of chronic inflammatory conditions like psoriasis.[ 186 ] Complementary smart delivery platforms employing external stimuli like ultrasound or electric fields provide precise temporal control of drug release, establishing non‐invasive treatment modalities particularly valuable for deep‐seated skin tumor therapy.[ 187 , 188 ] Notably, a groundbreaking example is a thermoresponsive hydrogel based on PLGA‐b‐PEG‐b‐PLGA triblock copolymers, which undergoes temperature‐induced sol–gel‐sol(suspension) phase transitions to form an asymmetrical structure with a gel exterior and sol interior.[ 189 ] This material exploits the temperature gradient between ambient air and body heat to achieve biphasic transitions, ensuring both drug stability on the skin surface and accelerated transdermal delivery of 5‐aminolevulinic acid (ALA). This platform has shown remarkable efficacy in photodynamic therapy, exemplifying the significant potential of smart soft materials for advanced transdermal drug delivery applications (Figure 7 ).[ 189 ]

Figure 7.

Figure 7

Hydrogels for drug delivery. A thermogel encapsulates the drug ALA. The aqueous system of the amphiphilic block copolymer undergoes sol–gel‐sol transitions upon heating. The T air‐T skin temperature difference is employed to generate asymmetry of the resultant physical hydrogel across a transdermal patch: a hydrogel layer on the air side to avoid flowing on skin and a sol layer near the skin to enhance the ALA release to skin surface. Post dermal application, photodynamic therapy is facilitated. Adapted from Ref. [189] with permission of Wiley, 2021.

Another critical direction focuses on multifunctional delivery systems that integrate antibacterial, immunomodulatory, and tissue repair functionalities. For example, biomimetic materials derived from animal tissue ECM can simultaneously act as antibiotic carriers and pro‐healing scaffolds, significantly expediting the regeneration of infected wounds.[ 38 ] ROS‐responsive nanosystems, capable of scavenging excess ROS while releasing immunomodulatory agents, provide innovative strategies for the precise treatment of inflammatory skin disorders.[ 190 ] Some critical areas for ongoing research are optimizing the sensitivity and specificity of ROS responsiveness to pathological levels (avoiding triggering by physiological fluctuations), achieving sufficient payload capacity for therapeutic efficacy, and ensuring the biocompatibility and clearance pathways of nanocarrier components. Furthermore, integrating multiple functions without compromising the efficiency or safety of any individual component, and managing the complexity of co‐delivery kinetics for synergistic effects, remains challenging in material designing and device manufacturing.

3.4. Dermatological Therapies

Recent advancements in biomaterial‐based strategies have shown significant promise in treating skin diseases (Table 2 ), particularly for complex conditions such as atopic dermatitis (AD), psoriasis, and melanoma.[ 191 , 192 , 193 , 194 ] These materials address the limitations of traditional therapies by employing targeted delivery, local microenvironment regulation, and immune response modulation to achieve precise intervention in critical disease pathways. They enhance drug bioavailability while reducing systemic toxicity and can further bolster skin barrier repair through biomimetic designs.[ 193 , 195 , 196 ] The information provided in Table 2 is sourced from ClinicalTrials.gov. (https://clinicaltrials.gov/).

Table 2.

Representative clinical trials of dermatological treatment with biomaterials.

Skin disease Biomaterial type Component Material function Registration number Phase
Dermatitis Polymer Poly(L‐lactide), etc. Drug delivery NCT05535738 III
Atopic dermatitis Hydrogel / Maintaining the skin barrier NCT01065714 IV
Atopic dermatitis Hydrogel / Drug delivery NCT02910011 II
Acute radiation dermatitis Hydrogel Bacterial cellulose, monolaurin Preventing therapy‐induced high‐grade acute dermatitis among filipinos with breast adenocarcinoma NCT05079763 II
Radiation dermatitis Hydrogel Acemannan Moist wound environment NCT04481802 Not applicable
Radiation dermatitis Polymer Polymeric cyanoacrylate Skin protectant NCT03546803 Not applicable
Hand dermatitis Polymer Silicone Hand sanitizer NCT01950494 Not applicable
Psoriasis Hydrogel / Adhesive pad NCT00924950 IV
Psoriasis Hydrogel / Drug delivery NCT00555646 II
Psoriasis Nanomaterial / Drug delivery NCT03004339 I
Melanoma Lipid Liposome Drug delivery NCT05264974 I
Melanoma Nanomaterial Gold nanorods Hyperthermia therapy NCT06894407 II
Melanoma Nanomaterial Super paramagnetic iron‐oxide nanoparticles Radioactive tracer NCT05569707 Not applicable
Melanoma Nanomaterial Gadolinium‐based nanoparticles Radiation therapy NCT04899908 II
Melanoma Nanomaterial/lipid Lipid nanoparticle mRNA delivery NCT03739931 I
Melanoma Polymer Cyclodextrin siRNA delivery NCT00689065 I
Melanoma Polymer Polyoxypropylene, polyoxyethylene Adjuvant NCT00003274 II
Melanoma Polymer Cyclodextrin Drug delivery NCT00333502 II
Squamous cell carcinoma/ Polymer / Tissue repair scaffold NCT02409628 Not applicable
Skin cancer Polymer / Collection of body odor samples NCT06493786 Not applicable
Skin cancer Nanomaterial Bioadhesive nanoparticle Sunscreen NCT05736224 I
Eczema Hydrogel / Drug delivery NCT00924508 Not applicable
Tinea Nanomaterial/lipid Solid lipid nanoparticles Drug delivery NCT03823040 I
Warts Hydrogel / Drug delivery NCT05300009 Not applicable
Pemphigus and pemphigoid Polymer Cellulose acetate Wound dressings NCT02365675 Not applicable
Acne vulgaris/ rosacea Polymer / Cleanser NCT05094700 Not applicable
Acne vulgaris Polymer Pre‐polymers of PPG and PEG Optical clearing agent NCT00580736 I
Acne vulgaris Hydrogel / Vehicle gel NCT02164084 I
Acne vulgaris Hydrogel Xanthan gum, alginate, etc. Immunomodulatory and regenerative properties NCT06925386 II
Acne vulgaris Hydrogel / Vehicle gel NCT02126709 II

Therapeutic approaches leveraging combined antioxidant and anti‐inflammatory actions show particular promise for AD treatment. A multifunctional hydrogel dressing designed with focal adhesion kinase (FAK) inhibition and ROS scavenging has demonstrated effectiveness. This dressing integrates oxidative stress modulation with mechanical signaling blockade, providing a synergistic treatment for AD that markedly reduces skin inflammation and barrier dysfunction (Figure 8A).[ 197 ] Copper/zinc metallic organic frameworks (MOFs) mimic natural antioxidant enzymes, simultaneously clearing ROS and inhibiting pro‐inflammatory cytokine release, breaking the vicious cycle of oxidative stress and immune imbalance seen in AD.[ 193 ] Additionally, temperature‐sensitive nanoparticles based on poly(N‐isopropylacrylamide) enable sustained transdermal release of the anti‐inflammatory peptide YARA with sequence of YARAAARQARAKALNRQGLVAA, significantly lowering the risk of skin atrophy associated with conventional glucocorticoids.[ 195 ] Another innovative approach involves an active biological dressing created by integrating skin commensal bacteria with hydrogels composed of poly(vinyl alcohol) and sodium alginate, which restores microbial homeostasis in AD patients while promoting barrier repair, offering a novel pathway for microbiome‐host interaction modulation.[ 196 ]

Figure 8.

Figure 8

Biomaterials for dermatological treatments. A) Schematic representation of a hydrogel designed for treating atopic dermatitis. The left diagram illustrates the condition's inflammatory response triggered by oxidative stress and the worsening effects of mechanical scratching. The right diagram shows how the hydrogel dressing works to alleviate atopic dermatitis by eliminating ROS and inhibiting FAK phosphorylation. Reproduced from Ref. [197] with permission of Springer Nature, 2023. B) A topical treatment using poly(2‐dimethylaminoethyl methacrylate) (PDMA) grafted cSPs for psoriatic skin through cfDNA scavenging. These particles, with improved penetration and extended retention, effectively remove local cfDNA, suppressing inflammation driven by cell‐free DNA in psoriasis. IMQ, imiquimod. Reproduced from Ref. [198] with permission of Elsevier, 2021.

In psoriasis management, efforts focus on combining interventions across multiple pathways. Cationic hairy silicon particles (cSPs) are engineered to target cell‐free DNA (cfDNA) in the skin. By optimizing particle charge and size, these cSPs effectively suppress localized inflammation, with 700 nm‐sized particles showing prolonged skin retention and superior therapeutic outcomes (Figure 8B).[ 198 ] Topical delivery systems incorporating tapinarof, an agonist of aryl hydrocarbon receptor, modulate epidermal inflammation and oxidative stress pathways, significantly decreasing key cytokines, particularly IL‐17 and IL‐23.[ 199 , 200 ] Novel nanocomposite hydrogels loaded with Janus kinase (JAK) inhibitors and anti‐IL‐17 antibodies block abnormal keratinocyte proliferation, achieving substantial reductions in lesion area in animal models without systemic immunosuppression.[ 201 ] Such multi‐targeted approaches tackle the challenges posed by the intricate immune network in psoriasis, but their complexity significantly increases development and manufacturing costs, and potential drug‐drug interactions within the formulation need careful evaluation.

Biomaterials show great potential in improving the specificity and precision of immunotherapy for melanoma. Biomimetic antigen‐presenting scaffolds facilitate efficient delivery of tumor‐associated antigens and promote dendritic cell maturation, significantly boosting T‐cell response intensity.[ 202 ] Sustained‐release microspheres based on PLGA prolong the local concentration of anti‐programmed cell death protein 1 (anti‐PD‐1) antibodies while minimizing systemic exposure‐related adverse effects such as colitis caused by immune checkpoint inhibitors.[ 203 ] Furthermore, magnetic‐responsive nanocarriers enable spatiotemporally controlled release of Toll‐like receptor (TLR) agonists and radiotherapy sensitizers, enhancing tumor immunogenic cell death and reshaping the immunosuppressive microenvironment.[ 203 , 204 ] These developments highlight the promising role of biomaterials in advancing melanoma therapy. Nevertheless, overcoming key translational barriers such as scalable manufacturing of complex scaffolds, precise control over sustained release kinetics, and reliable deep‐tissue targeting with magnetic systems remains critical for achieving durable clinical efficacy across diverse patient populations.

3.5. Medical Aesthetics

The field of biomaterials for skin applications is rapidly advancing in medical aesthetics and cosmetics, with an increasing focus on functionalized regeneration and sometimes related to mesenchymal stem cells (MSCs). More biomaterials are being discovered and developed for use in medical aesthetics, progressing toward clinical applications (Tables 3 and  4 ). The information is sourced from ClinicalTrials.gov. (https://clinicaltrials.gov/). Some key priorities in medical aesthetics include anti‐aging, barrier repair, and pigment metabolism regulation.[ 205 , 206 , 207 , 208 ] Rather than merely providing static structural support, novel biomaterials are designed to actively modulate the skin microenvironment through various mechanisms, such as promoting collagen regeneration to achieve long‐lasting rejuvenation effects.[ 209 , 210 , 211 , 212 ] For example, a thermosensitive block copolymer composed of biodegradable PLGA and PEG undergoes sol–gel transition upon injection, forming a physical hydrogel that releases lactic acid sustainably through gradual degradation; lactic acid further activates fibroblasts via the TGF‐β/Smads signaling pathway, stimulating balanced synthesis of collagen types I and III, thereby achieving tissue remodeling without excessive scarring.[ 102 ] Such materials not only enhance aesthetic outcomes but also significantly contribute to overall skin health.

Table 3.

Representative clinical trials of medical aesthetics with natural biomaterials.

Biomaterial/treatment Study Aim Registration number Phase
Hyaluronic acid (HA) based
HA To compare different molecular‐weight HA as therapy for xerotic skin in the elderly NCT06178367 III
Cross‐linked HA To restore the physiological volumes of the face and body NCT06915402 Not applicable
HA combined with other multiple components To improve facial skin quality, hydration, and skin barrier when combined with heptapeptide‐32, copper peptide CuGHK, palmitoyl tetrapeptide‐7, palmitoyl tripeptide‐5, azelaoyl bis‐dipeptide‐10, K3 vitamin C and HA NCT05932732 IV
Collagen based
Amnion‐derived collagen To smooth skin wrinkles NCT06054646 II
Bovine collagen For facial dermal tissue filling to correct frontal wrinkles NCT06703294 III
Human‐based collagen To treat moderate to severe vertical lip rhytids and/or radial cheek lines NCT01212809 IV
Platelet rich plasma (PRP) based
PRP To treat dark circles under the eyes NCT03114514 Not applicable
PRP + microneedling To rejuvenate facial and hand skin NCT03647917 I
PRP To evaluate scar formation after unilateral cleft lip repair NCT02958306 II
PRP For the treatment of androgenetic alopecia NCT05348343 II
PRP To treat diabetic foot ulcers NCT06680856 II
PRP To treat deep 2nd and 3rd degree burns NCT01843686 I
Platelet rich fibrin (PRF) based
PRF To treat female pattern hair loss NCT06440655 Not applicable
PRF + HA For cosmetic volume restoration of the tear troughs NCT03313934 I
PRF To treat hypertensive leg ulcers NCT01957124 IV
Polynucleotide (PN) based
PN To correct wrinkles and improve skin tones and irregularities (atrophies) on the skin surface NCT04650620 Not applicable
PN To treat dermal tissue defects NCT05239117 Not applicable
PN + HA To improve skin hydration NCT06821867 Not applicable
PN + HA To treat moderate‐to‐severe atrophic post‐acne scars NCT05936437 Not applicable
Elastin System
Elastin + collagen To treat loss of cutaneous substances using skin grafts NCT02090361 III
Tropoelastin To assess persistence and tissue compatibility NCT01466413 I
Tropoelastin polymer cross‐linked with HA To treat striae distensae alba NCT02510768 I
Botulinum toxin (Botox) based
Botox type A To treat sun‐induced wrinkles NCT01032954 IV
Botox type A To treat persistent idiopathic facial pain NCT03462290 II
Botox type A To treat facial flushing NCT02216838 IV
Extracellular vesicle (EV) based
MSC‐derived exosomes To rejuvenate skin NCT05813379 II
MSC‐derived EVs To manage dystrophic epidermolysis bullosa NCT04173650 II
Others
Peptide 144 (A peptide) for treating skin fibrosis in systemic sclerosis NCT00574613 II
N6‐furfuryladenine (A plant hormone) for the treatment of cutaneous photoaging NCT01898182 IV
KB304 (A gene therapy) for correcting moderate to severe wrinkles in the décolleté region NCT06724900 II

Table 4.

Representative clinical trials of medical aesthetics with synthetic biomaterials.

Biomaterial/ treatment Study Aim Registration number Phase
Poly(L‐lactide) (PLLA) based
PLLA To treat moderate to severe nasolabial folds NCT06013332 Not applicable
PLLA To improve the appearance of cellulite NCT05064761 Not applicable
PLLA To treat upper knee skin laxity NCT03487172 Not applicable
PLLA To improve facial wrinkles and skin quality NCT02003833 IV
PLLA + 1565 nm non‐ablative fractional laser To treat striae distensae NCT05827913 Not applicable
Polydioxanone (PDO) based
Subcision + PDO mono‐threads To treat severe atrophic acne scars NCT06227481 II
Calcium hydroxylapatite (CaHA) based
CaHA + ultrasound To restore skin laxity and volume NCT04176068 I
Ultherapy + CaHA To improve lower face skin quality and wrinkles NCT05469516 Not applicable
CaHA particles To treat nasolabial folds NCT01012388 IV
Silicon based
Silicone For preventative scar management NCT01602458 Not applicable
Silicon gel To prevent scar formation NCT01004536 IV
Silicone To treat keloids and hypertrophic scars NCT06909812 III
PCL based
PCL To improve forehead contour NCT06380972 Not applicable
PCL To restore moderate to severe nasolabial folds NCT06885775 II
PCL To treat crow's feet lines NCT06376838 Not applicable
Poly(methyl methacrylate) (PMMA) based
PMMA To treat HIV‐associated facial lipoatrophy NCT02009462 I
PMMA To correct moderate to severe atrophic acne scars NCT01559922 III
PMMA To correct nasolabial folds NCT03299712 Not applicable

Anti‐aging strategies have evolved beyond the traditional physical support provided by fillers, focusing instead on bioactive stimulation to induce endogenous collagen regeneration. For example, PLA/PCL microspheres, recognized as collagen‐regenerating materials, degrade gradually to activate fibroblasts and remodel ECM, significantly enhancing skin density and elasticity.[ 213 , 214 , 215 ] PLLA microspheres, for instance, not only delay cellular senescence within the dermis but also promote the synergistic regeneration of type I and type III collagen, achieving long‐term improvements in skin texture (Figure 9A).[ 213 , 216 ] Nevertheless, the variability in individual degradation rates, inflammatory responses to degradation products, and the potential for nodule formation or granulomatous reactions with certain microsphere formulations remain concerns requiring careful patient selection and technique. Achieving natural‐looking volumization and texture improvement without overcorrection or irregularities also demands significant practitioner skill and experience.

Figure 9.

Figure 9

Biomaterials for medical aesthetics and cosmetic applications. A) PLLA particles used as facial volumizers and their working mechanism. Reproduced from Ref. [216] with permission of Royal Society of Chemistry, 2021. B) An intelligent, paper‐free, sprayable skin mask utilizing an environmentally friendly thermogel, along with its first clinical study. Adapted from Ref. [217] with permission of Wiley, 2022.

For barrier repair and pigment metabolism regulation, innovative materials and technologies have demonstrated unique benefits. A smart spray mask based on thermoresponsive hydrogels forms an asymmetric structure with an outer moisturizing layer and an inner layer that facilitates controlled release of active ingredients. This design addresses the common challenge of balancing hydration with rapid delivery of actives, offering a novel solution for skin barrier repair. When loaded with niacinamide, this material achieves significant skin‐lightening effects in human study, showcasing the potential of intelligent, eco‐friendly materials in pigment regulation (Figure 9B).[ 217 ] Additionally, nanoscale transdermal collagen accelerates fibroblast activation, promotes barrier protein expression, and reduces transepidermal water loss, providing an effective repair strategy for sensitive or photodamaged skin.[ 218 ] In pigment metabolism, the combination of collagen peptides and ascorbic acid derivatives improves uneven skin tone through dual mechanisms of antioxidant activity and collagen synthesis promotion.[ 219 ]

Emerging technologies like exosomes also show great promise in the field of skin rejuvenation and aesthetic medicine. Nanovesicles derived from umbilical cord MSCs inhibit key enzymes involved in melanin synthesis and modulate ECM remodeling to achieve uniform skin tone.[ 220 , 221 ] Furthermore, nanocellulose, with its rich electron‐donating groups on the surface, exhibits antioxidant, whitening, and anti‐aging properties, along with water retention and biocompatibility. It has been applied in injectable hydrogels, offering stable suspension and dispersion for ingredients prone to precipitation and aggregation in cosmetic formulations.[ 222 ] While offering formulation advantages, robust clinical evidence specifically demonstrating superior whitening or anti‐aging efficacy attributable to nanocellulose itself, compared to the active ingredients it carries, is currently limited. The long‐term fate and biocompatibility of nanocellulose particles in vivo, particularly for injectable applications, also require thorough assessment.

3.6. E‐Skin for Sensing and Monitoring

Skin‐interfacing biomaterials have recently established themselves as critical enabling technologies for continuous health monitoring and adaptive sensing with the development of flexible electronics. By emulating the mechanical flexibility, biocompatibility, and multimodal sensory capabilities of human skin, these materials provide innovative pathways for developing high‐performance e‐skin and wearable sensor systems. Current designs focus on biomimetic structures, multi‐material composites, and integrated functional modules to enable real‐time, non‐invasive, and highly precise monitoring of physiological signals, with a growing emphasis on diagnostic applications such as early lesion detection and chronic disease progression tracking.[ 223 , 224 , 225 , 226 , 227 ]

Representative materials include flexible hydrogels, conductive fibers, and hybrid biomaterials. Some conductive hydrogels, which can be engineered to exhibit tissue‐like mechanical properties and excellent signal acquisition capabilities, are used in epidermal sensors for the simultaneous monitoring of temperature, hydration levels, and bioelectrical signals.[ 228 , 229 ] Long‐term stability under varying environmental conditions and potential signal drift remain concerns for some hydrogel formulations. Fiber‐based materials, through microstructural adjustments, respond sensitively to multidimensional mechanical stimuli such as pressure and stretching, offering new solutions for monitoring wound healing progression and detecting pathological skin stiffness associated with fibrosis.[ 230 , 231 ] Achieving consistent sensitivity and durability across large areas and complex curvatures presents an ongoing challenge. Hybrid systems, integrating nanoscale conductive networks with biopolymers, enhance sensor signal‐to‐noise ratios while adding self‐adhesive properties and environmental interference resistance. These attributes make them promising candidates for stable signal acquisition in dynamic physiological environments and facilitate long‐term diagnostic monitoring.[ 232 , 233 ] Additionally, a stretchable organic bioelectronic material based on topological supramolecular networks has been developed, exhibiting both high conductivity and remarkable stretchability. This material supports direct photolithographic patterning and maintains high conductivity without cracking under physiological conditions, making it suitable for low‐impedance, seamless bio‐integrated systems (Figure 10A). This breakthrough enables patterning at cellular feature scales while preserving conductivity under strain, advancing the miniaturization and high‐density integration of bioelectronic devices.[ 136 ] Further development might be toward scalability and cost‐effectiveness of such sophisticated material systems for widespread deployment.

Figure 10.

Figure 10

Biomaterials for skin sensing and monitoring applications. A) Intrinsically stretchable organic electronics for multimodal and conformal biointerfaces. A flexible multielectrode array enables seamless integration with skin tissues, facilitating precise bidirectional interactions. PEDOT, poly(3,4‐ethylene dioxythiophene); PSS, polystyrene sulfonate; PR, polyrotaxane. Adapted from Ref. [136] with permission of the American Association for the Advancement of Science, 2022. B) An integrated system‐level sweat‐permeable wearable electronic device based on the concept of a 3D liquid diode. Contrast between traditional flexible electronics (left) and the permeable electronics (right). The permeable design enhances breathability and sweat management, which improves signal stability, adhesion strength, and wear comfort during perspiration. Reproduced from Ref. [234] with permission of Springer Nature, 2024.

Functional integration is a critical focus for biosensing and monitoring materials. For example, an integrated wearable electronic system using a 3D liquid diode configuration achieves unidirectional sweat pumping from the skin to an outlet via spatially heterogeneous wettability. Its maximum flow rate exceeds the physiological sweat rate during exercise by 4000 times, showcasing excellent skin compatibility, user comfort, and stable signal performance, even in sweaty conditions. This integration improves device breathability and comfort while enhancing signal stability, offering a reliable solution for long‐term health monitoring (Figure 10B).[ 234 ] Self‐powered sensors, leveraging triboelectric or piezoelectric effects to convert mechanical energy into electrical signals, eliminate the need for external power sources, significantly boosting portability and enabling extended monitoring of motility‐related disorders or rehabilitation progress.[ 235 ] Their output signal strength and consistency can be variable depending on user activity and environmental factors, and achieving sufficient power for complex sensing modalities remains challenging.

Multimodal sensing systems allow for highly sensitive detection and analysis of both biomarkers and physical signals, providing multidimensional data for early disease detection and personalized healthcare.[ 229 , 236 , 237 ] For example, solid‐state epidermal sensors designed with ion‐electronic double‐layer hydrogels can continuously monitor water‐soluble analytes (e.g., solid lactate) and water‐insoluble analytes (e.g., solid cholesterol), enabling non‐invasive indirect tracking of blood biomarkers. Their detection sensitivity surpasses traditional electrochemical interfaces by 3 times, highlighting their potential for non‐invasive diagnosis and management of metabolic syndromes or localized skin pathologies.[ 236 ] Translating the high sensitivity demonstrated in controlled settings to robust performance in diverse real‐world scenarios, including variations in skin condition and the presence of interferents, requires extensive validation and refinement.

3.7. Surgery‐Assistant Devices

Skin‐related biomaterials can be integrated into various applications in the surgical field, such as surgical suturing,[ 151 ] tissue adhesion,[ 238 , 239 ] and rapid hemostasis.[ 240 ] The corresponding products are classified by Food and Drug Administration (FDA) into “medical devices” to distinguish with “drugs”. By incorporating biomimetic designs, dynamic responsiveness, and multifunctional integration, these materials have significantly improved surgical outcomes while minimizing the risk of complications, establishing themselves as a vital component of modern surgical practice.

While traditional suturing methods remain a fundamental part of modern surgical practice, tissue adhesives developed from high‐toughness biomaterials are increasingly being recognized as a valuable supplementary option. For example, peptide‐based bioadhesives inspired by mussel adhesive proteins achieve robust bonding on wet tissues through supramolecular interactions.[ 241 ] Asymmetric adhesive hydrogels featuring both adhesive and anti‐adhesive layers offer dual functionality for tissue sealing and postoperative anti‐adhesion. Their unique asymmetric adhesion properties effectively reduce the risk of secondary injuries.[ 242 , 243 ] These materials also regulate the secretion of inflammatory factors, such as tumor necrosis factor‐alpha and IL‐6,[ 242 ] promoting wound healing while avoiding mechanical irritation associated with traditional sutures.[ 242 , 244 ] In the area of hemostasis, absorbable biomaterials designed with nanoscale surface topography and mechanisms to activate coagulation factors demonstrate rapid hemostasis compared to conventional gauze in complex trauma cases. Their porous structures further support tissue regeneration during the healing process.[ 245 , 246 ]

The diverse applications outlined above demonstrate the remarkable capabilities of modern skin‐related biomaterials. Their efficacy is deeply rooted in their ability to engage in sophisticated dialogues with biological systems. Understanding the mechanisms underlying these interactions—how biomaterials modulate the cellular microenvironment and activate specific biological pathways, is crucial for rational design and further optimization. This mechanistic insight forms the foundation upon which next‐generation, intelligent biomaterials are being built.

4. Biomaterial‐Driven Mechanisms in Skin‐Relevant Applications

The core value of biomaterials in skin treatment lies not only in their physical or chemical properties but also in their ability to actively influence skin biological processes through a series of complex regulatory mechanisms.[ 247 ] This modulation stems from their dynamic interaction with the cellular microenvironment, their capacity to target and activate critical signaling pathways, and their precise influence on cellular behavior.[ 248 , 249 , 250 , 251 ] Whether operating at the nanoscale for molecular recognition or transmitting mechanical signals at the macroscale, ideal biomaterials replicate the physicochemical properties of the natural ECM or incorporate external stimuli to reconstruct and enhance the molecular signaling networks required for skin regeneration. This capability drives skin therapies toward greater precision and efficacy, and supports the development of advanced, intelligent treatment approaches.

4.1. Modulation to Cellular Microenvironment

Modern biomaterials have advanced beyond being passive elements that offer physical support; they now serve as active platforms capable of influencing and optimizing these microenvironmental traits.[ 251 , 252 , 253 , 254 , 255 ] In this way, they play a more proactive role in fostering cell growth, differentiation, and functional performance.[ 256 , 257 , 258 , 259 , 260 , 261 , 262 ] Advanced research highlights the creation of smart biomaterials with dynamic responsiveness over space and time. For instance, photoresponsive liquid crystal hydrogels can dynamically adjust matrix stiffness and topography in response to external stimuli, precisely mimicking the spatiotemporal changes in mechanical signaling of ECM.[ 263 ] Similarly, ROS/pH‐responsive hydrogels target the release of anti‐inflammatory or pro‐angiogenic factors, adapting to the acidic and high oxidative stress conditions typical of diabetic wounds.[ 264 ] These “environment‐adaptive” designs not only facilitate precise control over cell migration, differentiation, and paracrine activity but also open new possibilities for smart biomaterial applications, particularly excelling in personalized treatments and regenerative therapies, showcasing significant potential.[ 265 , 266 ]

Regarding modulation of the immune microenvironment, some biomaterials actively regulate macrophage polarization via their intrinsic material properties or by incorporating functional molecules such as cytokine receptor antagonists. This shifts macrophages from a pro‐inflammatory M1 phenotype to a reparative M2 phenotype, breaking the cycle of chronic inflammation seen in conditions like diabetic foot ulcers.[ 29 , 267 ] Crosslinking density and then stiffness of gelatin methacryloyl (GelMA) hydrogels are proved to influence macrophage and fibroblast behaviors: soft GelMA hydrogels with low crosslinking densities (lo‐GelMA) promote macrophage phagocytosis and reparative phenotypes while reducing inflammation and enhancing fibroblast chemotaxis and proliferation, promoting healing and minimizing scar formation; conversely, stiff GelMA hydrogels with high crosslinking densities (hi‐GelMA) intensify inflammatory signals, leading to pro‐fibrotic interactions between macrophages and fibroblasts, resulting in fibrosis and scarring. These mechanisms illustrate how biomaterials drive the dynamic process of skin healing by modulating signaling pathways and cellular behaviors within the microenvironment (Figure 11 ).[ 268 ] Moreover, innovative microporous hydrogels, with their 3D interpenetrating networks, support directed migration of epidermal and dermal cells and achieve synergistic effects by reshaping the immune‐regenerative microenvironment, providing solutions for scar‐free healing in full‐thickness skin defects.[ 269 ] Such immunomodulatory and ECM‐mimetic mechanisms represent highly promising directions for both clinical translation and further investigation, particularly in the context of chronic wound healing and scar suppression.

Figure 11.

Figure 11

Interaction of biomaterials with the cellular microenvironment. Hydrogel crosslinking modulates macrophages and fibroblasts, and their communication, influencing skin tissue regeneration outcomes. Reproduced from Ref. [268] with permission of Springer Nature, 2024.

4.2. Activation of Biological Pathways

By integrating functional molecules or modulating physicochemical properties, biomaterials can selectively activate key signaling pathways involved in skin repair, regeneration, and immune regulation, offering novel strategies for wound‐healing and disease treatment. For example, composite materials made from silk fibroin and sericin enhance the paracrine effects of MSCs by regulating the integrin/phosphatidylinositol 3‐kinase (PI3K)/Akt and glycolysis pathways. This coordination boosts the functions of fibroblasts, endothelial cells, and macrophages, speeding up the reconstruction of the skin microenvironment.[ 270 ] Moreover, through inhibition of TGF‐β and bone morphogenetic protein (BMP) signaling pathways while activating fibroblast growth factor (FGF) signaling, biomaterials can induce the formation of skin organoids, offering a highly biomimetic platform for studying human skin development and pathological mechanisms.[ 271 ]

At the forefront of material design, a self‐contracting bioactive microgel assembly with robust tissue‐adhesion (SMART‐EXO) uses its distinctive dynamic self‐contracting features to activate mechanotransduction pathways in skin, such as TGF‐β/Smad and Hippo pathways, promoting the transformation of fibroblasts into myofibroblasts, collagen synthesis, and angiogenesis. Additionally, this material enhances cell proliferation, migration, and vascular regeneration by loading and releasing exosomes derived from human bone marrow derived MSCs on demand, further activating the PI3K/Akt and mitogen‐activated protein kinase (MAPK)/extracellular signal‐regulated kinase (Erk) signaling pathways. Consequently, it significantly accelerates the healing of diabetic skin wounds. Combining biomechanical and biochemical signaling regulation, this material offers an innovative solution for chronic diabetic wounds (Figure 12 ).[ 272 ]

Figure 12.

Figure 12

Biological pathway activation by biomaterials. An in situ self‐contracting bioactive microgel system enhances healing of diabetic skin wounds by activating mechanotransduction and biochemical mechanisms. SMART, self‐contraction microgel assembly with robust tissue‐adhesion; EXO, exosomes. Reproduced from Ref. [272] with permission of Wiley, 2024.

Researchers also achieve spatiotemporal‐specific control over signaling pathways by incorporating nanotopographical structures, bioactive ions, and functionalized molecules.[ 273 , 274 ] For instance, 3D‐printed scaffolds with fibrous topographies like PCL and bacterial cellulose composites, modulate the paracrine activities of adipose‐derived MSCs, activating pathways related to immune modulation, angiogenesis, and cell migration, thus promoting regeneration and repair of skin tissues.[ 274 ] Furthermore, specific signaling pathways can be activated by adjusting the physical, chemical, or biological properties of materials, such as using electrospun nanofibers to mimic ECM topography to promote cell migration and proliferation, employing bioactive glass to release calcium ions that activate calcium‐sensing receptor signaling to boost angiogenesis, and utilizing gene‐activated matrices loaded with VEGF‐encoding DNA for sustained expression to enhance vascularization.[ 251 ] These strategies collectively provide precise microenvironmental support for wound healing.[ 251 ] Therefore, the strategies summarized above highlight that targeted activation of pathways such as PI3K/Akt, TGF‐β/Smad, FGF, and calcium‐sensing receptors through tailored material design offers transformative potential for treating impaired wound healing and opens new avenues for future biomaterial‐based therapies.

4.3. Regulation of Cellular Processes

Cell adhesion, migration, and other behaviors are profoundly influenced by the surface properties of biomaterials.[ 275 , 276 , 277 , 278 , 279 , 280 ] Recent advancements have highlighted the importance of bio‐inspired design and materials engineering in optimizing surface topography, chemical signaling, and dynamic responsiveness to enhance the functionality of biomaterials.[ 281 , 282 , 283 , 284 ] These well‐designed materials not only replicate the physical and chemical attributes of the native ECM, but also enable precise spatiotemporal control over signal delivery, allowing for accurate modulation of cellular activities such as keratinocyte migration or fibroblast function during wound healing. Such progress provides innovative strategies for skin biomaterial design in complex applications, propelling the field of skin biomaterials science toward greater precision and efficacy in treating dermatological conditions.

The topological features of biomaterial surfaces play a critical role in mechanotransduction, significantly affecting focal adhesion formation, cytoskeletal reorganization, and migration patterns.[ 285 , 286 , 287 , 288 ] By engineering micropatterns decorated with cell‐adhesive peptides such as arginine‐glycine‐aspartic acid (RGD), researchers have revealed how the surface nanocue precisely regulate migration trajectories of endothelial cells.[ 289 ] Evidence suggests also that RGD nanospacing can modulate the distribution and strength of focal adhesions, thereby influencing cytoskeletal dynamics and migration modes (Figure 13A).[ 286 ] Moreover, studies have demonstrated that surfaces with RGD gradient can induce directional cell migration and cell orientation (Figure 13B).[ 288 ] These findings offer novel approaches for designing materials capable of fine‐tuning cell behavior, with direct relevance to skin tissue engineering and regenerative medicine, where such capabilities hold immense promise for improving skin substitutes and healing outcomes.

Figure 13.

Figure 13

The influence of nanopatterning on cell adhesion and migration. A) Impact of RGD nanospacing on cell migration and its connection to cell adhesion. Adapted from Ref. [286] with permission of Elsevier, 2020. B) Influence of gradient RGD nanospacing on cellular adhesion. EC, endothelial cell; SMC, smooth muscle cell. Reproduced from Ref. [288] with permission of the American Chemical Society, 2022.

Emerging research has further incorporated dynamic response elements into biomaterial surfaces. For example, light‐responsive materials was employed to create active substrates with programmable topological features for guiding cell adhesion, migration, and differentiation.[ 26 ] Dynamic modulation of RGD peptide accessibility through negative electric potential stimulation has been proved to regulate cell adhesion and stem cell fate determination, ultimately influencing cellular behavior and function.[ 290 ] Additionally, modifying poly(vinyl alcohol) surfaces with fucoidan and introducing microscale topographical features enables precise control over endothelial cell behavior.[ 291 ] Fucoidan facilitates adhesion and signaling of endothelial cells by interacting with fibronectin, while microtopographies accelerate cell migration via contact guidance mechanisms, significantly improving endothelialization efficiency and hemocompatibility in synthetic vascular grafts.[ 291 ] These dynamic and topographical approaches are stimulating for developing next‐generation skin biomaterials that actively participate in and guide the complex processes of skin regeneration and integration. The material‐based strategies for guiding cellular adhesion, polarization, and migration (especially through dynamic and spatially controlled cues) are of high clinical relevance and warrant broader application in skin wound healing and bioengineered skin substitutes.

Deciphering these complex material‐driven biological mechanisms provides crucial guidance for creating next‐generation biomaterials. However, translating this mechanistic understanding into practical materials requires optimizing countless parameters spanning from molecular structure to macroscopic properties, a multidimensional challenge that presents significant challenges for traditional experimentation, rendering such approaches increasingly inefficient and time‐consuming. As a result, there is a growing need for advanced computational strategies that can integrate multiscale data, identify non‐linear relationships, and guide rational material design. In this context, AI has emerged as a transformative enabler, capable of efficiently exploring vast parameter landscapes and accelerating the translation of fundamental insights into functional, high‐performance biomaterials.

5. Skin‐Related Biomaterials Enabled by AI

Conventional research of biomaterials is frequently limited by the high costs and inefficiencies of trial‐and‐error approaches. The advent of AI is revolutionizing this field by introducing a new paradigm that integrates data, algorithms, and experiments into a cohesive workflow. By unraveling the principles of materials genomics, constructing predictive models across multiple scales, and fine‐tuning the dynamic responses of smart materials, AI significantly accelerates the development of novel biomaterials, and profoundly expands their real‐world functionality and applications. This synergy between computational and experimental sciences is redefining the innovation landscape for skin‐related biomaterials, enabling a closed‐loop pipeline that spans from molecular design to clinical implementation. As a result, AI is driving more precise, efficient, and impactful advances across both the creation and practical deployment of skin biomaterials, ranging from high‐throughput material discovery to intelligent systems for diagnostics, monitoring, and personalized therapy.[ 20 , 22 , 292 , 293 ]

5.1. AI‐Driven Acceleration in Material Development

AI is profoundly transforming the field of skin‐related biomaterials by accelerating material design through data‐driven and algorithm‐guided approaches, optimizing functional interfaces, and improving the interpretation of complex biological signals. For example, AI algorithms integrate patient‐specific data, including genetic profiles and tissue mechanics, to customize scaffold biomaterials that precisely support cellular growth and regeneration, improving the efficiency of stem cell therapies for tissue repair.[ 294 , 295 ] A typical AI‐aided workflow begins with data aggregation from diverse sources (such as high‐throughput experiments, molecular dynamics simulations, and literature databases), followed by feature engineering and model training using algorithms ranging from decision trees to deep neural networks. For example, artificial neural networks have been used to optimize GelMA hydrogels by predicting the influence of critical parameters like raw material concentration and pH on stiffness and gelation time.[ 294 , 296 ] By integrating high‐throughput screening with predictive modeling, AI significantly enhances the efficiency and precision of developing new materials and navigating complex design spaces (Figure 14A).[ 22 ]

Figure 14.

Figure 14

The convergence of skin‐related biomaterials with AI. A) A comparison among combinatorial methods, high‐throughput screening, and AI‐driven design. Reproduced from Ref.[22] with permission of Elsevier, 2025. B) Schematic of ML algorithm training using lipid screening data, showcasing the training and prediction workflow. Reproduced from Ref. [23] with permission of Springer Nature, 2024.

A key area where AI demonstrates substantial impact is in the design of biomaterial compositions and structures. ML, in particular, excels in extracting complex structure–property relationships from large datasets, facilitating rapid virtual screening and guiding experimental validation.[ 20 ] For instance, ML algorithms such as random forests and support vector machines have been employed to predict the printability of bioinks by correlating polymer composition and cross‐linking density with rheological behavior, significantly reducing experimental iterations in 3D bioprinting of skin grafts and wound‐healing scaffolds.[ 21 , 297 ] Moreover, AI‐powered high‐throughput strategies enable rapid screening of material formulations with minimal material consumption. As an illustration, a study combined miniaturized experiments with machine learning to optimize material properties within a high‐dimensional space of ≈13440 possible hydrogels, achieving results in just 13 experiments while consuming only 0.65 mL of stock solution and less than 170 mg of monomer and crosslinker materials.[ 298 ] Generative adversarial networks and variational autoencoders are also used for de novo design of biomaterials, generating novel hydrogel compositions or peptide sequences with tailored immunomodulatory or antimicrobial properties.[ 297 ] Bayesian optimization and active learning frameworks further refine these designs by iteratively proposing experimental configurations that maximize target properties (e.g., angiogenic potential or antibacterial efficacy), thereby closing the loop between computation and experimentation.[ 299 ] Additionally, ML accelerates the discovery and optimization of key components in biomaterials such as ionizable lipids combining virtual screening with high‐throughput experimentation. This approach streamlines material development workflows, and shifts them from experience‐driven to data‐driven paradigms (Figure 14B).[ 23 ] As multimodal biological databases mature and algorithm interpretability improves, AI is advancing skin‐related biomaterials beyond single‐function mimicry toward lifelike systems capable of environmental self‐adaptation and learning‐based evolution.[ 300 , 301 ]

Another critical contribution of AI lies in the prediction and optimization of the properties of biomaterials. These models leverage quantitative structure‐property relationships to correlate microscale molecular descriptors with macroscale behaviors, facilitating predictions of mechanical, optical, and electronic properties.[ 302 , 303 ] For instance, ML algorithms are applied to predict the mechanical properties of soft hydrogel biomaterials, such as elasticity and resilience under varying physiological conditions.[ 294 ] Similarly, predictive frameworks for protein engineering accelerate the forecasting of properties in next‐generation biosmart materials, allowing researchers to identify trends in material behavior without extensive experimental trials.[ 20 , 304 ] Beyond prediction, AI enhances optimization processes in functional biomaterials. For example, reinforcement learning algorithms dynamically adjust bioprinting parameters (e.g., nozzle speed, temperature) in real time to optimize pore size and mechanical compliance of scaffolds for specific skin tissue regeneration applications.[ 305 ] In nanosafety assessment, ML models trained on physicochemical descriptors of nanomaterials (e.g., surface charge, hydrophobicity) accurately predict cytotoxicity and immune responses, accelerating the translation of safer nanotherapies.[ 306 ] Additionally, AI‐enhanced optimization of hydrogels for biomedical use has enabled multi‐attribute predictions, such as balancing swelling behavior with mechanical integrity, which reduces fabrication time and costs for applications like targeted DDSs.[ 294 ] Generative models and data‐driven approaches are also addressing complex nonlinear mechanical challenges including fracture, plastic deformation, and dynamic impact, ushering in a new era of data‐ and intelligence‐driven materials science.[ 20 ] Notably, generative AI platforms optimize antibacterial biomaterials by balancing constraints such as biocompatibility and therapeutic efficacy, leading to the development of novel antimicrobial agents like peptide‐based variants.[ 307 ] Meanwhile, high‐throughput in silico screening, integrated with ML, accelerates the exploration of vast chemical design spaces, enabling rapid optimization of biomaterials for applications such as e‐skin and biosensing technologies with enhanced structural and functional attributes.[ 21 , 22 , 304 ] Furthermore, AI also facilitates the optimization of immunomodulatory responses by designing biomaterials that influence host immune interactions for regenerative medicine, as seen in the development of materials tailored to modulate endotoxin levels and improve therapeutic outcomes.[ 308 ]

Despite significant progress, AI‐driven acceleration in material development still faces several limitations. A major challenge is the scarcity of high‐quality, standardized, and annotated datasets, which constrains the training and generalizability of AI models. Additionally, the black‐box nature of many ML algorithms hinders interpretability and undermines confidence in predictions, particularly in interdisciplinary research where understanding causal mechanisms is critical. Algorithmic biases and overfitting to limited datasets also pose risks, potentially leading to erroneous material design recommendations. Furthermore, integrating AI tools effectively with experimental validation remains complex, requiring close collaboration between computational and experimental domains. Addressing these issues will be essential to fully leverage AI's potential in advancing skin‐related biomaterials.

5.2. AI‐Enabled Applications of Skin‐Related Biomaterials

The integration of AI with skin‐related biomaterials has greatly enhanced intelligent interactions with the skin interface, extending the functionality of conventional biomaterials and enabling novel uses in personalized medicine, smart rehabilitation, and remote health monitoring through real‐time data processing and adaptive feedback.[ 300 , 309 , 310 ]

A prominent example of the progress outstands in wearable medical devices. Research on e‐skin has experienced rapid growth, with AI powered flexible sensing systems evolving from basic physiological signal collection to sophisticated decision‐support tools. For instance, researchers have mimicked the multi‐layered interlocking structure of the epidermis‐dermis interface with AI algorithms.[ 181 , 311 ] With support from material inference mechanisms based on dielectric constants and softness/hardness properties, these systems achieve multimodal sensing capabilities, such as pressure and temperature.[ 311 ] ML algorithms process high‐dimensional sensor data, perform dimensionality reduction and pattern recognition, and have reduced tactile recognition error rates from 44% to 0.4%, allowing e‐skin to reliably identify and react to complex environments.[ 312 ] Such a sensing‐processing‐response closed‐loop system enables e‐skin to demonstrate performance close to that of biological skin in applications like robotic tactile feedback and wearable health monitoring.[ 300 , 313 ] Additionally, a soft human‐machine interface fabricated with all‐printing techniques and integrated onto robotic surfaces, employs AI‐driven embedded ML algorithms to analyze and respond to physicochemical signals, such as temperature, pressure, and hazardous chemicals in real time. This showcases the dynamic responsiveness of biomimetic skin in environmental interactions through autonomous robotic decision‐making (Figure 15A).[ 314 ]

Figure 15.

Figure 15

Applications of AI in the development of skin‐related biomaterials. A) AI‐powered multimodal robotic sensing system based on a fully printed soft human‐machine interface. This system includes two types of fully printed soft e‐skins: e‐skin‐H (H, human) for interaction with human skin and e‐skin‐R (R, robot) for interfacing with robotic surfaces. It enables AI‐powered robotic control and provides multimodal physicochemical sensing with interactive user feedback. LPS, laser proximity sensor; KNN, k‐nearest neighbor; sEMG, surface electromyography. Reproduced from Ref. [314] with permission of the American Association for the Advancement of Science, 2022. B) ML‐driven stretchable device platform enabling wireless measurement and intelligent analysis of throat vibrations and muscle electrical activities for enhanced functionalities and precision. Reproduced from Ref. [315] with permission of Springer Nature, 2023.

In clinical settings, AI technology is enhancing diagnostic capabilities through their integration with skin‐related biomaterials. For instance, a newly developed stretchable device platform integrates sensors and adaptive ML modules directly into flexible substrates, enabling real‐time monitoring of biosignals like electromyography and acceleration.[ 315 ] By leveraging deep learning algorithms such as convolutional neural networks, the system can classify and diagnose complex signals, facilitating real‐time disease monitoring, remote healthcare management, and personalized rehabilitation assessments. It adapts to individual variations and motion artifacts, providing efficient and precise diagnostic and therapeutic support for conditions, such as swallowing disorders and throat diseases (Figure 15B).[ 315 ] Similarly, e‐skin based on flexible sensors can capture multimodal data streams such as skin contact pressure, temperature, and bioelectrical signals in real time. Through feature extraction and deep learning models, these systems enable accurate analysis of the captured data, such as detecting nocturnal breathing signals in patients of Parkinson's disease.[ 301 , 309 ] In skin cancer diagnosis, AI‐driven image analysis systems combined with biocompatible optical materials can identify microstructural features of malignant melanoma from dermoscopic images, achieving diagnostic accuracy comparable to that of trained dermatologists and greatly improving screening efficiency.[ 316 , 317 ] In wound management, AI supports tasks such as injury classification, wound measurement (including area and depth), tissue type categorization, wound monitoring, predictive analysis, and personalized treatment planning.[ 318 ]

The synergy between computational and experimental sciences is redefining the innovation landscape for skin‐related biomaterials, leading to more precise, efficient, and impactful material design and application. AI accelerates the design of advanced biomaterials, whose application yields performance data and mechanistic insights, which in turn feed back into refining AI models and inspiring new design principles. This integrative approach, combining application‐driven goals, mechanism‐based understanding, and AI‐powered execution, is poised to unlock unprecedented possibilities in cutaneous health management.

6. Summary and Perspective

Biomaterials is fundamentally transforming traditional therapeutic paradigms.[ 16 , 319 , 320 , 321 , 322 , 323 , 324 , 325 , 326 , 327 ] Biomaterial research covers broad fields including but not limited to tissue engineering and drug delivery, and is now expanding from smart responsiveness to interdisciplinary integration, showcasing unprecedented innovation and vitality.[ 328 , 329 , 330 , 331 , 332 , 333 , 334 , 335 , 336 , 337 , 338 ] Their interdisciplinary nature enables the integration of cutting‐edge technologies of materials science, biology, medicine, and engineering,[ 339 , 340 , 341 , 342 , 343 , 344 , 345 , 346 , 347 , 348 ] providing precise, personalized, and dynamic solutions for complex disease treatment. Within this context, significant breakthroughs have been achieved in skin‐related biomaterials, establishing them as a cornerstone of regenerative medicine and precision healthcare.[ 339 , 349 , 350 , 351 , 352 ] Natural biomaterials, such as proteins, polysaccharides, and lipids, leverage their exceptional biocompatibility and biomimetic properties to excel in wound healing, anti‐aging, and barrier function restoration. For example, protein‐based materials promote cell proliferation and immunomodulation through molecular structure design;[ 13 ] polysaccharide‐based materials utilize their 3D network structures to facilitate tissue regeneration and drug delivery;[ 12 , 34 ] lipid‐based materials mimic skin barrier functions, playing critical roles in hydration and inflammation modulation.[ 14 ] These natural materials have further enhanced their multifunctional capabilities through genetic engineering and biomimetic design. Synthetic biomaterials achieve functionalities such as controlled drug release, mechanical adaptability, and intelligent responsiveness by precisely tuning their physicochemical properties. Polymer materials optimize mechanical performance and biocompatibility;[ 92 ] hydrogels simulate tissue physical characteristics with their high water content and 3D structures;[ 17 , 98 , 353 , 354 , 355 , 356 ] nanomaterials enable precise drug delivery and microenvironment modulation through surface functionalization.[ 107 ] The dynamic responsiveness of synthetic materials provides vast potential for applications in complex physiological environments.[ 16 , 85 , 263 , 314 ] Composite biomaterials integrate the advantages of both natural and synthetic materials, enabling multi‐level microenvironment simulation. Bioactive composites promote cell behavior regulation and tissue regeneration by incorporating growth factors and functional carriers;[ 124 , 125 ] biomimetic structural composites optimize mechanical performance and biological functionality through hierarchical design;[ 127 , 128 ] functionalized smart composites endow materials with sensing and self‐adaptive capabilities via dynamic response units.[ 11 , 129 , 130 ] These composite materials provide innovative platforms for skin repair, disease monitoring, and treatment.

The integration of AI is reshaping the research paradigm of skin‐related biomaterials. High‐throughput screening and performance prediction powered by intelligent algorithms accelerate the discovery and functional design of new materials.[ 22 , 23 ] Furthermore, studies on the interactions between biomaterials and the skin microenvironment have revealed mechanisms by which key signaling pathways (e.g., MAPK/Erk and TGF‐β) are modulated to actively influence cell behavior.[ 268 , 272 ] These signaling pathways play pivotal roles in cell proliferation, migration, differentiation, and immunomodulation, providing theoretical support for the precise regulation of skin repair and regeneration.

Despite the remarkable progress in skin‐related biomaterials that has significantly improved treatment efficacy, challenges remain in this field. In our view, at least some critical aspects of skin‐related biomaterial development warrant careful consideration in the future, as schematically presented in Figure 16 and described as follows.

  1. The development of novel materials stands as the central driving force behind advancements in skin‐related biomaterials. Current efforts often face limitations in achieving the desired complexity and dynamism of native ECM replication, where precise control over molecular architecture while simultaneously ensuring optimal biocompatibility, biodegradability, and mechanical adaptation in vivo remains a significant hurdle. Progressing beyond traditional static materials necessitates clever biomimetic design and dynamic functional integration.[ 342 , 348 ] For instance, biomimetic design meticulously engineers materials to replicate key structural and functional elements of native skin, leveraging natural components such as protein‐based materials whose molecular architecture can be tuned through genetic engineering[ 45 , 46 ] to display bioactive sequences that actively direct cell behavior; polysaccharide‐based materials that exploit their innate biocompatibility and capacity to form biomimetic 3D networks[ 52 ] facilitating tissue integration; and lipid‐based systems that emulate the skin's barrier organization[ 14 ] to restore homeostasis. More chances might exist toward synthetic yet biomimetic polymers and composites. Building upon the biomimetic foundation, dynamic functional integration enables materials to sense and adapt to the evolving wound milieu. This integrated approach transforms materials from passive scaffolds to active systems that dynamically interface with skin microenvironments, precisely modulating regeneration through continuous biochemical and biophysical dialogue.

  2. Responsive biomaterials are paving the way for more precise therapeutic control. A limitation lies in the development of systems that are reliably sensitive, specific, and stable within the complex, variable, and long‐term environment of the skin. Many existing responsive systems suffer from delayed responses, limited biocompatibility over extended periods, or insufficient robustness for diverse clinical scenarios. The next generation of smart materials should integrate flexible sensing technologies, dynamic feedback mechanisms, and self‐regulating capabilities to form a complete “sense‐decide‐act” system.[ 315 ] Such systems would enable real‐time monitoring of skin conditions and automatic adjustments in drug release rates or material properties based on monitoring data, thereby achieving optimal therapeutic outcomes. Ultimately, such intelligent systems are steering skin treatments away from generalized therapies and toward personalized and data‐driven strategies.

  3. The integration of advanced biomaterials with cell therapy represents a direction in regenerative medicine. Critical challenges include ensuring long‐term viability, functionality, and precise control over the fate of therapeutic cells within the biomaterial construct in vivo. Issues like potential immunogenicity, inconsistent cell engraftment or survival, and scalable manufacturing of viable cell‐material hybrids need effective solutions. Synergistic design of materials and cell therapies overcomes the limitations of single‐modality treatments.[ 357 , 358 ] Functionalized scaffolds enhance stem cell homing through surface modifications with targeting molecules such as RGD peptides,[ 290 ] while cell‐laden hydrogels with stem cells encapsulated can remodel the local immune microenvironment and promote tissue regeneration.[ 359 ] These “material‐cell” hybrid systems are propelling regenerative medicine from static replacement to dynamic regulation.

  4. Comprehensive and in‐depth investigations into material‐driven biological mechanisms is critical for the design and development of innovative skin materials. A major limitation of medical materials is the incomplete understanding of how biomaterials precisely orchestrate complex cellular responses and signaling cascades over different time scales. Predicting potential off‐target effects or unintended long‐term consequences (e.g., fibrotic responses, chronic inflammation) based on material properties is still largely empirical. Cutting‐edge scientific techniques, including single‐cell omics, in situ imaging, and mechanotransduction signal tracking, are being employed to elucidate how materials influence cell fate and the underlying mechanisms. This mechanism‐based approach is shifting material design from trial‐and‐error to theory‐driven, providing a solid foundation for precise material intervention.

  5. Interdisciplinary collaboration is vital for the rapid evolution of skin‐related biomaterials. The complexity of skin treatment demands deep integration among materials science, biology, engineering, and clinical medicine.[ 332 ] Establishing an innovation pipeline guided by clinical demands, supported by fundamental research, and driven by engineering technology can address major challenges in large‐scale production and clinical translation, streamlining the pathway from concept to market. Some new medical applications depending strongly on interdisciplinary collaboration are indirectly related to skin relevant biomaterials. For instance, brain‐machine interfaces (BMIs) are making rapid progress.[ 232 , 360 , 361 ] Significant material challenges persist: for invasive BMI, achieving stable, long‐term, infection‐resistant percutaneous sealing with biomaterials remains unsolved; for non‐invasive BMI, developing skin‐interfacing materials that ensure consistent, artifact‐free signal acquisition during prolonged wear without causing irritation is critical. Skin relevant biomaterials should be paid attention to in both cases.

  6. Enhanced applications of AI are driving R&D of adaptive and predictive biomaterials. AI is revolutionizing the material development process. For instance, generative adversarial networks can reverse‐engineer novel molecular structures tailored to specific performance criteria; ML‐driven autonomous experimental platforms can identify optimal material formulations within days; and clinical big data models can predict patient responses to therapies, guiding personalized treatment. Current limitations include the scarcity of high‐quality, standardized, and comprehensive datasets (particularly for complex in vivo responses and long‐term outcomes), the “black box” nature of some complex models hindering interpretability and trust, computational resource demands for sophisticated simulations, and the significant gap between in silico predictions and experimental/clinical validation. Future advances, such as quantum computing and cross‐modal large models, offer potential to overcome current algorithmic constraints, unlocking new potential for discovering high‐performance materials. Simultaneously, skin‐related biomaterials are offering innovative tools and perspectives for exploring AI, brain science, and disease treatment.[ 25 ] By integrating with advanced medical devices and technologies, skin‐related biomaterials hold promise for uncovering complex biological mechanisms.[ 362 ]

Figure 16.

Figure 16

Key future trends of R&D of skin‐relevant biomaterials. The perspective outlines six major focus areas to guide future development: novel materials; smart biomaterials for skin therapy; biomaterials combined with cell therapies; bio‐mechanisms for skin materials; interdisciplinary collaboration; and Enhanced AI applications.

Beyond these six perspectives, additional challenges exist for skin‐relevant biomaterials. A prime example is achieving efficient, controllable, and predictable percutaneous absorption for transdermal DDSs. This challenge is significant due to the formidable barrier function of the stratum corneum, significant inter‐ and intra‐individual variability in skin physiology (e.g., age, disease state, hydration, anatomical site), the physicochemical limitations of many therapeutic molecules (e.g., size, hydrophilicity, instability), and the need for formulations that are not only effective but also safe, non‐irritating, and patient‐compliant over prolonged use.[ 184 , 185 , 363 ] Other challenges include managing microbial biofilms in chronic wounds, achieving long‐term biocompatibility and functional stability of implanted/implanted devices, modulating complex immune responses (both pro‐regenerative and anti‐fibrotic) in a spatiotemporally controlled manner, and developing truly biomimetic materials that fully recapitulate the dynamic reciprocity of native skin. Addressing these multifaceted challenges demands concerted efforts leveraging the core strategies of novel material development, interdisciplinary integration, and intelligent technologies.

The groundbreaking progress in skin‐related biomaterials will rely on an open and collaborative innovation ecosystem. The key lies in advancing the deep integration of three critical directions: the development of novel materials, interdisciplinary integration, and the application of intelligence technologies. By leveraging AI‐assisted design, developing dynamically responsive materials, and conducting mechanistic studies of cell‐material interactions, a next‐generation material system with intelligent regulatory capabilities can be established, driving skin treatments and skin‐relevant medical devices toward significant precision and functionality.

Conflict of Interest

The authors declare no conflict of interest.

Acknowledgements

The authors are grateful for the financial supports from National Natural Science Foundation of China (grant No. 52130302) and National Key R&D Program of China (grant No. 2023YFC2410300).

Biographies

Yanshuang Zhang obtained Ph.D. in Biomedical Engineering from Shanghai Jiao Tong University in 2023. He is currently a postdoctor in the group of Prof. Jiandong DING at the State Key Laboratory of Molecular Engineering of Polymers, Fudan University. His research focuses on biomedical translation of skin relevant polymers with emphasis on regenerative biomaterials.

graphic file with name ADMA-38-e12919-g014.gif

Jiandong Ding is a Distinguished Professor of Biomaterials and Polymer Science at Fudan University, and the Director of the State Key Laboratory of Molecular Engineering of Polymers. His research covers injectable hydrogels, tissue regeneration, and drug delivery systems, with emphasis on developing cell‐responsive biomaterials for clinical applications and medical innovation. He is the leading scientist of a 973 program and a national research and development program about biomedical materials in China, and a Fellow of the International Union of Societies of Biomaterials Science and Engineering.

graphic file with name ADMA-38-e12919-g018.gif

References

  • 1. Christman K. L., Nat. Biomed. Eng. 2023, 7, 92.36627365 [Google Scholar]
  • 2. Zhuang Y., Lin F., Xiang L., Cai Z., Wang F., Cui W., Adv. Mater. 2024, 36, 2312556. [DOI] [PubMed] [Google Scholar]
  • 3. Xu H., Yan S., Gerhard E., Xie D., Liu X., Zhang B., Shi D., Ameer G. A., Yang J., Adv. Mater. 2024, 36, 2402871. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Nguyen M., Karkanitsa M., Christman K. L., Nat. Rev. Bioeng. 2024, 2, 810. [Google Scholar]
  • 5. Sundaram S., Lee J. H., Bjørge I. M., Michas C., Kim S., Lammers A., Mano J. F., Eyckmans J., White A. E., Chen C. S., Nature 2024, 636, 361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Abudousu A., Tang Y. K., Wang Z., Lin F., Cui W. G., Nat. Rev. Bioeng. 2025, 3, 355. [Google Scholar]
  • 7. Liu H., Yang Y., Liu Y., Pan J., Wang J., Man F., Zhang W., Liu G., Adv. Sci. 2020, 7, 1903129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Chen B., Cao Y., Li Q., Yan Z., Liu R., Zhao Y., Zhang X., Wu M., Qin Y., Sun C., Yao W., Cao Z., Ajayan P. M., Chee M. O. L., Dong P., Li Z., Shen J., Ye M., Nat. Commun. 2022, 13, 1206. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Zhu H., Wang J., Yang X., Zhang B., Wang Z., Adv. Mater. 2024, 2413112. [Google Scholar]
  • 10. Zhang M., Zhao L., Tian F., Zhao X., Zhang Y., Yang X., Huang W., Yu R., Adv. Mater. 2024, 36, 2405776. [DOI] [PubMed] [Google Scholar]
  • 11. Shi J., Kim S., Li P., Dong F., Yang C., Nam B., Han C., Eig E., Shi L. L., Niu S., Yue J., Tian B., Science 2024, 384, 1023. [DOI] [PubMed] [Google Scholar]
  • 12. Albuquerque P. B. S., De Oliveira W. F., Dos Santos Silva P. M., Dos Santos Correia M. T., Kennedy J. F., Coelho L. C. B. B., Carbohydr. Polym. 2022, 277, 118824. [DOI] [PubMed] [Google Scholar]
  • 13. Zhang H., Lin X., Cao X., Wang Y., Wang J., Zhao Y., Bioact. Mater. 2024, 33, 355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Nicolaou A., Kendall A. C., Pharmacol. Ther. 2024, 260, 108681. [DOI] [PubMed] [Google Scholar]
  • 15. Fan R., Zhao J., Yi L., Yuan J., Mccarthy A., Li B., Yang G., John J. V., Wan W., Zhang Y., Chen S., Adv. Mater. 2024, 36, 2307328. [DOI] [PubMed] [Google Scholar]
  • 16. Yu B., Kang S., Akthakul A., Ramadurai N., Pilkenton M., Patel A., Nashat A., Anderson D. G., Sakamoto F. H., Gilchrest B. A., Anderson R., Langer R., Nat. Mater. 2016, 15, 911. [DOI] [PubMed] [Google Scholar]
  • 17. Rauner N., Meuris M., Zoric M., Tiller J. C., Nature 2017, 543, 407. [DOI] [PubMed] [Google Scholar]
  • 18. Shou Y., Le Z., Cheng H. S., Liu Q., Ng Y. Z., Becker D. L., Li X., Liu L., Xue C., Yeo N. J. Y., Tan R., Low J., Kumar A. R., Wu K. Z., Li H., Cheung C., Lim C. T., Tan N. S., Chen Y., Liu Z., Tay A., Adv. Mater. 2023, 35, 2304638. [DOI] [PubMed] [Google Scholar]
  • 19. Wang C., Shirzaei Sani E., Shih C., Lim C. T., Wang J., Armstrong D. G., Gao W., Nat. Rev. Mater. 2024, 9, 550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Guo K., Yang Z., Yu C. H., Buehler M. J., Mater. Horiz. 2021, 8, 1153. [DOI] [PubMed] [Google Scholar]
  • 21. Suwardi A., Wang F., Xue K., Han M., Teo P., Wang P., Wang S., Liu Y., Ye E., Li Z., Loh X. J., Adv. Mater. 2022, 34, 2102703. [DOI] [PubMed] [Google Scholar]
  • 22. Hang R., Yao X., Bai L., Hang R., Acta Biomater. 2025, 197, 29. [DOI] [PubMed] [Google Scholar]
  • 23. Li B., Raji I. O., Gordon A. G. R., Sun L., Raimondo T. M., Oladimeji F. A., Jiang A. Y., Varley A., Langer R. S., Anderson D. G., Nat. Mater. 2024, 23, 1002. [DOI] [PubMed] [Google Scholar]
  • 24. Liu Z., Hu X., Bo R., Yang Y., Cheng X., Pang W., Liu Q., Wang Y., Wang S., Xu S., Shen Z., Zhang Y., Science 2024, 384, 987. [DOI] [PubMed] [Google Scholar]
  • 25. Hu H., Huang H., Li M., Gao X., Yin L., Qi R., Wu R. S., Chen X., Ma Y., Shi K., Li C., Maus T. M., Huang B., Lu C., Lin M., Zhou S., Lou Z., Gu Y., Chen Y., Lei Y., Wang X., Wang R., Yue W., Yang X., Bian Y., Mu J., Park G., Xiang S., Cai S., Corey P. W., Wang J., Xu S., Nature 2023, 613, 667. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Puliafito A., Ricciardi S., Pirani F., Čermochová V., Boarino L., De Leo N., Primo L., Descrovi E., Adv. Sci. 2019, 6, 1801826. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Wang H., Liu R., Yu Y., Xue H., Shen R., Zhang Y., Ding J., Biomaterials 2025, 317, 123013. [DOI] [PubMed] [Google Scholar]
  • 28. Liu X., Zhang M., Wang P., Zheng K., Wang X., Xie W., Pan X., Shen R., Liu R., Ding J., Wei Q., Proc. Natl. Acad. Sci. USA 2025, 122, 2501264122. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Monaghan M. G., Borah R., Thomsen C., Browne S., Adv. Drug Delivery Rev. 2023, 203, 115120. [DOI] [PubMed] [Google Scholar]
  • 30. Liu Y., Suarez‐Arnedo A., Caston E. L., Riley L., Schneider M., Segura T., Adv. Mater. 2023, 35, 2304049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Cao D. L., Ding J. D., Regen. Biomater. 2022, 9, rbac098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Sierra‐Sánchez Á., Cabañas‐Penagos J., Igual‐Roger S., Martínez‐Heredia L., Espinosa‐Ibáñez O., Sanabria‐De La Torre R., Quiñones‐Vico M. I., Ubago‐Rodríguez A., Lizana‐Moreno A., Fernández‐González A., Guerrero‐Calvo J., Fernández‐Porcel N., Ramírez‐Muñoz A., Arias‐Santiago S., Regen. Biomater. 2024, 11, rbae115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Luo M., Zhang X., Wu J., Zhao J., Carbohydr. Polym. 2021, 266, 118097. [DOI] [PubMed] [Google Scholar]
  • 34. Yuan M., Wang J., Geng L., Wu N., Yang Y., Zhang Q., Int. J. Biol. Macromol. 2024, 272, 132846. [DOI] [PubMed] [Google Scholar]
  • 35. Han S., Park Y., Kim H., Nam H., Ko O., Lee J. B., ACS Appl. Mater. Interfaces 2020, 12, 55554. [DOI] [PubMed] [Google Scholar]
  • 36. Zhou T., Chen Y., Fu L., Wang S., Ding H., Bai Q., Guan J., Mao Y., Regen. Biomater. 2024, 11, rbae107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Dai S., Jiang L., Liu L., Su Z., Yao L., Yang P., Huang N., Regen. Biomater. 2024, 11, rbae119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Cao X., Lin X., Li N., Zhao X., Zhou M., Zhao Y., Mater. Horiz. 2023, 10, 3237. [DOI] [PubMed] [Google Scholar]
  • 39. Wang L., Shang Y., Zhang J., Yuan J., Shen J., Adv. Colloid Interface Sci. 2023, 321, 103012. [DOI] [PubMed] [Google Scholar]
  • 40. Peng W., Li D., Dai K., Wang Y., Song P., Li H., Tang P., Zhang Z., Li Z., Zhou Y., Zhou C., Int. J. Biol. Macromol. 2022, 208, 400. [DOI] [PubMed] [Google Scholar]
  • 41. Feroz S., Muhammad N., Ranayake J., Dias G., Bioact. Mater. 2020, 5, 496. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Sapru S., Das S., Mandal M., Ghosh A. K., Kundu S. C., Carbohydr. Polym. 2021, 258, 117717. [DOI] [PubMed] [Google Scholar]
  • 43. Ahn W., Lee J. H., Kim S. R., Lee J., Lee E. J., J. Mater. Chem. 2021, 9, 1919. [DOI] [PubMed] [Google Scholar]
  • 44. Kim B. S., Kwon Y. W., Kong J., Park G. T., Gao G., Han W., Kim M., Lee H., Kim J. H., Cho D., Biomaterials 2018, 168, 38. [DOI] [PubMed] [Google Scholar]
  • 45. Yi J., Liu Q., Zhang Q., Chew T. G., Ouyang H., Biomaterials 2022, 282, 121414. [DOI] [PubMed] [Google Scholar]
  • 46. Chemla Y., Kaufman F., Amiram M., Alfonta L., Chem. Rev. 2024, 124, 11187. [DOI] [PubMed] [Google Scholar]
  • 47. Majekodunmi T., Britton D., Montclare J. K., Chem. Rev. 2024, 124, 9113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Johnson J. A., Lu Y. Y., Van Deventer J. A., Tirrell D. A., Curr. Opin. Chem. Biol. 2010, 14, 774. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Gong Q., Liu B., Yuan F., Tao R., Huang Y., Zeng X., Zhu X., Zhao Y., Zhang Y., Yang M., Wang J., Liu T., Zhang G., ACS Nano 2023, 17, 23679. [DOI] [PubMed] [Google Scholar]
  • 50. Zubair M., Hussain S., Ur‐Rehman M., Hussain A., Akram M. E., Shahzad S., Rauf Z., Mujahid M., Ullah A., Biomater. Sci. 2024, 13, 130. [DOI] [PubMed] [Google Scholar]
  • 51. Mirzaei M., Dodi G., Gardikiotis I., Pasca S., Mirdamadi S., Subra G., Echalier C., Puel C., Morent R., Ghobeira R., Soleymanzadeh N., Moser M., Goriely S., Shavandi A., Biomater. Adv. 2023, 149, 213361. [DOI] [PubMed] [Google Scholar]
  • 52. Duceac I. A., Coseri S., Biotechnol. Adv. 2022, 61, 108056. [DOI] [PubMed] [Google Scholar]
  • 53. Tarrahi R., Khataee A., Karimi A., Yoon Y., Chemosphere 2022, 288, 132529. [DOI] [PubMed] [Google Scholar]
  • 54. Tyeb S., Verma V., Kumar N., Carbohydr. Polym. 2023, 316, 121038. [DOI] [PubMed] [Google Scholar]
  • 55. Li M., Zhao Y., Zhang W., Zhang S., Zhang S., Carbohydr. Polym. 2021, 269, 118323. [DOI] [PubMed] [Google Scholar]
  • 56. Yin X., Wang L., Niu Y., Xie D., Zhang Q., Xiao J., Dong L., Wang C., Adv. Mater. 2024, 36, 2304655. [DOI] [PubMed] [Google Scholar]
  • 57. Su Y., Niu M., Xu K., Xu C., Yang P., Hu Y., Xu F., Sci. China‐Technol. Sci. 2024, 67, 3235. [Google Scholar]
  • 58. Chen N., Hu M., Jiang T., Xiao P., Duan J. A., Carbohydr. Polym. 2024, 333, 122003. [DOI] [PubMed] [Google Scholar]
  • 59. Lopes P., Joaquinito A. S. M., Ribeiro A., Moura N. M., Gomes A. T., Guerreiro S. G., Faustino M. A. F., Almeida A., Ferreira P., Coimbra M. A., Neves M. G. P., Gonçalves I., Carbohydr. Polym. 2023, 313, 120894. [DOI] [PubMed] [Google Scholar]
  • 60. Lu S., Zhou T., Shabbir I., Choi J., Kim Y. H., Park M., Aweya J. J., Tan K., Zhong S., Cheong K., Carbohydr. Polym. 2025, 353, 123276. [DOI] [PubMed] [Google Scholar]
  • 61. Ng J. Y., Obuobi S., Chua M. L., Zhang C., Hong S., Kumar Y., Gokhale R., Ee P. L. R., Carbohydr. Polym. 2020, 241, 116345. [DOI] [PubMed] [Google Scholar]
  • 62. Tong Y. L., Yang K., Wei W., Gao L. T., Li P. C., Zhao X. Y., Chen Y. M., Li J., Li H., Miyatake H., Ito Y., Carbohydr. Polym. 2024, 342, 122203. [DOI] [PubMed] [Google Scholar]
  • 63. Fragal E. H., Fragal V. H., Silva E. P., Paulino A. T., Da Silva Filho E. C., Mauricio M. R., Silva R., Rubira A. F., Muniz E. C., Carbohydr. Polym. 2022, 292, 119665. [DOI] [PubMed] [Google Scholar]
  • 64. Li Y., Sun L., Chen R., Ni W., Liang Y., Zhang H., He C., Shi B., Petropoulos S., Zhao C., Shi L., ACS Cent. Sci. 2024, 10, 184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65. Jia B., Li G., Cao E., Luo J., Zhao X., Huang H., Mater. Today. Bio. 2023, 19, 100582. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Liu Y., Zhang Y., Yang Q., Yu Z., He M., Zhu Y., Fu X., Meng F., Ma Q., Kong L., Pan S., Che Y., Int. J. Biol. Macromol. 2024, 277, 134337. [DOI] [PubMed] [Google Scholar]
  • 67. Meng Q., Zhong S., Xu L., Wang J., Zhang Z., Gao Y., Cui X., Carbohydr. Polym. 2022, 279, 119013. [DOI] [PubMed] [Google Scholar]
  • 68. Barclay T. G., Day C. M., Petrovsky N., Garg S., Carbohydr. Polym. 2019, 221, 94. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. Shah R. M., Jadhav S. R., Bryant G., Kaur I. P., Harding I. H., Adv. Colloid Interface Sci. 2025, 338, 103402. [DOI] [PubMed] [Google Scholar]
  • 70. Almoughrabie S., Cau L., Cavagnero K., O'Neill A. M., Li F., Roso‐Mares A., Mainzer C., Closs B., Kolar M. J., Williams K. J., Bensinger S. J., Gallo R. L., Sci. Adv. 2023, 9, adg6262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71. Kapoor M. S., GuhaSarkar S., Banerjee R., Ther. Deliv. 2017, 8, 701. [DOI] [PubMed] [Google Scholar]
  • 72. Keck C. M., Specht D., Brüßler J., J. Controlled Release 2021, 338, 149. [DOI] [PubMed] [Google Scholar]
  • 73. Rahman R. T., Koo B. I., Jang J., Lee D. J., Choi S., Lee J. B., Nam Y. S., Int. J. Pharm. 2024, 661, 124409. [DOI] [PubMed] [Google Scholar]
  • 74. Motsoene F., Abrahamse H., Dhilip Kumar S. S., Adv. Colloid Interface Sci. 2023, 321, 103002. [DOI] [PubMed] [Google Scholar]
  • 75. Ma X., Cong R., Cui X., Tang Y., Ren J., Hou J., Liu B., Zhao J., Li P., Li L., Zhang H., Tu J., Jiang L., J. Controlled Release 2025, 381, 113581. [DOI] [PubMed] [Google Scholar]
  • 76. Wang W., Chen K., Jiang T., Wu Y., Wu Z., Ying H., Yu H., Lu J., Lin J., Ouyang D., Nat. Commun. 2024, 15, 10804. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77. Han Y., Xi L., Leng F., Xu C., Zheng Y., Int. J. Nanomedicine. 2024, 19, 2625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78. García‐Villén F., Viseras C., Pharmaceutics 2020, 12, 1142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79. Solish N., Humphrey S., Waller B., Vanderveen S., Dermatol. Surg. 1508, 2020, 12 [DOI] [PubMed] [Google Scholar]
  • 80. Choimet M., Tourrette A., Marsan O., Rassu G., Drouet C., Acta Biomater. 2020, 111, 418. [DOI] [PubMed] [Google Scholar]
  • 81. Haftek M., Abdayem R., Guyonnet‐Debersac P., Int. J. Mol. Sci. 2022, 23, 6267 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82. Portugal‐Cohen M., Cohen D., Ish‐Shalom E., Laor‐Costa Y., Ma'or Z., Exp. Dermatol. 2019, 28, 585. [DOI] [PubMed] [Google Scholar]
  • 83. Moraes J. D. D., Bertolino S. R. A., Cuffini S. L., Ducart D. F., Bretzke P. E., Leonardi G. R., Int. J. Pharm. 2017, 534, 213. [DOI] [PubMed] [Google Scholar]
  • 84. Sharma P., Saurav S., Tabassum Z., Sood B., Kumar A., Malik T., Mohan A., Girdhar M., RSC Adv. 2024, 14, 36226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85. Madl A. C., Madl C. M., Myung D., ACS Macro. Lett. 2020, 9, 619. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86. Dong Y., Ramey‐Ward A. N., Salaita K., Adv. Mater. 2021, 33, 2006600. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87. Liu Y., Yang X., Wu K., Feng J., Zhang X., Li A., Cheng C., Zhu Y. Z., Guo H., Wang X., Adv. Mater 2025, 37, 2414989. [DOI] [PubMed] [Google Scholar]
  • 88. Yang X., Li C., Li B., Zhang Y., Li J., Liu N., Nie X., Zhang D., Zhou M., Liao X., Regen. Biomater. 2025, 12, rbaf031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 89. Tiwari N., Osorio‐Blanco E. R., Sonzogni A., Esporrín‐Ubieto D., Wang H., Calderón M., Angew. Chem. Int. Ed. Engl. 2022, 61, 202107960. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90. Brakat A., Zhu H., Nanomicro. Lett. 2021, 13, 94. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91. Liu X., Cao L., Jiang C., Wang H., Zhang X., Liu Q., Li H., Tang Y., Feng Y., Int. J. Biol. Macromol. 2024, 279, 135259. [DOI] [PubMed] [Google Scholar]
  • 92. Gsib O., Eggermont L. J., Egles C., Bencherif S. A., Biomater. Sci. 2020, 8, 7106. [DOI] [PubMed] [Google Scholar]
  • 93. Zhang M., Gong S., Hakobyan K., Gao Z., Shao Z., Peng S., Wu S., Hao X., Jiang Z., Wong E. H., Liang K., Wang C. H., Cheng W., Xu J., Adv. Sci. 2024, 11, 2309006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94. Hewitt E., Mros S., McConnell M., Cabral J. D., Ali A., Biomed. Mater. 2019, 14, 055013. [DOI] [PubMed] [Google Scholar]
  • 95. Vázquez N., Sánchez‐Arévalo F., Maciel‐Cerda A., Garnica‐Palafox I., Ontiveros‐Tlachi R., Chaires‐Rosas C., Piñón‐Zarate G., Herrera‐Enríquez M., Hautefeuille M., Vera‐Graziano R., Castell‐Rodríguez A., Biomed. Mater. 2019, 14, 045006. [DOI] [PubMed] [Google Scholar]
  • 96. Lopresti F., Campora S., Tirri G., Capuana E., Carfì Pavia F., Brucato V., Ghersi G., La Carrubba V., Mater. Sci. Eng. C. Mater. Biol. Appl. 2021, 127, 112248. [DOI] [PubMed] [Google Scholar]
  • 97. Gao L., Zabihi F., Ehrmann S., Hedtrich S., Haag R., J. Controlled Release 2019, 300, 64. [DOI] [PubMed] [Google Scholar]
  • 98. Song R., Wang X., Johnson M., Milne C., Lesniak‐Podsiadlo A., Li Y., Lyu J., Li Z., Zhao C., Yang L., Lara‐Sáez I., A S., Wang W., Adv. Funct. Mater. 2024, 34, 2313322. [Google Scholar]
  • 99. Qiao B., Wang J., Qiao L., Maleki A., Liang Y., Guo B., Regen. Biomater. 2024, 11, rbad110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100. Zhang J., Zeng Z., Chen Y., Deng L., Zhang Y., Que Y., Jiao Y., Chang J., Dong Z., Yang C., Regen. Biomater. 2023, 10, rbad049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101. Zarrintaj P., Ghorbani S., Barani M., Singh Chauhan N. P., Khodadadi Yazdi M., Saeb M. R., Ramsey J. D., Hamblin M. R., Mozafari M., Mostafavi E., Bioeng. Transl. Med. 2022, 7, 10261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102. Zhang Y., Sun T., Li W., Yu L., Ding J., Adv. Funct. Mater. 2025, 14562. [Google Scholar]
  • 103. Gu H. J., Li H., Wei L. R., Lu J., Wei Q. R., Regen. Biomater. 2023, 10, rbad018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104. Hong S. H., Lee M. H., Go E. J., Park J. C., Regen. Biomater. 2024, 11, rbae101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 105. Cao H., Wang M., Ding J., Lin Y., J. Mater. Chem. B 2024, 12, 8007. [DOI] [PubMed] [Google Scholar]
  • 106. Ding J., Sun L., Zhu Z., Wu X., Xu X., Xiang Y., J. Nanobiotechnology 2023, 21, 268. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107. Salvioni L., Morelli L., Ochoa E., Labra M., Fiandra L., Palugan L., Prosperi D., Colombo M., Adv. Colloid Interface Sci. 2021, 293, 102437. [DOI] [PubMed] [Google Scholar]
  • 108. Liu T., Lu Y., Zhan R., Qian W., Luo G., Adv. Drug Delivery Rev. 2023, 193, 114670. [DOI] [PubMed] [Google Scholar]
  • 109. Yu R., Zhang H., Guo B., Nanomicro. Lett. 2021, 14, 1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 110. Li Y. Y., Ji S. F., Fu X. B., Jiang Y. F., Sun X. Y., Mil. Med. Res. 2024, 11, 13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 111. Dong P., Sahle F. F., Lohan S. B., Saeidpour S., Albrecht S., Teutloff C., Bodmeier R., Unbehauen M., Wolff C., Haag R., Lademann J., Patzelt A., Schäfer‐Korting M., Meinke M. C., J. Controlled Release 2019, 295, 214. [DOI] [PubMed] [Google Scholar]
  • 112. Li M., Cui H., Cao Y., Lin Y., Yang Y., Gao M., Zhang W., Wang C., J. Controlled Release 2023, 354, 664. [DOI] [PubMed] [Google Scholar]
  • 113. Sun J., Dai L., Lv K., Wen Z., Li Y., Yang D., Yan H., Liu X., Liu C., Li M., Adv. Colloid Interface Sci. 2024, 328, 103177. [DOI] [PubMed] [Google Scholar]
  • 114. Kaur H., Kesharwani P., J. Controlled Release 2021, 337, 589. [DOI] [PubMed] [Google Scholar]
  • 115. Sun K., Ko H., Park H., Seong M., Lee S., Yi H., Park H. W., Kim T., Pang C., Jeong H. E., Small 2018, 14, 1803411. [DOI] [PubMed] [Google Scholar]
  • 116. Yao S., Ren P., Song R., Liu Y., Huang Q., Dong J., O'Connor B. T., Zhu Y., Adv. Mater. 2020, 32, 1902343. [DOI] [PubMed] [Google Scholar]
  • 117. Lei D., Liu N., Su T., Zhang Q., Wang L., Ren Z., Gao Y., Adv. Mater. 2022, 34, 2110608. [DOI] [PubMed] [Google Scholar]
  • 118. Bostan L. E., Clarkin C. E., Mousa M., Worsley P. R., Bader D. L., Dawson J. I., Evans N. D., ACS Biomater. Sci. Eng. 2021, 7, 2716. [DOI] [PubMed] [Google Scholar]
  • 119. Zhang M. D., Zhang C., Li Z., Fu X. B., Huang S., Regen. Biomater. 2023, 10, rbac105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 120. Cao Y., Wang L., Zhang X., Lu Y., Wei Y., Liang Z., Hu Y., Huang D., Regen. Biomater. 2023, 10, rbad081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 121. Yao X., Chen X., Sun Y., Yang P., Gu X., Dai X., Regen. Biomater. 2024, 11, rbae009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 122. Gong X., Luo M., Wang M., Niu W., Wang Y., Lei B., Regen. Biomater. 2022, 9, rbab074. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 123. Yu H., Sun J., She K., Lv M., Zhang Y., Xiao Y., Liu Y., Han C., Xu X., Yang S., Wang G., Zang G., Regen. Biomater. 2023, 10, rbad071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 124. Liu Z., Xu J., Wang X., MedComm 2025, 6, 70113. [Google Scholar]
  • 125. Dreanca A., Muresan‐Pop M., Taulescu M., Tóth Z., Bogdan S., Pestean C., Oren S., Toma C., Popescu A., Páll E., Sevastre B., Baia L., Magyari K., Mater. Sci. Eng. C. Mater. Biol. Appl. 2021, 123, 112006. [DOI] [PubMed] [Google Scholar]
  • 126. Im P., Shin H., Kim J., Biomacromolecules 2024, 25, 1153. [DOI] [PubMed] [Google Scholar]
  • 127. Yaraghi N. A., Kisailus D., Annu. Rev. Phys. Chem. 2018, 69, 23. [DOI] [PubMed] [Google Scholar]
  • 128. Yu S., Hwang Y. H., Lee K. T., Kim S. O., Hwang J. Y., Hong S. H., Adv. Sci. 2022, 9, 2103561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 129. Lei Z., Wu P., Nat. Commun. 2018, 9, 1134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 130. Zhang X., Li G., Wu D., Zhang B., Hu N., Wang H., Liu J., Wu Y., Biosens. Bioelectron. 2019, 145, 111699. [DOI] [PubMed] [Google Scholar]
  • 131. Sheikholeslam M., Wright M. E. E., Jeschke M. G., Amini‐Nik S., Adv. Healthcare Mater. 2018, 7, 1700897. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 132. Savoji H., Godau B., Hassani M. S., Akbari M., Front. Bioeng. Biotechnol. 2018, 6, 86. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 133. Feldman D., Materials 2022, 15, 6366.36143676 [Google Scholar]
  • 134. Zhang J. H., Hu J. F., Chen B. S., Zhao T. B., Gu Z. P., Regen. Biomater. 2021, 8, rbaa059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 135. Zhang M., Xing J., Zhong Y., Zhang T., Liu X., Xing D., Mater. Today Bio 2024, 24, 100918. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 136. Jiang Y., Zhang Z., Wang Y., Li D., Coen C., Hwaun E., Chen G., Wu H., Zhong D., Niu S., Wang W., Saberi A., Lai J., Wu Y., Wang Y., Trotsyuk A. A., Loh K. Y., Shih C., Xu W., Liang K., Zhang K., Bai Y., Gurusankar G., Hu W., Jia W., Cheng Z., Dauskardt R. H., Gurtner G. C., Tok J. B., Deisseroth K., Soltesz I., Bao Z., Science 2022, 375, 6587. [DOI] [PubMed] [Google Scholar]
  • 137. Yang Y., Huang S., Ma Q., Li N., Li R., Wang Y., Liu H., Regen. Biomater. 2024, 11, rbae062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 138. Zhang Y., Zheng Z., Zhu S., Xu L., Zhang Q., Gao J., Ye M., Shen S., Xing J., Wu M., Xu R. X., Adv. Sci. 2025, 12, 2416267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 139. Kwak S., Song C. L., Lee J., Kim S., Nam S., Park Y., Lee J., Biomaterials 2024, 307, 122522. [DOI] [PubMed] [Google Scholar]
  • 140. Li S., Li J., Xu J., Shen Y., Shang X., Li H., Wang J., Liu Y., Qiang L., Qiao Z., Wang J., He Y., Hu Y., Adv. Mater. 2024, 36, 2406891. [DOI] [PubMed] [Google Scholar]
  • 141. Gao W., Cheng T., Tang Z., Zhang W., Xu Y., Han M., Zhou G., Tao C., Xu N., Xia H., Sun W., Regen. Biomater. 2024, 11, rbae010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 142. Lu Z., Du S., Li J., Zhang M., Nie H., Zhou X., Li F., Wei X., Wang J., Liu F., He C., Yang G., Gu Z., Adv. Mater. 2023, 35, 2303388. [DOI] [PubMed] [Google Scholar]
  • 143. Yang Q., Guo P., Lei P., Yang Q., Liu Y., Tian Y., Shi W., Zhu C., Lei M., Zeng R., Zhang C., Qu Y., Regen. Biomater. 2024, 11, rbae086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 144. Chang L., Xu Y., Wu Z., Shao Y., Yu D., Yang W., Ye L., Wang X., Li B., Yin Y., Regen. Biomater. 2023, 10, rbad023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 145. Fei Y., Yu X., Liu P., Ren H., Wei T., Cheng Q., Adv. Mater. 2024, 36, 2409812. [DOI] [PubMed] [Google Scholar]
  • 146. Wang H., Xiao C. S., Chen X. S., Acta Polym. Sin. 2024, 55, 1. [Google Scholar]
  • 147. Ansaf R. B., Ziebart R., Gudapati H., Simoes Torigoe R. M., Victorelli S., Passos J., Wyles S. P., Regen. Biomater. 2023, 10, rbad060. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 148. Liu T., Hao J., Lei H., Chen Y., Liu L., Jia L., Gu J., Kang H., Shi J., He J., Song Y., Tang Y., Fan D., Regen. Biomater. 2024, 11, rbae108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 149. Zhang C., Zhao Y. S., Adv. Mater. 2024, 2415856. [Google Scholar]
  • 150. Li Q., Wang L. H., Fan C. H., Ye D. K., Acta Polym. Sin. 2024, 55, 655. [Google Scholar]
  • 151. Li Y., Meng Q., Chen S., Ling P., Kuss M. A., Duan B., Wu S., Acta Biomater. 2023, 168, 78. [DOI] [PubMed] [Google Scholar]
  • 152. Yannas I. V., Regen. Biomater. 2018, 5, rby012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 153. Wang J., Fu S. J., Li H. S., Wu Y., Regen. Biomater. 2023, 10, rbad028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 154. Du J. Q., Zhang Y. F., Cheng Y. L., Acta Polym. Sin. 2024, 55, 624. [Google Scholar]
  • 155. Yang Y., Zhang C., Jiang Y., He Y., Cai J., Liang L., Chen Z., Pan S., Hua C., Wu K., Wang L., Zhang Z., Regen. Biomater. 2024, 11, rbad116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 156. Zhang T., Zhong X. C., Feng Z. X., Lin X. Y., Chen C. Y., Wang X. W., Guo K., Wang Y., Chen J., Du Y. Z., Zhuang Z. M., Wang Y., Tan W. Q., Bioact. Mater. 2025, 45, 322. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 157. Zhang Z., Fan C., Xu Q., Guo F., Li W., Zeng Z., Xu Y., Yu J., Ge H., Yang C., Chang J., Adv. Sci. 2024, 11, 2407718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 158. Xiong M., Yang X., Shi Z., Xiang J., Gao H., Ji S., Li Y., Pi W., Chen H., Zhang H., Wang M., Li Y., Hong Y., Liu D., Fu X., Dong Y., Sun X., Adv. Mater. 2024, 36, 2407322. [DOI] [PubMed] [Google Scholar]
  • 159. Zhang H., Wang J., Hu H., Ma L., Acta Biomater. 2025, 198, 161. [DOI] [PubMed] [Google Scholar]
  • 160. Sun X., Wang P., Tang L., Li N., Lou Y., Zhang Y., Li P., Adv. Funct. Mater. 2024, 34, 2411117. [Google Scholar]
  • 161. Wang Q., Zhang S., Jiang J., Chen S., Ramakrishna S., Zhao W., Yang F., Wu S., Regen. Biomater. 2024, 11, rbae063. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 162. Du M., Liu S., Lan N., Liang R., Liang S., Lan M., Feng D., Zheng L., Wei Q., Ma K., Regen. Biomater. 2024, 11, rbad114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 163. Su Y. L., Zhang M. D., Yu B. Y., Tian F., Zhu D. Z., Guo X., Wang Y. Z., Ding L., Li Z., Kong Y., Song W., Zhang C., Li J. J., Liang L. T., Du J. P., Liu Q. H., Kong Y., Fu X. B., Huang S., Small 2025, 21, 15. [Google Scholar]
  • 164. Meng H., Su J. L., Shen Q., Hu W. Z., Li P. X., Guo K. L., Liu X., Ma K., Zhong W. C., Chen S. Q., Ma L. Q., Hao Y. Y., Chen J. L., Jiang Y. F., Li L. L., Fu X. B., Zhang C. P., Adv. Healthcare Mater. 2025, 14, 18. [Google Scholar]
  • 165. Li J., Liu X., Tao W., Li Y., Du Y., Zhang S., Regen. Biomater. 2023, 10, rbac108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 166. Wang Y., Vizely K., Li C. Y., Shen K., Shakeri A., Khosravi R., Smith J. R., Alteza E. A. I. I., Zhao Y., Radisic M., Regen. Biomater. 2024, 11, rbae032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 167. Li Y., Wang Y., Ding Y., Fan X., Ye L., Pan Q., Zhang B., Li P., Luo K., Hu B., He B., Pu Y., ACS Nano 2024, 18, 17251. [DOI] [PubMed] [Google Scholar]
  • 168. Joorabloo A., Liu T., Adv. Colloid Interface Sci. 2024, 330, 103207. [DOI] [PubMed] [Google Scholar]
  • 169. Gültekin H. E., Yaşayan G., Bal‐Öztürk A., Bigham A., Simchi A., Zarepour A., Iravani S., Zarrabi A., Mater. Horiz. 2024, 11, 363. [DOI] [PubMed] [Google Scholar]
  • 170. Chang L., Du H., Xu F., Xu C., Liu H., Trends Biotechnol. 2024, 42, 31. [DOI] [PubMed] [Google Scholar]
  • 171. Liu W., Wang M., Cheng W., Niu W., Chen M., Luo M., Xie C., Leng T., Zhang L., Lei B., Bioact. Mater. 2021, 6, 721. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 172. Duan W., Jin Y., Cui Y., Xi F., Liu X., Wo F., Wu J., Biomaterials 2021, 272, 120772. [DOI] [PubMed] [Google Scholar]
  • 173. Nosrati H., Aramideh Khouy R., Nosrati A., Khodaei M., Banitalebi‐Dehkordi M., Ashrafi‐Dehkordi K., Sanami S., Alizadeh Z., J. Nanobiotechnology 2021, 19, 1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 174. Xue J. M., Qin C., Wu C. T., Regen. Biomater. 2023, 10, rbad032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 175. Hong Y. Y., Wang M. Y., Hu D. R., Wang Y. J., Ji S. F., Xiang J. B., Zhang H. L., Chen H. T., Li Y., Xiong M. C., Pi W., Wang Q. Y., Yang X. L., Li Y. Y., Shui C. C., Wang X. L., Fu X. B., Sun X. Y., Adv. Funct. Mater. 2024, 34, 16. [Google Scholar]
  • 176. Wang H., Sun D., Lin W., Fang C., Cheng K., Pan Z., Wang D., Song Z., Long X., Bioact. Mater. 2023, 28, 420. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 177. Kacvinská K., Pavliňáková V., Poláček P., Michlovská L., Blahnová V. H., Filová E., Knoz M., Lipový B., Holoubek J., Faldyna M., Pavlovský Z., Vícenová M., Cvanová M., Jarkovský J., Vojtová L., J. Nanobiotechnology 2023, 21, 80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 178. Jiang L., Dong J., Jiang M., Tan W., Zeng Y., Liu X., Wang P., Jiang H., Zhou J., Liu X., Li H., Liu L., Biomaterials 2025, 318, 123196. [DOI] [PubMed] [Google Scholar]
  • 179. Lee J., Rabbani C. C., Gao H., Steinhart M. R., Woodruff B. M., Pflum Z. E., Kim A., Heller S., Liu Y., Shipchandler T. Z., Koehler K. R., Nature 2020, 582, 399. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 180. Wang M., Luo Y., Wang T., Wan C., Pan L., Pan S., He K., Neo A., Chen X., Adv. Mater. 2021, 33, 2003014. [DOI] [PubMed] [Google Scholar]
  • 181. Niu H., Li H., Gao S., Li Y., Wei X., Chen Y., Yue W., Zhou W., Shen G., Adv. Mater. 2022, 34, 2202622. [DOI] [PubMed] [Google Scholar]
  • 182. Phatale V., Vaiphei K. K., Jha S., Patil D., Agrawal M., Alexander A., J. Controlled Release 2022, 351, 361. [DOI] [PubMed] [Google Scholar]
  • 183. Ding S., Alexander E., Liang H., Kulchar R. J., Singh R., Herzog R. W., Daniell H., Leong K. W., Chem. Rev. 2025, 125, 4009. [DOI] [PubMed] [Google Scholar]
  • 184. Sabbagh F., Kim B. S., J. Controlled Release 2022, 341, 132. [DOI] [PubMed] [Google Scholar]
  • 185. Karve T., Dandekar A., Agrahari V., Melissa Peet M., Banga A. K., Doncel G. F., Adv. Drug Delivery Rev. 2024, 210, 115326. [DOI] [PubMed] [Google Scholar]
  • 186. Bi D., Qu F., Xiao W., Wu J., Liu P., Du H., Xie Y., Liu H., Zhang L., Tao J., Liu Y., Zhu J., ACS Nano 2023, 17, 4346. [DOI] [PubMed] [Google Scholar]
  • 187. Zhang H., Pan Y., Hou Y., Li M., Deng J., Wang B., Hao S., Small 2024, 20, 2306944. [DOI] [PubMed] [Google Scholar]
  • 188. Wang C., He G., Zhao H., Lu Y., Jiang P., Li W., Adv. Mater. 2024, 36, 2311246. [DOI] [PubMed] [Google Scholar]
  • 189. Cao D. L., Chen X., Cao F., Guo W., Tang J. Y., Cai C. Y., Cui S. Q., Yang X. W., Yu L., Su Y., Ding J. D., Adv. Funct. Mater. 2021, 31, 12. [Google Scholar]
  • 190. Chen Y., Shui M., Yuan Q., Vong C. T., Yang Z., Chen Z., Wang S., J. Controlled Release 2023, 358, 510. [DOI] [PubMed] [Google Scholar]
  • 191. Xu F., Fei Z., Dai H., Xu J., Fan Q., Shen S., Zhang Y., Ma Q., Chu J., Peng F., Zhou F., Liu Z., Wang C., Adv. Mater. 2022, 34, 2106265. [DOI] [PubMed] [Google Scholar]
  • 192. Xu K., Wang Y., Xie Y., Zhang X., Chen W., Li Z., Wang T., Yang X., Guo B., Wang L., Zhu X., Zhang X., Regen. Biomater. 2022, 9, rbac050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 193. Huang F., Lu X., Kuai L., Ru Y., Jiang J., Song J., Chen S., Mao L., Li Y., Li B., Dong H., Shi J., J. Am. Chem. Soc. 2024, 146, 3186. [DOI] [PubMed] [Google Scholar]
  • 194. Wu C., Chen W., Yan S., Zhong J., Du L., Yang C., Pu Y., Li Y., Lin J., Zeng M., Zhang X., Regen. Biomater. 2024, 11, rbae019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 195. Dartora V. F. C., Passos J. S., Osorio B., Hung R., Nguyen M., Wang A., Panitch A., J. Controlled Release 2023, 362, 591. [DOI] [PubMed] [Google Scholar]
  • 196. Liu X., Qin Y., Dong L., Han Z., Liu T., Tang Y., Yu Y., Ye J., Tao J., Zeng X., Feng J., Zhang X. Z., Bioact. Mater. 2023, 21, 253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 197. Jia Y., Hu J., An K., Zhao Q., Dang Y., Liu H., Wei Z., Geng S., Xu F., Nat. Commun. 2023, 14, 2478. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 198. Yan Y., Liang H., Liu X., Liu L., Chen Y., Biomaterials 2021, 276, 121027. [DOI] [PubMed] [Google Scholar]
  • 199. Keam S. J., Drugs 2022, 82, 1221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 200. Silverberg J. I., Boguniewicz M., Quintana F. J., Clark R. A., Gross L., Hirano I., Tallman A. M., Brown P. M., Fredericks D., Rubenstein D. S., McHale K. A., J. Allergy Clin. Immunol. 2024, 154, 1. [DOI] [PubMed] [Google Scholar]
  • 201. Xu J., Chen H., Chu Z., Li Z., Chen B., Sun J., Lai W., Ma Y., He Y., Qian H., Wang F., Xu Y., J. Nanobiotechnology 2022, 20, 155. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 202. Viswanath D. I., Liu H. C., Huston D. P., Chua C. Y. X., Grattoni A., Biomaterials 2022, 280, 121297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 203. Liu L., Pan Y., Zhao C., Huang P., Chen X., Rao L., ACS Nano 2023, 17, 3225. [DOI] [PubMed] [Google Scholar]
  • 204. Yan S., Luo Z., Li Z., Wang Y., Tao J., Gong C., Liu X., Angew. Chem. Int. Ed. Engl. 2020, 59, 17332. [DOI] [PubMed] [Google Scholar]
  • 205. Zhang B., Gong J., He L., Khan A., Xiong T., Shen H., Li Z., Front. Bioeng. Biotechnol. 2022, 10, 1083640. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 206. Corduff N., J. Cosmet. Dermatol. 2023, 22, 8. [Google Scholar]
  • 207. Li H., Xu X., Wu L., Chen X., Akhter H., Wang Y., Song P., Liao X., Zhang Z., Li Z., Zhou C., Cen Y., Ai H., Zhang X., Regen. Biomater. 2023, 10, rbad005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 208. Gao J., Guo Z., Zhang Y., Liu Y., Xing F., Wang J., Luo X., Kong Y., Zhang G., Regen. Biomater. 2023, 10, rbac110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 209. Dan X., Li S., Chen H., Xue P., Liu B., Ju Y., Lei L., Li Y., Fan X., Mater. Today. Bio. 2024, 28, 101210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 210. Yao L., Ling B., Huang W., Wang Q., Cai X., Xiao J., Regen. Biomater. 2024, 11, rbae085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 211. Lee D. H., Choi Y., Lee M. H., Park J. C., Regen. Biomater. 2024, 11, rbae069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 212. Zhang Y., Liang H., Luo Q., Chen J., Zhao N., Gao W., Pu Y., He B., Xie J., Regen. Biomater. 2021, 8, rbab042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 213. Dong Y., Zhang Y., Yu H., Zhou L., Zhang Y., Wang H., Hu Z., Luo S., Front. Immunol. 2024, 15, 1394530. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 214. Chang S., Zhao M., Gao W., Cao J., He B., J. Mater. Chem. B 2025, 13, 904. [DOI] [PubMed] [Google Scholar]
  • 215. Cao M., Tao L., Zhang Y., Zhou L., Wu S., Zhou H., Ge Y., Zou Y., Luo S., Biochim. Biophys. Acta Mol. Cell Res. 2025, 1872, 119931. [DOI] [PubMed] [Google Scholar]
  • 216. Ray S., Adelnia H., Ta H. T., Biomater. Sci. 2021, 9, 5714. [DOI] [PubMed] [Google Scholar]
  • 217. Cai C. Y., Tang J. Y., Zhang Y., Rao W. H., Cao D. L. G., Guo W., Yu L., Ding J. D., Adv. Healthcare Mater. 2022, 11, 16. [DOI] [PubMed] [Google Scholar]
  • 218. Shi S., Zhang J., Quan S., Yang Y., Yao L., Xiao J., Int. J. Biol. Macromol. 2024, 272, 132857. [DOI] [PubMed] [Google Scholar]
  • 219. Ryu T. K., Lee H., Yon D. K., Nam D. Y., Lee S. Y., Shin B. H., Choi G. W., Jeon D. S., Oh B. B., Kim J. H., Yoon Y., Kim H. J., Duteil L., Bruno‐Bonnet C., Heo C. Y., Kang S. M., PLoS One 2022, 17, 0277188. [Google Scholar]
  • 220. Kee L. T., Foo J. B., How C. W., Nur Azurah A. G., Chan H. H., Mohd Yunus M. H., Ng S. N., Ng M. H., Law J. X., Int. J. Nanomedicine. 2025, 20, 1561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 221. Xiong M., Zhang Q., Hu W., Zhao C., Lv W., Yi Y., Wang Y., Tang H., Wu M., Wu Y., Pharmacol. Res. 2021, 166, 105490. [DOI] [PubMed] [Google Scholar]
  • 222. Wang X., Zhong C., Zhong Y., Fan Z., Liu Z., Xu P., Deng X., Guo J., Sawant T. R., Zhou M., Wang Q., Liu H., Liu J., Carbohydr. Polym. 2025, 353, 123270. [DOI] [PubMed] [Google Scholar]
  • 223. Kim J., Salvatore G. A., Araki H., Chiarelli A. M., Xie Z., Banks A., Sheng X., Liu Y., Lee J. W., Jang K., Heo S. Y., Cho K., Luo H., Zimmerman B., Kim J., Yan L., Feng X., Xu S., Fabiani M., Gratton G., Huang Y., Paik U., Rogers J. A., Sci. Adv. 2016, 2, 1600418. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 224. Xu C., Yang Y., Gao W., Matter 2020, 2, 1414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 225. Jiang Y., Liang F., Li H. Y., Li X., Fan Y. J., Cao J. W., Yin Y. M., Wang Y., Wang Z. L., Zhu G., ACS Nano 2022, 16, 746. [DOI] [PubMed] [Google Scholar]
  • 226. Bei Z., Chen Y., Li S., Zhu Z., Xiong J., He R., Zhu C., Cao Y., Qian Z., Chem. Eng. J. 2023, 451, 138675. [Google Scholar]
  • 227. Zhu Y., Li J., Kim J., Li S., Zhao Y., Bahari J., Eliahoo P., Li G., Kawakita S., Haghniaz R., Gao X., Falcone N., Ermis M., Kang H., Liu H., Kim H., Tabish T., Yu H., Li B., Akbari M., Emaminejad S., Khademhosseini A., Biomaterials 2023, 296, 122075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 228. Li X., He L., Li Y., Chao M., Li M., Wan P., Zhang L., ACS Nano 2021, 15, 7765. [DOI] [PubMed] [Google Scholar]
  • 229. Zhu Y., Haghniaz R., Hartel M. C., Guan S., Bahari J., Li Z., Baidya A., Cao K., Gao X., Li J., Wu Z., Cheng X., Li B., Emaminejad S., Weiss P. S., Khademhosseini A., Adv. Mater. 2023, 35, 2209300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 230. Hong S., Yu T., Wang Z., Lee C. H., Biomaterials 2025, 314, 122862. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 231. Liu S. Z., Guo W. T., Chen H., Yin Z. X., Tang X. G., Sun Q. J., Small 2024, 20, 2405520. [DOI] [PubMed] [Google Scholar]
  • 232. Wang W., Zhou H., Xu Z., Li Z., Zhang L., Wan P., Adv. Mater. 2024, 36, 2401035. [DOI] [PubMed] [Google Scholar]
  • 233. Liu X., Ji X., Zhu R., Gu J., Liang J., Adv. Mater. 2024, 36, 2309508. [DOI] [PubMed] [Google Scholar]
  • 234. Zhang B., Li J., Zhou J., Chow L., Zhao G., Huang Y., Ma Z., Zhang Q., Yang Y., Yiu C. K., Li J., Chun F., Huang X., Gao Y., Wu P., Jia S., Li H., Li D., Liu Y., Yao K., Shi R., Chen Z., Khoo B. L., Yang W., Wang F., Zheng Z., Wang Z., Yu X., Nature 2024, 628, 8006. [DOI] [PubMed] [Google Scholar]
  • 235. Zhao Y., Gao W., Dai K., Wang S., Yuan Z., Li J., Zhai W., Zheng G., Pan C., Liu C., Shen C., Adv. Mater. 2021, 33, 2102332. [DOI] [PubMed] [Google Scholar]
  • 236. Arwani R. T., Tan S. C. L., Sundarapandi A., Goh W. P., Liu Y., Leong F. Y., Yang W., Zheng X. T., Yu Y., Jiang C., Ang Y. C., Kong L., Teo S. L., Chen P., Su X., Li H., Liu Z., Chen X., Yang L., Liu Y., Nat. Mater. 2024, 23, 1115. [DOI] [PubMed] [Google Scholar]
  • 237. Kaewpradub K., Veenuttranon K., Jantapaso H., Mittraparp‐Arthorn P., Jeerapan I., Nanomicro. Lett. 2024, 17, 71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 238. Ren H., Zhang Z., Cheng X., Zou Z., Chen X., He C., Sci. Adv. 2023, 9, adh4327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 239. Li Y., Liu J., Lian C., Yang H., Zhang M., Wang Y., Dai H., Regen. Biomater. 2024, 11, rbad101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 240. Guo W., Zhao B., Shafiq M., Yu X., Shen Y., Cui J., Chen Y., Cai P., Yuan Z., El‐Newehy M., El‐Hamshary H., Morsi Y., Sun B., Pan J., Mo X., Regen. Biomater. 2023, 10, rbad019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 241. Wang P., Pu Y., Ren Y., Liu S., Yang R., Tan X., Zhang W., Shi T., Li S., Chi B., Sci. China Mater. 2022, 65, 246. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 242. Liu L., Zhao F., Zhang Y., Yu X., Chen H., Rong H., Yuan H., Zhang J., Deng L., Li S., Dong A., ACS Biomater. Sci. Eng. 2025, 11, 595. [DOI] [PubMed] [Google Scholar]
  • 243. Li S., Liu L., Qiao F., Ma J., Miao H., Gao S., Ma Y., Yu X., Liu S., Yuan H., Dong A., Adv. Healthcare Mater. 2024, 13, 2402268. [DOI] [PubMed] [Google Scholar]
  • 244. Kim H., Jang J., Han W., Hwang H., Jang J., Kim J. Y., Cho D., Biomaterials 2023, 292, 121941. [DOI] [PubMed] [Google Scholar]
  • 245. Montazerian H., Davoodi E., Baidya A., Baghdasarian S., Sarikhani E., Meyer C. E., Haghniaz R., Badv M., Annabi N., Khademhosseini A., Weiss P. S., Chem. Rev. 2022, 122, 12864. [DOI] [PubMed] [Google Scholar]
  • 246. Yang Z., Chen L., Liu J., Zhuang H., Lin W., Li C., Zhao X., Adv. Mater. 2023, 35, 2301849. [DOI] [PubMed] [Google Scholar]
  • 247. Cong J., Cheng Y., Liu T., Cai X., Xu J., Guo R., He R., Xiang Q., Regen. Biomater. 2025, 12, rbaf027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 248. Gao J. M., Yu X. Y., Wang X. L., He Y. N., Ding J. D., Engineering 2022, 13, 31. [Google Scholar]
  • 249. Peng Y., Liu Q., He T., Ye K., Yao X., Ding J., Biomaterials 2018, 178, 467. [DOI] [PubMed] [Google Scholar]
  • 250. Liu W., Liu R., Chu L. T., Wang X., Wu J., Ding J., Chen T. H., Regen. Biomater. 2025, rbaf043. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 251. Castaño O., Pérez‐Amodio S., Navarro‐Requena C., Mateos‐Timoneda M. Á., Engel E., Adv. Drug Delivery Rev. 2018, 129, 95. [DOI] [PubMed] [Google Scholar]
  • 252. Zhang H. J., Zhang W. Q., Qiu H., Zhang G., Li X., Qi H. P., Guo J. Z., Qian J., Shi X. L., Gao X., Shi D. K., Zhang D. Y., Gao R. L., Ding J. D., Adv. Healthcare Mater. 2022, 11, 16. [DOI] [PubMed] [Google Scholar]
  • 253. Gao C., Wang G., Wang L., Wang Q., Wang H., Yu L., Liu J., Ding J., Chin. J. Polym. Sci. 2023, 41, 51. [Google Scholar]
  • 254. Liu R., Wang H., Ding J., ACS Appl. Bio Mater. 2024, 7, 3997. [DOI] [PubMed] [Google Scholar]
  • 255. Shi D., Kang Y., Jiang Z., Li X., Zhang H., Wang Q., Guo J., Jiang H., Luo Q., Ding J., Biomaterials 2024, 304, 122411. [DOI] [PubMed] [Google Scholar]
  • 256. Lagneau N., Tournier P., Halgand B., Loll F., Maugars Y., Guicheux J., Le Visage C., Delplace V., Bioact. Mater. 2023, 24, 438. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 257. Liu Z., Wan X., Wang Z. L., Li L., Adv. Mater. 2021, 33, 2007429. [DOI] [PubMed] [Google Scholar]
  • 258. Wu L. B., Ding J. D., Biomaterials 2004, 25, 5821. [DOI] [PubMed] [Google Scholar]
  • 259. Gao C., Yao L., Liu X., Wang Z., Hu R., Ding J., Ding Y., Chen G., ACS Appl. Mater. Interfaces 2024, 16, 67458. [DOI] [PubMed] [Google Scholar]
  • 260. Gao J. M., Ding X. Q., Yu X. Y., Chen X. B., Zhang X. Y., Cui S. Q., Shi J. Y., Chen J., Yu L., Chen S. Y., Ding J. D., Adv. Healthcare Mater. 2021, 10, 13. [Google Scholar]
  • 261. Deng J. J., Wang X., Zhang W. H., Sun L. Y., Han X. X., Tong X. Q., Yu L. M., Ding J. D., Yu L., Liu Y. H., Adv. Funct. Mater. 2023, 33, 22. [Google Scholar]
  • 262. Huang D. Y., Li Y. H., Ma Z. H., Lin H., Zhu X. D., Xiao Y., Zhang X. D., Sci. Adv. 2023, 9, 16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 263. Koçer G., Ter Schiphorst J., Hendrikx M., Kassa H. G., Leclère P., Schenning A. P. H. J., Jonkheijm P., Adv. Mater. 2017, 29, 1606407. [DOI] [PubMed] [Google Scholar]
  • 264. Li H., Li B., Lv D., Li W., Lu Y., Luo G., Adv. Drug Delivery Rev. 2023, 196, 114778. [DOI] [PubMed] [Google Scholar]
  • 265. Xie W., Wei X., Kang H., Jiang H., Chu Z., Lin Y., Hou Y., Wei Q., Adv. Sci. 2023, 10, 2204594. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 266. Cherry C., Maestas D. R., Han J., Andorko J. I., Cahan P., Fertig E. J., Garmire L. X., Elisseeff J. H., Nat. Biomed. Eng. 2021, 5, 1228. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 267. Feng Y., Xiao K., Chen J., Lin J., He Y., He X., Cheng F., Li Z., Li J., Luo F., Tan H., Fu Q., Carbohydr. Polym. 2023, 320, 121238. [DOI] [PubMed] [Google Scholar]
  • 268. Butenko S., Nagalla R. R., Guerrero‐Juarez C. F., Palomba F., David L., Nguyen R. Q., Gay D., Almet A. A., Digman M. A., Nie Q., Scumpia P. O., Plikus M. V., Liu W. F., Nat. Commun. 2024, 15, 6820. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 269. Guan Q., Hou S., Wang K., Li L., Cheng Y., Zheng M., Liu C., Zhao X., Zhou J., Li P., Niu X., Wang L., Fan Y., Biomaterials 2025, 318, 123192. [DOI] [PubMed] [Google Scholar]
  • 270. Zhang Y., Sheng R., Chen J., Wang H., Zhu Y., Cao Z., Zhao X., Wang Z., Liu C., Chen Z., Zhang P., Kuang B., Zheng H., Shen C., Yao Q., Zhang W., Adv. Mater. 2023, 35, 2210517. [DOI] [PubMed] [Google Scholar]
  • 271. Shafiee A., Sun J., Ahmed I. A., Phua F., Rossi G. R., Lin C., Souza‐Fonseca‐Guimaraes F., Wolvetang E. J., Brown J., Khosrotehrani K., Small 2024, 20, 2304879. [DOI] [PubMed] [Google Scholar]
  • 272. Xie Q., Yan C., Liu G., Bian L., Zhang K., Adv. Mater. 2024, 36, 2406434. [DOI] [PubMed] [Google Scholar]
  • 273. Xu Y., Peng J., Dong X., Xu Y., Li H., Chang J., Acta Biomater. 2017, 55, 249. [DOI] [PubMed] [Google Scholar]
  • 274. Huang R., Wang J., Chen H., Shi X., Wang X., Zhu Y., Tan Z., Biomater. Sci 2019, 7, 4248. [DOI] [PubMed] [Google Scholar]
  • 275. Rahmati M., Silva E. A., Reseland J. E., Heyward C. A., Haugen H. J., Chem. Soc. Rev. 2020, 49, 5178. [DOI] [PubMed] [Google Scholar]
  • 276. Wang Q., Liu Q., Gao J., He J., Zhang H., Ding J., ACS Appl. Mater. Interfaces 2023, 15, 6142. [DOI] [PubMed] [Google Scholar]
  • 277. Shen Y., Zhang W., Xie Y., Li A., Wang X., Chen X., Liu Q., Wang Q., Zhang G., Liu Q., Liu J., Zhang D., Zhang Z., Ding J., Biomaterials 2021, 279, 121208. [DOI] [PubMed] [Google Scholar]
  • 278. Tang J., Peng R., Ding J. D., Biomaterials 2010, 31, 2470. [DOI] [PubMed] [Google Scholar]
  • 279. Peng R., Yao X., Ding J. D., Biomaterials 2011, 32, 8048. [DOI] [PubMed] [Google Scholar]
  • 280. Huang J., Gräter S. V., Corbellini F., Rinck S., Bock E., Kemkemer R., Kessler H., Ding J., Spatz J. P., Nano Lett. 2009, 9, 1111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 281. Dosta P., Cryer A. M., Prado M., Artzi N., Nat. Rev. Bioeng. 2025, 3, 660. [Google Scholar]
  • 282. Yu Y., Wang X., Zhu Y., He Y., Xue H., Ding J., Regen. Biomater. 2022, 9, rbac078. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 283. Wang X., Lei X., Yu Y., Miao S., Tang J., Fu Y., Ye K., Shen Y., Shi J., Wu H., Zhu Y., Yu L., Pei G., Bi L., Ding J., Biomater. Sci. 2021, 9, 5192. [DOI] [PubMed] [Google Scholar]
  • 284. Yao X., Peng R., Ding J. D., Adv. Mater. 2013, 25, 5257. [DOI] [PubMed] [Google Scholar]
  • 285. Viswanathan P., Ondeck M. G., Chirasatitsin S., Ngamkham K., Reilly G. C., Engler A. J., Battaglia G., Biomaterials 2015, 52, 140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 286. Liu Q., Zheng S., Ye K., He J., Shen Y., Cui S., Huang J., Gu Y., Ding J., Biomaterials 2020, 263, 120327. [DOI] [PubMed] [Google Scholar]
  • 287. He J., Liu Q., Zheng S., Shen R., Wang X., Gao J., Wang Q., Huang J., Ding J., ACS Appl. Mater. Interfaces 2021, 13, 42344. [DOI] [PubMed] [Google Scholar]
  • 288. He J., Shen R., Liu Q., Zheng S., Wang X., Gao J., Wang Q., Huang J., Ding J., ACS Appl. Mater. Interfaces 2022, 14, 37436. [DOI] [PubMed] [Google Scholar]
  • 289. Yao X., Ding J., ACS Appl. Mater. Interfaces 2020, 12, 27971. [DOI] [PubMed] [Google Scholar]
  • 290. Zhang L., Wang Z., Das J., Labib M., Ahmed S., Sargent E. H., Kelley S. O., Angew. Chem. Int. Ed. Engl. 2019, 58, 14519. [DOI] [PubMed] [Google Scholar]
  • 291. Yao Y., Zaw A. M., Anderson D. E. J., Jeong Y., Kunihiro J., Hinds M. T., Yim E. K. F., Bioact. Mater. 2023, 22, 535. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 292. López C., Adv. Mater. 2023, 35, 2208683. [Google Scholar]
  • 293. Zhang Z. R., Zhou X. H., Fang Y. C., Xiong Z., Zhang T., Bioact. Mater. 2025, 45, 201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 294. Li Z., Song P., Li G., Han Y., Ren X., Bai L., Su J., Mater. Today Bio 2024, 25, 101014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 295. Nosrati H., Nosrati M., Biomimetics 2023, 8, 442.37754193 [Google Scholar]
  • 296. Karaoglu I. C., Kebabci A. O., Kizilel S., ACS Appl. Mater. Interfaces 2023, 15, 44796. [DOI] [PubMed] [Google Scholar]
  • 297. Chen H., Liu Y., Balabani S., Hirayama R., Huang J., Research 0197, 6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 298. Seifermann M., Reiser P., Friederich P., Levkin P. A., Small Methods 2023, 7, 2300553. [DOI] [PubMed] [Google Scholar]
  • 299. Pollice R., Dos Passos Gomes G., Aldeghi M., Hickman R. J., Krenn M., Lavigne C., Lindner‐D'Addario M., Nigam A., Ser C. T., Yao Z., Aspuru‐Guzik A., Acc. Chem. Res. 2021, 54, 849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 300. Fu X., Cheng W., Wan G., Yang Z., Tee B. C. K., Chem. Rev. 2024, 124, 9899. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 301. Duan S., Shi Q., Hong J., Zhu D., Lin Y., Li Y., Lei W., Lee C., Wu J., ACS Nano 2023, 17, 1355. [DOI] [PubMed] [Google Scholar]
  • 302. Kerner J., Dogan A., von Recum H., Acta Biomater. 2021, 130, 54. [DOI] [PubMed] [Google Scholar]
  • 303. Dai X., Chen Y., Adv. Mater. 2023, 35, 2204798. [DOI] [PubMed] [Google Scholar]
  • 304. Zhou B., Li X., Pan Y., He B., Gao B., Colloids Surf. B Biointerfaces 2025, 255, 114970. [DOI] [PubMed] [Google Scholar]
  • 305. Ejeromedoghene O., Kumi M., Akor E., Zhang Z., Adv. Colloid Interface Sci. 2025, 336, 103360. [DOI] [PubMed] [Google Scholar]
  • 306. Singh A. V., Ansari M. H. D., Rosenkranz D., Maharjan R. S., Kriegel F. L., Gandhi K., Kanase A., Singh R., Laux P., Luch A., Adv. Healthcare Mater. 2020, 9, 1901862. [DOI] [PubMed] [Google Scholar]
  • 307. Jiang Z., Feng J., Wang F., Wang J., Wang N., Zhang M., Hsieh C., Hou T., Cui W., Ma L., Adv. Mater. 2025, 37, 2500043. [DOI] [PubMed] [Google Scholar]
  • 308. Salthouse D., Novakovic K., Hilkens C. M. U., Ferreira A. M., Acta Biomater. 2023, 155, 1. [DOI] [PubMed] [Google Scholar]
  • 309. Xu C., Solomon S. A., Gao W., Nat. Mach. Intell. 2023, 5, 1344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 310. Koo J. H., Lee Y. J., Kim H. J., Matusik W., Kim D., Jeong H., Annu. Rev. Biomed. Eng. 2024, 26, 331. [DOI] [PubMed] [Google Scholar]
  • 311. Niu H., Li H., Zhang Q., Kim E., Kim N., Li Y., Small 2024, 20, 2308127. [DOI] [PubMed] [Google Scholar]
  • 312. Wan C., Chen G., Fu Y., Wang M., Matsuhisa N., Pan S., Pan L., Yang H., Wan Q., Zhu L., Chen X., Adv. Mater. 2018, 30, 1801291. [DOI] [PubMed] [Google Scholar]
  • 313. Chortos A., Liu J., Bao Z., Nat. Mater. 2016, 15, 937. [DOI] [PubMed] [Google Scholar]
  • 314. Yu Y., Li J., Solomon S. A., Min J., Tu J., Guo W., Xu C., Song Y., Gao W., Sci. Robot. 2022, 7, abn0495. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 315. Xu H., Zheng W., Zhang Y., Zhao D., Wang L., Zhao Y., Wang W., Yuan Y., Zhang J., Huo Z., Wang Y., Zhao N., Qin Y., Liu K., Xi R., Chen G., Zhang H., Tang C., Yan J., Ge Q., Cheng H., Lu Y., Gao L., Nat. Commun. 2023, 14, 7769. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 316. Beltrami E. J., Brown A. C., Salmon P. J., Leffell D. J., Ko J. M., Grant‐Kels J. M., J. Am. Acad. Dermatol. 2022, 87, 1336. [DOI] [PubMed] [Google Scholar]
  • 317. Jones O. T., Matin R. N., Van Der Schaar M., Prathivadi Bhayankaram K., Ranmuthu C. K. I., Islam M. S., Behiyat D., Boscott R., Calanzani N., Emery J., Williams H. C., Walter F. .M., Lancet Digit. Health. 2022, 4, 466. [DOI] [PubMed] [Google Scholar]
  • 318. Liu H., Sun W., Cai W., Luo K., Lu C., Jin A., Zhang J., Liu Y., Theranostics 2025, 15, 1662. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 319. Christman K. L., Science 2019, 363, 340. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 320. Wang L., Wan F., Xu Y., Xie S., Zhao T., Zhang F., Yang H., Zhu J., Gao J., Shi X., Wang C., Lu L., Yang Y., Yu X., Chen S., Sun X., Ding J., Chen P., Ding C., Xu F., Yu H., Peng H., Nat. Nanotechnol. 2023, 18, 1085. [DOI] [PubMed] [Google Scholar]
  • 321. Yu X. Y., Wang P., Gao J. M., Fu Y., Wang Q. S., Chen J., Chen S. Y., Ding J. D., Biofabrication 2024, 16, 16. [DOI] [PubMed] [Google Scholar]
  • 322. Wang Q., Gao C., Zhai H., Peng C., Yu X., Zheng X., Zhang H., Wang X., Yu L., Wang S., Ding J., Adv. Healthcare Mater. 2024, 13, 2303395. [DOI] [PubMed] [Google Scholar]
  • 323. Shi D., Kang Y., Wang W., Liu R., Tang Q., Li Z., Jiang H., Ding J., Regen. Biomater. 2025, 12, rbaf016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 324. Zhang W. Q., Gao X., Zhang H. J., Sun G. Y., Zhang G., Li X., Qi H. P., Guo J. Z., Qin L., Shi D. K., Shi X. L., Li H. F., Zhang D. Y., Guo W., Ding J. D., Nat. Commun. 2024, 15, 13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 325. Li B., Xie Z., Wang Q., Chen X., Liu Q., Wang W., Shen Y., Liu J., Li A., Li Y., Zhang G., Liu J., Zhang D., Liu C., Wang S., Xie Y., Zhang Z., Ding J., Biomaterials 2021, 274, 120851. [DOI] [PubMed] [Google Scholar]
  • 326. Wang G., Gao C., Xiao B., Zhang J., Jiang X., Wang Q., Guo J., Zhang D., Liu J., Xie Y., Shu C., Ding J., Regen. Biomater. 2022, 9, rbac049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 327. Tan J., Fang Y., Wang K., Wei M., Zhang Z., Wang L., Chen S., Pan J., Adv. Funct. Mater. 2025, 2417798. [Google Scholar]
  • 328. Liu S., Xiang Y., Liu Z., Li L., Dang R., Zhang H., Wei F., Chen Y., Yang X., Mao M., Zhang Y. S., Song J., Zhang X., Adv. Mater. 2024, 36, 2309774. [DOI] [PubMed] [Google Scholar]
  • 329. Fu Y., Okuro K., Ding J. D., Aida T., Angew. Chem. Int. Ed. Engl. 2025, 64, 7. [DOI] [PubMed] [Google Scholar]
  • 330. Zhang H., Li X., Qu Z., Zhang W., Wang Q., Cao D., Wang Y., Wang X., Wang Y., Yu L., Ding J., Regen. Biomater. 2024, 11, rbad112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 331. Guo W., Cao D., Rao W., Sun T., Wei Y., Wang Y., Yu L., Ding J., ACS Appl. Mater. Interfaces 2023, 15, 42113. [DOI] [PubMed] [Google Scholar]
  • 332. Wu Y., Liu P., Mehrjou B., Chu P. K., Adv. Mater. 2024, 36, 2305940. [DOI] [PubMed] [Google Scholar]
  • 333. Gao J., Xu X., Yu X., Fu Y., Zhang H., Gu S., Cao D., Guo Q., Xu L., Ding J., Regen. Biomater. 2023, 10, rbad035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 334. Rao W. H., Yu L., Ding J. D., Chin. J. Polym. Sci. 2023, 41, 745. [Google Scholar]
  • 335. Cao D. L. G., Guo W., Cai C. Y., Tang J. Y., Rao W. H., Wang Y., Wang Y. B., Yu L., Ding J. D., Adv. Funct. Mater. 2022, 32, 16. [Google Scholar]
  • 336. Cui S. Q., Yu L., Ding J. D., Macromolecules 6405, 2018, 51. [Google Scholar]
  • 337. Qi Y., Qi H., He Y., Lin W., Li P., Qin L., Hu Y., Chen L., Liu Q., Sun H., Liu Q., Zhang G., Cui S., Hu J., Yu L., Zhang D., Ding J., ACS Appl. Mater. Interfaces 2018, 10, 182. [DOI] [PubMed] [Google Scholar]
  • 338. Shin Y., Lee H. S., Kim J., An Y., Kim Y., Hwang N. S., Kim D., Biomaterials 2025, 314, 122802. [DOI] [PubMed] [Google Scholar]
  • 339. Lou P., Liu S., Wang Y., Lv K., Zhou X., Li L., Zhang Y., Chen Y., Cheng J., Lu Y., Liu J., Adv. Mater. 2023, 35, 2300602. [DOI] [PubMed] [Google Scholar]
  • 340. Wei Y. M., Cui S. Q., Yu L., Ding J. D., Macromolecules 2023, 56, 2619. [Google Scholar]
  • 341. Wang G., Feng Y., Gao C., Zhang X., Wang Q., Zhang J., Zhang H., Wu Y., Li X., Wang L., Fu Y., Yu X., Zhang D., Liu J., Ding J., Regen. Biomater. 2023, 10, rbad056. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 342. Narkar A. R., Tong Z., Soman P., Henderson J. H., Biomaterials 2022, 283, 121450. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 343. Li X., Ding J., Regen. Biomater. 2023, 10, rbad007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 344. Tang J., Cai C., Cao D., Rao W., Guo W., Yu L., Ding J., Biomater. Sci. 2022, 10, 4561. [DOI] [PubMed] [Google Scholar]
  • 345. Yu X., Li G., Zheng Y., Gao J., Fu Y., Wang Q., Huang L., Pan X., Ding J., Regen. Biomater. 2022, 9, rbac007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 346. Yu L., Ding J. D., Chem. Soc. Rev. 2008, 37, 1473. [DOI] [PubMed] [Google Scholar]
  • 347. Yu L., Zhang H., Ding J. D., Angew. Chem. Int. Ed. Engl. 2006, 45, 2232. [DOI] [PubMed] [Google Scholar]
  • 348. Kostiainen M. A., Priimagi A., Timonen J. V. I., Ras R. H. A., Sammalkorpi M., Penttilä M., Ikkala O., Linder M. B., Adv. Funct. Mater. 2024, 34, 12. [Google Scholar]
  • 349. Chen W., Chen M., Chen S., Wang S., Huang Z., Zhang L., Wu J., Peng W., Li H., Wen F., Regen. Biomater. 2025, 12, rbae138. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 350. Jin J., Li H., Chen Z., Liu Q., Chen J., Tao Z., Hong X., Ding Y., Zhou Y., Chen A., Zhang X., Lv K., Zhu L., Zhu S., Regen. Biomater. 2025, 12, rbae149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 351. Chen Z., Mo Q., Mo D., Pei X., Liang A., Cai J., Zhou B., Zheng L., Li H., Yin F., Zhao J., Regen. Biomater. 2025, 12, rbae143. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 352. Kim S. J., Kim M., Yang S. M., Park K., Hahn S. K., Adv. Healthcare Mater. 2024, 13, 2401159. [Google Scholar]
  • 353. Song W., Zhang C., Li Z., Li K., Kong Y., Du J., Kong Y., Guo X., Ju X., Zhu M., Tian Y., Huang S., Niu Z., Regen. Biomater. 2025, 12, rbaf002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 354. Yuan Z., Zhang W., Wang C., Zhang C., Hu C., Liu L., Xiang L., Yao S., Shi R., Fan D., Ren B., Luo G., Deng J., Regen. Biomater. 2025, 12, rbae134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 355. Fang Y., Han Y., Yang L., Kankala R. K., Wang S., Chen A., Fu C., Regen. Biomater. 2025, 12, rbae127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 356. Zhu H. J., Chen W., Deng R. T., Peng S. L., Zhang Z. W., Wang J., Qiao Y. Q., Zhang Y. X., Niu Y. T., Guo S. M., Zhang C. L., Cao W., Adv. Mater. 2025, 2508196. [Google Scholar]
  • 357. Cong M., Wu X., Zhu L., Gu G., Ding F., Li G., Shi H., Regen. Biomater. 2024, 11, rbae005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 358. Chen H., Ma X., Zhang M., Liu Z., Regen. Biomater. 2023, 10, rbac086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 359. Li Q., Qi G., Lutter D., Beard W., Souza C. R. S., Highland M. A., Wu W., Li P., Zhang Y., Atala A., Sun X., Biomolecules 2022, 12, 1317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 360. Serino A., Bockbrader M., Bertoni T., Colachis lv S., Solcà M., Dunlap C., Eipel K., Ganzer P., Annetta N., Sharma G., Orepic P., Friedenberg D., Sederberg P., Faivre N., Rezai A., Blanke O., Nat. Hum. Behav. 2022, 6, 565. [DOI] [PubMed] [Google Scholar]
  • 361. Shen K., Chen O., Edmunds J. L., Piech D. K., Maharbiz M. M., Nat. Biomed. Eng. 2023, 19. [DOI] [PubMed] [Google Scholar]
  • 362. Wang W., Jiang Y., Zhong D., Zhang Z., Choudhury S., Lai J., Gong H., Niu S., Yan X., Zheng Y., Shih C., Ning R., Lin Q., Li D., Kim Y., Kim J., Wang Y., Zhao C., Xu C., Ji X., Nishio Y., Lyu H., Tok J. B., Bao Z., Science 2023, 380, 6646. [DOI] [PubMed] [Google Scholar]
  • 363. Zhu W. J., Wei T., Xu Y. C., Jin Q. T., Chao Y., Lu J. Q., Xu J., Zhu J. F., Yan X. Y., Chen M. C., Chen Q., Liu Z., Nat. Commun. 2024, 15, 15. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Advanced Materials (Deerfield Beach, Fla.) are provided here courtesy of Wiley

RESOURCES