Kidney Organoids in Drug Development: Integrating Technological Advances and Standardization for Effective Implementation

ABSTRACT

Kidney organoids have emerged as promising in vitro models for studying human kidney development and nephrotoxicity. Despite their potential, limitations in maturation, reproducibility, and scalability have hindered their adoption in current drug development. Recent advances in differentiation protocols, biomaterials formulations, and enabling technologies such as bioprinting, organ‐on‐chip systems, and cell sorting are helping to overcome these challenges. However, further standardization in organoid differentiation, imaging, in silico analysis, and high‐throughput screening automation is required for practical and effective implementation and regulatory alignment. This review provides a comprehensive overview of technological advancements that enhance kidney organoid models, emphasizing the steps needed for their integration into preclinical testing. By focusing on standardization, we highlight how kidney organoids can become reliable tools for future drug development.

This review examines how emerging enabling technologies enhance the physiological relevance, scalability, and reproducibility of kidney organoids, while advanced analytical approaches support model validation and deepen mechanistic insight into nephrotoxicity. It also highlights the critical role of standardization across kidney organoid generation, characterization, and data analysis to enable their reliable integration into preclinical drug development.

1. Introduction

The kidneys play a central role in preserving physiological homeostasis, balancing water and electrolyte levels while removing metabolic waste and toxins through their functional units, the nephrons. Due to their continuous role in systemic filtration, nephrons are exposed to a broad range of pharmaceutical compounds, making them particularly susceptible to drug‐induced kidney injury (DIKI) [1]. DIKI is known to cause disruption to cell–cell interactions, transporter protein function, and vascular integrity [2]. Despite its clinical significance, the underlying mechanisms of DIKI remain poorly understood, contributing to high rates of late‐stage clinical trial failures and post‐market drug withdrawals. These failures not only impose substantial financial and resource losses for drug developers, but more crucially delay the availability of new drug therapies, which further limits treatment options for medical conditions. In many cases, nephrotoxic drugs continue to be prescribed to patients due to the lack of safer alternatives [3, 4].

A key challenge in mitigating DIKI is the lack of predictive and physiologically relevant in vitro models that can accurately recapitulate human kidney organization and function. Traditional models, such as 2D cell cultures and animal studies, fail to recapitulate the complexity and specificity of the human nephron, leading to poor translatability of preclinical findings [5], highlighting the need for more robust predictive models to be incorporated into the drug development process (DDP) [6]. This limitation has driven the development of complex in vitro models (CIVM) integrating multiple cell types with micro‐environmental cues that support cellular performance [7, 8]. Among these CIVMs, kidney organoids derived from pluripotent stem cells (PSCs) have emerged as promising in vitro models for drug toxicity screening. Their multi‐lineage cellular composition and structural organization recapitulate key features of the developing nephron, including rudimentary kidney function, making them a physiologically relevant alternative to traditional 2D cultures [9]. However, their widespread adoption in preclinical research is hindered by challenges in reproducibility, scalability, maturation, and function. Key contributors include inconsistent differentiation protocols that generate off‐target cells and batch‐to‐batch variation in culture reagents and biomaterials. Addressing these limitations has therefore become a major focus, prompting recent efforts to develop standardization strategies for CIVMs.

Recent efforts have focused on defining standardization strategies for CIVMs [10, 11]. For kidney organoids, this means harmonizing protocols and quality control measures to improve reproducibility, while also aligning their applications with regulatory expectations, including the establishment of minimum criteria for characterization, such as morphological assessment, marker expression, and functional readouts. Such efforts are being advanced through international guidelines, regulatory initiatives, and collaborative projects that foster comparability, data sharing, and technological innovation. Establishing these frameworks is critical for the successful integration of CIVMs into drug development pipelines [12]. To fully realize these frameworks, it is important to recognize that standardization must also encompass the enabling‐technologies increasingly applied in kidney organoid research (Table 1). While optimized kidney organoid differentiation protocols, and controlled culture environments improve protocol efficiency and nephrogenesis [13, 14], biomaterials and advanced manufacturing technologies enhance the reproducibility and functionality of kidney organoids for drug toxicity screening applications [15, 16]. Automation and high‐throughput (HT) platforms facilitate large‐scale organoid production, reducing manual variability. Additionally, cell sorting approaches, and cryopreservation strategies are refining organoid composition and enabling “off‐the‐shelf” availability for drug testing. Collectively, these advancements are driving the adoption of standardized CIVMs for nephrotoxicity screening.

TABLE 1.

Examples of studies reported in literature investigating nephrotoxicity of compounds.

Author	Year	Enabling‐technologies for enhancing Kidney Organoid development	Nephrotoxic compound	Endpoint readout	Reference
Ma, Sadeghian et al.	2024	Proximal tubule‐on‐chip model from hiPSC‐derived kidney organoids with enhanced expression and polarity of OAT1/3	Aristolochic acid and Cisplatin	Cytotoxicity: LDH release assay (Dojindo Laboratories, Cytotoxicity LDH Assay Kit‐WST, 343–91753). LIVE/DEAD cell viability assays	[27]
Vanslambrouck et al.	2022	An extended differentiation protocol enhanced proximal tubule maturation, and the use of bioprinted organoid sheets enabled spatial analysis showing that WNT‐signaling gradients drive nephron alignment and directional organization.	Cisplatin	IF: KIM‐1, qRT‐PCR: HAVCR1	[33]
Czernieki et al.	2018	Liquid handler used to automate cells seeding and large volume of kidney organoids generated in microwell plates.	Cisplatin	Phenotypic screen assessing phase‐contrast effects on tubular integrity, quantification of cell survival, KIM‐1 expression detected by ELISA, and IF	[45]
Garreta et al.	2019	Soft polyacrylamide hydrogels enhance and accelerate expression of genes for late‐stage nephrons and vasculature in kidney organoids.	Cisplatin	IF: KIM‐1, Caspase 3	[47]
Homan et al.	2019	Kidney organoids cultured in vitro under high fluid flow exhibit enhanced vascularization during nephrogenesis.	Doxorubicin	TEM: Podocyte foot process fusion	[39]
Bas‐Christobal et al.	2022	Microfluidic organ‐on‐chip system supports kidney organoid development. Co‐culture with endothelialized channels promotes HUVEC migration into the organoid tissue and formation of open lumen structures	None assessed	NA	[91]
Kroll et al.	2024	Perfusion of macro‐vessel connects to micro‐vasculature of kidney organoids on a chip model	Future outlook	Future outlook	[92]
Kim et al.	2022	Porcine dECM enhances endothelial cell growth	None assessed	NA	[77]
Nerger et al.	2024	Viscoelasticity of hydrogels regulates the spatial distribution of nephron segments within the encapsulated differentiating kidney organoids	Elevated extracellular calcium levels in culture medium	Ratio of Glomerulus‐to‐Tubule Nephron Segments. IF: Podocalyxin, LTL and E‐cadherin	[81]
Ruiter et al.	2022	Culturing kidney organoid on hydrogel reduces Epithelial to Mesenchymal Transition	None assessed	Cell Viability Assay: EthD1/calcein AM staining	[82]
Geuens et al.	2021	Culturing kidney organoid on hydrogel reduces Collagen IV deposition	None assessed	Cell Viability Assay: EthD1/calcein AM staining	[83]
van Sprang et al.	2024	Supramolecular UPy‐based hydrogel (mechanoresponsive, integrin‐binding, low–molecular‐weight co‐assembled network) to encapsulate organoids and enhance glomerulogenesis via mechanotransduction	None assessed	NA	[87]
Lawlor et al.	2021	Bioprinting enhances throughput and reproducibility of kidney organoid generation, and impacts patterning and nephron number	Cisplatin, Amikacin, Tobramycin, Gentamycin, Neomycin, and Streptomycin	Metabolic activity: ATP content (CellTiter‐Glo and CellTiter‐Glo 3D viability assays). RT–qPCR: HAVCR1, BAX, CASP3, NPHS1, PODXL and CUBN	[107]
Shin et al.	2024	Low‐cost, customizable pneumatic extrusion bioprinter enabling high‐throughput, reproducible kidney organoid fabrication from as few as 8,000 NPCs; precise droplet deposition; size‐tunable organoids; formation of podocytes, proximal/distal tubules, and endothelial cells	None assessed	Live and dead assay (Viability/Cytotoxicity Kit, Biotium)	[108]
Aceves et al.	2022	A perfusable 3D proximal tubule model was35 generated from epithelial cells isolated from kidney organoids through magnetic‐activated cell sorting (MACS) of LTL‐positive cells	Cisplatin and Aristolochic acid	Cytotoxicity: LDH release assay (Promega, CytoTox Non‐Radioactive Cytotoxicity Assay, G1780)	[93]
Hong et al.	2024	Microphysiological Analysis Platform (MAP) enabling kidney organoid development under biochemically defined perfusion dynamics, with consistent and accurate organogenesis. NPCs are differentiated and cryopreserved in liquid nitrogen until users are ready to seed MAP	Cisplatin and Gentamicin	IF: KIM1, PODXL, LTL, E‐cadherin with further evaluation of nephron integrity calculating percentage of segments displaying specific signs of nephrotoxicity	[90]
Formica et al.	2025	Microfluidic bioprinting used to produce human iPSCs‐derived renal organoids	Doxorubicin	qPCR used to evaluate KIM‐1 gene expression	[110]
Kim et al.	2024	UniMat platform: 3D geometrically engineered permeable membrane enabling scalable production of uniformly mature kidney organoids with enhanced nephron transcript expression, vascularization, and stability; standardized for AKI and PKD modeling	Lipopolysaccharide (LPS)	IF: KIM‐1, LTL. Used images to calculate percentage KIM‐1⁺ area.	[112]
Przepiorski et al.	2022	Magnetic stirrer–based bioreactor method for scalable kidney organoid generation; CytochromeC‐GFP reporter iPSC line enabling real‐time monitoring of mitochondrial injury and apoptosis	Hemin	IF: KIM‐1, Casp3, HMOX1, NPHS1, and oxidative stress markers (3‐NT) expression; CytoC‐GFP mitochondrial release; functional transport assays (OAT/OCT) with 6‐carboxyfluorescein and ethidium bromide uptake	[113]
Mashouf et al.	2024	Optimized vitrification (V1 protocol) enables reliable cryopreservation of kidney organoids, reducing labor demands and batch variability to support broader experimental use.	Cisplatin	IF: KIM1, LTL, CDH1, PODXL, Ki67 and γH2AX with further structural analysis and marker expression	[119]
Wiersma et al.	2022	Scalable protocol generating large nephron sheets; vascularization and functional maturation after transplantation; cryopreservation of intermediate mesoderm for reproducible large‐scale production	None assessed	NA	[118]

AKI—acute kidney injury, ATP—adenosine triphosphate, BAX—BCL2‐associated X protein, CASP3 – cysteine‐aspartic acid protease 3, CDH1 – cadherin‐1, CytoC‐GFP—cytochrome C–green fluorescent protein, dECM—decellularized extracellular matrix, ELISA—enzyme‐linked immunosorbent assay, EthD1 – ethidium homodimer‐1, GFP—green fluorescent protein, γH2AX—phosphorylated H2A histone family member X, HMOX1 – heme oxygenase‐1, HAVCR1 – hepatitis A virus cellular receptor 1, HUVEC—human umbilical vein endothelial cell, IF—immunofluorescence, Ki67 – proliferation marker Ki‐67, KIM‐1 – kidney injury molecule‐1, LDH—lactate dehydrogenase, LTL—lotus tetragonolobus lectin, MACS—magnetic‐activated cell sorting, MAP—microphysiological analysis platform, NA—not applicable, NPCs—nephron progenitor cells, NPHS1 – nephrin, OAT—organic anion transporter, OCT—organic cation transporter, PODXL—podocalyxin, PKD—polycystic kidney disease, qPCR—quantitative polymerase chain reaction, qRT‐PCR—quantitative reverse transcription polymerase chain reaction, RT–qPCR—reverse transcription quantitative polymerase chain reaction, TEM—transmission electron microscopy, UPy—ureido‐pyrimidinone.

Beyond culture standardization, the adoption of advanced analytical techniques is transforming kidney organoid‐based toxicity assessments. Novel nephrotoxicity biomarkers [17], multi‐omics profiling [18], and high‐content imaging are expanding the scope of organoid‐based drug screening [19]. Computational approaches, including deep learning algorithms and in silico modeling, are further enhancing the predictive power of these models [20]. By addressing both the standardization of culture protocols and the integration of advanced analytical technologies, kidney organoids can evolve into reproducible, scalable, and physiologically relevant models with improved accuracy for drug development. This review explores recent progress in these areas and outlines the critical steps required for their regulatory acceptance and widespread application in nephrotoxicity screening.

2. Setting the Standard: Kidney Organoid Culture and Enabling‐Technologies

Kidney organoids were first described in studies demonstrating how human pluripotent stem cells (PSCs) could be directed to nephron progenitor cells (NPCs), which self‐assemble into kidney‐like structures resembling the renal tissue of a first‐trimester human fetus [21, 22, 23, 24, 25]. The nephron, the functional unit of the kidney, is a highly complex structure composed of multiple cell types and specialized segments, each performing distinct functions. The nephron arises from two cell populations; the metanephric mesenchyme (MM), which gives rise to kidney stroma, glomerulus, and tubules, and ureteric bud (UB), which develops into the collecting duct system [26]. Early kidney organoid protocols successfully established MM‐ and UB‐derived NPCs from PSCs [22, 24], enabling further differentiation into kidney organoids that recapitulate key stages of nephron development. These organoids exhibit several aspects of nephron functionality, including albumin uptake [2], and expression of key transporter proteins (OAT1/3 and OCT2) [27, 28], which are often inadequately expressed in traditional in vitro models, such as RPTEC/TERT1 cell lines [29]. Several comprehensive reviews have already compared the major kidney organoid differentiation protocols, outlining resulting nephron cell populations and their suitability for different applications [9, 30, 31, 32]. Recent refinements in differentiation protocols have led to the development of kidney organoids with elongated proximal tubule segments [33, 34], branching morphogenesis [35], and reduced off‐target chondrocytes [36]. However, kidney organoids still remain highly heterogeneous, with varying degrees of cellular composition and maturation, depending on the PSC source [37], differentiation protocols, and culture conditions [39]. Also, the role of bystander cells, which provide critical paracrine support and contribute to overall organoid resilience, remains poorly understood.

Another significant challenge in kidney organoid development is the lack of functional connectivity between nephron segments. In native kidneys, proximal tubules, loop of Henle, distal tubules, and collecting ducts function as an integrated system, yet in kidney organoids, these structures often remain disconnected or spatially disorganized, leading to suboptimal fluid transport and metabolic interactions affecting their ability to replicate glomerular filtration, tubular reabsorption, and secretion, which are crucial for drug screening applications [40]. Co‐culture systems with human PSC‐derived MM and UB populations have successfully integrated the collecting system through fusion of distal nephron to ureteric bud, resulting in a more structurally and functionally advanced kidney organoids compared to previous methodologies [41]. Addressing functional inter‐segmental connectivity will be essential for the development of kidney models that accurately recapitulate human physiology.

Adding to this complexity, nephron maturation and function rely on an intricate vascular network, without which kidney organoids remain immature [42]. There is still limited knowledge about signaling cues between the vasculature and developing nephrons. A recent study found Netrin 1 expression in Foxd1+ stromal progenitors is essential for the developing mouse kidney nephrogenesis [43]. Some approaches, such as the modulation of WNT signaling [44], and the addition of vascular‐inducing factors have improved the differentiation of endothelial cell population within kidney organoids [45]. Implantation of kidney organoids under the renal capsule in mice [44, 46], or within the highly vascularized chorioallantoic membrane [47], has been shown to successfully induce a more mature vasculature in the organoids. While these in vivo approaches provide essential vascular cues, a fully in vitro approach would better align with evolving FDA and EU guidance prioritizing non‐animal models and phasing down animal testing.

2.1. Collaborative Efforts and Key Initiatives for Implementing Standardization of CIVMs

Standardization refers to the development and adoption of consistent protocols, criteria, and quality measures to ensure reproducibility, reliability, and interoperability across studies and platforms. Regulatory and scientific organizations play a crucial role in establishing guidelines for in vitro models (Table 2), ensuring their reliability and alignment with drug development standards. Defining and implementing standards requires collaboration among diverse stakeholders such as regulatory bodies, industry, and academia. Efforts led by regulatory agencies, such as the European Medicines Agency (EMA), the US Food and Drug Administration (FDA), and the Pharmaceutical and Medical Device Agency (PMDA) are crucial in this regard, involving joint workshops, shared guidance documents, and collaborative initiatives that aim to ensure consistency and robustness of CIVMs [21]. The FDA promotes advanced in vitro models through the FDA Modernization Act 2.0, reducing reliance on animal testing [11]. Similarly, the EU efforts align with the 3Rs principle (Replacement, Reduction, Refinement of animal models) highlighting the shift toward the use of new approach methodologies (NAMs) in the DDP [48], and supported by organizations such as European Organ‐on‐Chip Society (EUROoCS), which foster standardization and validation by building shared frameworks, benchmarking practices, and community‐wide engagement [49]. Most recently, the UK announced a roadmap to phase out animal testing by 2030 [50]. At the international level, the IQ microphysiological systems affiliate (IQ MPS) plays a similar role, advancing the qualification and adoption of microphysiological systems through cross‐sector collaboration [11]. These collaborative projects play a crucial role in driving consensus by establishing shared terminology, databases, quality control measures, and benchmarking metrics to support reproducibility and regulatory uptake [51]. Several international organizations have established guidelines on standardization of in vitro models for various sectors, and continuously release detailed documentation outlining best practices, validation requirements, and regulatory considerations. For example, the Organization for Economic Co‐operation and Development (OECD) published guidelines such as the Good in vitro Method Practices (GIVIMP) framework, which provides recommendations for ensuring the reliability, reproducibility, and relevance of in vitro models in regulatory applications [52]. In parallel with such guidance, innovation programs, such as the National Center for Advancing Translational Sciences (US) [53], Innovative Health Initiative (EU) [54], and NXT GEN Hightech (NL) [55], support biomedical innovation by advancing the reproducibility, scalability, and automation of advanced in vitro models. They seek to bridge the gap between academic research and industrial application by integrating technological expertise (e.g., precision engineering, robotics, and AI) with biological systems, while addressing key challenges such as the need for multidisciplinary supply chains that can enable standardization and commercialization.

TABLE 2.

A list of organizations that foster international collaboration, develop standards, and promote innovation in CIVMs for drug development.

Organization	Abbreviation	Purpose	Reference
Organization for Economic Co‐operation and Development	OECD	Promote policies that enhance global economic and social well‐being, offering a platform for governments to collaborate on key issues.	[164]
The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use	ICH	Facilitate cooperation between regulatory authorities and the pharmaceutical industry to harmonize drug registration guidelines.	[165]
International Organization for Standardization	ISO	Develop global standards to ensure quality, safety, and efficiency across industries, supporting trade and innovation.	[166]
Predictive Safety Testing Consortium	PSTC	Collaboration between pharmaceutical companies focused on identifying and validating safety biomarkers to improve drug safety.	[167]
The European Committee for Standardization	CEN and CENELEC	Establish voluntary European standards to facilitate trade, safety, and innovation. They align with international organizations like ISO and IEC to streamline standard development and prevent duplication of efforts.	[168]
Joint Research Centre—European Commission	JRC	European Commission's science and knowledge service. It provides independent scientific advice and support to EU policy, ensuring that policies are based on sound scientific evidence.	[169]
American Type Culture Collection	ATCC	A non‐profit that supplies authenticated biological materials, such as cell lines and microorganisms, to support scientific research.	[170]
American Society for Testing and Materials	ASTM	Develop voluntary consensus standards across industries to enhance quality, safety, and trade. It collaborates with organizations like CEN to promote global cooperation.	[171]
IQ Microphysiological Systems Affiliate	IQMSA	Advance the development, qualification, and adoption of microphysiological systems to enhance drug discovery and regulatory science through cross‐sector collaboration.	[172]
Critical Path Institute	C‐Path	Accelerate the development of innovative tools and approaches to improve drug development and regulatory decision‐making through public‐private partnerships.	[173]

In the context of kidney organoids, an increasing number of international projects are advancing CIVMs for nephrotoxicity screening through the development and application of kidney organoid‐based systems. These projects encompass diverse initiatives, including stem cell repositories, kidney organoid derivation, development of renal microphysiological systems, and bioprinted organoid‐on‐chip platforms (Table 3). Collectively, they aim to improve reproducibility, enable cross‐study comparisons, strengthen benchmarking, and accelerate the regulatory acceptance of human‐relevant renal systems in drug development. The International Society of Nephrology recently published consensus guidance (TRANSFORM) for preclinical animal studies, which notably recommends considering kidney organoids and organ‐on‐chip (OoC) models as alternative systems to reduce or replace animal experiments, reflecting their growing regulatory relevance in drug development [56]. Establishing kidney organoids as reliable CIVMs for drug development not only requires high‐level regulatory alignment but also standardized practices at the bench level [57]. Despite growing international efforts to harmonize guidelines, a major barrier remains with the biological variability introduced during cell sourcing and differentiation. This variability can significantly affect organoid consistency, function, and ultimately, their predictive value in nephrotoxicity screening. Therefore, addressing this challenge requires the establishment of robust and reproducible protocols using fully characterized cell lines and defined reagents, alongside enabling‐technologies that support reproducibility, such as automation, cell sorting, and cryopreserved biobanks (Figure 1). Furthermore, these enabling technologies must also be optimized and standardized in parallel to ensure that kidney organoids meet the robustness, scalability, and reliability standards required for pharmaceutical development pipelines and translational applications.

TABLE 3.

A list of international projects focused on establishing standards and advancing the use of kidney organoids in drug development.

Project	Program	Purpose	Reference
Stem cells for biological assays for novel drugs and predictive toxicology (STEMBANCC)	EU IHI	Generated large hiPSC repositories, enabling kidney organoid derivation for disease modeling and drug safety screening.	[174, 175]
European Union Toxicology Project (EU‐ToxRisk)	EU Horizon 2020	Advanced kidney organoid models for toxicology, supporting transition away from animal testing.	[175]
Tissue Chip in Space	NCATS	Developed kidney‐on‐chip systems; some projects incorporate kidney organoids for nephrotoxicity studies.	[176]
Bioprinting on‐chip microphysiological models of humanized kidney tubulointerstitium (BIRDIE)	EU Horizon 2020	Integrates bioprinting, iPSC‐derived kidney organoids, and microfluidics to model the renal tubulointerstitium for nephrotoxicity and infection studies.	[177]
Human Cell Atlas—Kidney Biological Network (HCA)	grass‐roots led, global and open scientific project	Provides single‐cell maps of human kidneys used to benchmark and validate kidney organoids.	[61, 178]

FIGURE 1.

Incorporation of enabling technologies to enhance kidney organoid development, scalability, and reproducibility. Biomaterials support nephrogenesis and vascularization, and can be integrated into bioinks for bioprinting, improving both reproducibility and automation of kidney organoid culture. Bioreactors facilitate large‐scale organoid production, while cell sorting enables the selection of specific cell types, refining organoid composition. Organ‐on‐chip systems provide a micro‐physiological culture environment that enhances features of model functionality and supports high‐throughput imaging compatibility. Cryopreservation reduces the need for continuous culture and provides an off‐the‐shelf availability option. In this review, bioprinting and organ‐on‐a‐chip platforms are highlighted in the context of how they contribute to improving reproducibility and scalability, as well as their alignment with emerging standardization frameworks. GFs—growth factors; SMs—small molecules. Created in BioRender. Kearney, H. (2025) https://Bioender.com/sswpo7l.

2.2. Cell Sourcing and Standardized Protocols for Kidney Organoid Culture

The reproducibility of kidney organoid models relies on the development of standardized protocols guided by developmental biology principles, which include details on cell sourcing and culture reagents. The International Society for Stem Cell Research (ISSCR) has proposed recommendations to enhance standards in stem cell research [58]. Variability among the differential potential of Induced pluripotent stem cell (iPSC) lines raises concerns regarding experimental reproducibility. Accurate pluripotency characterization and genomic screening for karyotypic stability assessment ensure iPSC lines are fit‐for‐use for differentiation applications [59]. Guidelines have been proposed for generating basic kidney organoids for nephrotoxicity screens [10], providing an initial framework for improving protocol robustness; however further efforts are needed for thorough characterization [60]. Published single‐cell datasets of kidney organoids generated using different iPSC lines and optimized protocols can be used for further comparison and characterization [38, 61]. These datasets now serve as references for assessing the robustness of differentiation outcomes and enhancing reproducibility through cross‐study comparison [62]. While it would also be beneficial to establish a definite number of donor lines needed to ensure protocol robustness, current guidelines emphasize minimum reporting standards and thorough documentation of cell sources and quality controls, rather than prescribing a fixed number of cell lines, thereby maintaining flexibility while supporting reproducibility [49, 58].

We must also consider heterogeneity in the general human population by introducing ethnic, sex‐, and age‐specific donor lines for overall protocol validation [63]. iPSCs exhibit variations in differentiation capacity, which may influence organoid development and drug response. This variation can be attributed to genetic and epigenetic factors, highlighting the need for comprehensive studies to better understand these influences. Epigenetic analyses may provide insights into how these factors shape cellular behavior and response to treatments. By incorporating diverse donor lines, researchers can study differences in drug metabolism, drug targets, and drug interactions among individuals within a diverse population [64]. Understanding these intrinsic differences will support the transition to more personalized therapeutic approaches. With this in mind, it is also important to highlight the ethical and regulatory considerations associated with organoid research. Donor consent, data privacy, and the management of genomic information represent critical concerns, particularly as patient‐derived organoid (PDO) biobanks continue to expand [65, 66, 67].

In parallel, regulatory guidance specific to the use of kidney organoids or kidney organoid‐derived cells in CIVMs remains limited, underscoring the need for clear criteria around validation, reproducibility, and fitness‐for‐use of tissue‐specific models in drug development applications. Equally important is the need to define which types of in vitro models are appropriate for specific experimental objectives. While full representation of all nephron structures may be necessary for some studies, simplified models, such as adult stem cell‐derived kidney tubuloids, could suffice for certain applications [68, 69]. In contrast, when greater functionality is needed, complex assembloid cultures incorporating different nephron progenitor populations or kidney organoid‐derived cell populations may be employed [70, 71].

2.3. Defined Biomaterials, Cell Sorting, and Dynamic Culture Platforms for Controlled Signaling in Kidney Organoid Development

Kidney organoid differentiation protocols frequently include culture steps using basement membrane extracts (BME) from Engelbreth‐Holm‐Swarm mouse sarcomas [39, 72, 73]. However, these BME extracts exhibit undefined composition and batch variability, which can alter kidney lineage commitment, contribute to off‐target populations, and hinder mechanistic interpretation [74]. These drawbacks in kidney organoid culture, coupled with the ethical implications and standardization difficulties, create an ever‐growing need for suitable biomaterial alternatives [75]. We can categorize biomaterials into three major classes: natural, synthetic, and hybrid. Each class presents distinct biochemical and mechanical features that can influence nephrogenesis, glomerular patterning, stromal expansion, and overall reproducibility.

Natural biomaterials, like BME, offer rich biochemical environments but lack definition. Examples of other natural‐based biomaterials being investigated are decellularized extra‐cellular matrix (dECM), derived from primary kidney tissue [76]. dECM‐based biomaterials promote kidney organoid maturation and vascularization, as they contain intrinsic biochemical signaling cues for cells [77, 78]. Furthermore, these can also offer suitable mechanical cues to support vascular network integration in kidney organoids [47]. While primary kidney tissue and animal‐derived sources, such as gelatin, raise ethical concerns, plant‐based natural biomaterials like alginate circumvent these issues, making them attractive cytocompatible alternatives.

Hybrid biomaterials, often derivatives of natural‐based materials including alginate–norbornene, gelatin‐methacrylate (GelMA), and functionalized dECM, combine chemically defined crosslinking chemistry with natural‐derived material bioactivity and cytocompatibility [79, 80]. These systems can support nephron maturation and reduce off‐target tissue formation. Culturing kidney organoids on alginate‐norbornene with a stiffness similar to native tissue has been shown to enhance nephrogenesis [81], prevent kidney organoids' degeneration [82], and reduce abnormal collagen deposition [83]. Furthermore, alginate could be further functionalized with synthetic peptides [84], which have been shown to reduce the presence of off‐target cells within the kidney organoids in studies using a pure synthetic peptide‐based hydrogel [85]. While hybrid materials offer greater consistency than unmodified alginate or kidney dECM, their natural components still introduce a degree of variability. For instance, alginate‐norbornene is still not fully chemically defined and may differ with varying batches of alginate, and GelMA differs widely in the degree of methacrylation between suppliers. This highlights the need for rigorous material characterization and reporting within hybrid biomaterials [86].

Synthetic biomaterials, such as supramolecular ureido‐pyrimidinone (UPy) hydrogels, provide highly controlled systems for modulating the mechanical and biochemical environment of kidney organoids [87]. Their defined chemistry and tunable stiffness, viscoelasticity, and adhesion ligand density enable precise control of mechanotransduction, improving nephron elongation, limiting stromal expansion, and enhancing podocyte maturation. UPy‐based hydrogels, particularly when functionalized with integrin‐binding motifs, have been shown to enhance glomerulogenesis and refine nephron segmentation. This example of a synthetic biomaterial demonstrates the capacity of these matrices to guide specific developmental processes when appropriately designed and developed, considering the aimed biological outcome.

The adoption of defined biomaterials is of utmost importance for the future adoption of organoids for DIKI screening, where reproducibility is paramount for consistency of experimental outcomes. Standardization is also required for the development of biomaterials. Ensuring consistent reproducibility requires the implementation of Good Manufacturing Practice (GMP) guidelines, which set the minimum standards for manufacturing processes, including in vitro model development. Within GMP, standard operating procedures (SOPs) for material preparation, labware usage, and experimental setup, along with detailed documentation of material properties should be considered for quality control (QC) assessment [51]. In this context, synthetic biomaterials are generally the most amenable to standardization due to their defined composition and predictable behavior, aligning well with GMP and QC expectations. Natural biomaterials, while biologically rich, present substantial challenges for reproducibility and regulatory qualification due to inherent batch variability. Hybrid materials sit between these extremes: their synthetic chemistry improves process control, but natural components still require strict analytical characterization. Therefore, biomaterial choice must balance biological complexity with manufacturability, traceability, and regulatory readiness. Furthermore, when designing these biomaterials, it is essential to consider not only the combination with organoids but also their processability with enabling‐technologies such as bioprinting [86]. While chemically defined biomaterials may be easier to standardize, their performance is still limited compared to natural‐based alternatives that present a diverse array of biochemical binding sites [74]. Advancements in biomaterial research will contribute to the standardization and functionality of kidney organoids, although additional developments are still needed to replicate the complexity of native kidney tissue.

In addition to their role in static culture systems, biomaterials are increasingly incorporated into OoC platforms, where they serve as extra‐cellular matrix‐mimetic substrates or structural scaffolds to guide tissue organization. The choice of biomaterial also heavily influences compatibility with dynamic culture systems, where mechanical stability, optical clarity, and predictable degradation kinetics are essential for microfluidic integration and real‐time imaging. OoC systems offer a dynamic culture environment by incorporating controlled fluid flow and biochemical gradients, which can influence organoid differentiation and function. OoCs are among the most highly endorsed next‐generation CIVM platforms for organoid culture [88]. These OoCs are designed with a small, enclosed chamber containing cells, tissues, or other biomaterials that mimic the natural extracellular matrix. The enclosed chamber is connected to a microfluidic or peristaltic pump to create a perfusable culture system, providing an ideal platform for dynamic flow culture conditions and for drug administration within the circulation medium. These OoCs have an added benefit that they can be designed to be compatible with analysis instruments, such as microscopes. The cellular samples contained in the inner chamber can be removed for post‐culture analysis, making them versatile tools for drug development [89, 90].

Customized OoC platforms have been developed to allow in vitro culture of kidney organoids by incorporating controlled fluid flow and shear stress, which promotes vascularization without the use of animal implantation [39, 91, 92]. Other advancements in OoC design include the development of proximal tubule epithelial cell‐on‐chip models with structural resemblance to proximal tubule using magnetic‐activated cell sorting (MACS) sorted, kidney organoid‐derived cells. These models showed significant upregulation of solute carrier transporters such as OCT2 and OAT1/3, enhancing drug uptake compared to models based on immortalized cell lines [27, 93]. Another study demonstrated how OoCs can be integrated within a well plate‐like configuration with optical oxygen sensors enabling HT nephrotoxicity screening in a humanized microfluidic co‐culture model [94]. Furthermore, OoCs with multi‐organ compartments have also been developed to couple different organs, such as kidney and cardiac [95], or kidney and liver [96], under dynamic conditions to investigate interactions between organ‐like compartments. Such OoCs with multiple organ‐like compartments can be relevant to investigating co‐morbidities and multi‐organ toxicity studies.

A specific push for standardization has emerged for OoC technology manufacturing. Regulatory agencies and research initiatives are working to establish a framework for reproducibility and validation with minimum reporting requirements for cells and biomaterials, in addition to consistency in device fabrication protocols, sterilization procedures, and standardizing test methods for chip performance [97, 98]. The recent Focus Group Organ‐on‐Chip (FGOoC) Standardization Roadmap (2024) reinforces these priorities, highlighting harmonized terminology, reporting standards, material qualification, and regulatory integration as urgent areas for action [49]. Collectively, these efforts aim to create best practices that ensure compatibility across research and industrial settings for the widespread adoption of OoCs in the DDP [90, 99, 100].

While engineering the external micro‐environment is critical, controlling the internal cellular composition of kidney organoids is equally important for ensuring reproducibility and functional relevance. While efforts to improve extrinsic cues remain essential, an equally important path lies in refining the intrinsic cellular composition of kidney organoids by better controlling the types and proportions of constituent cell populations, particularly important given the persistent issue of off‐target cell populations in PSC‐derived kidney organoids [37]. To address this issue, advanced cell sorting techniques, such as MACS, [27, 93] and fluorescence‐activated cell sorting (FACS) [72], are being employed to isolate and purify desired cell types. However, there are certain limitations with these techniques when using antibodies with limited specificity. One way to overcome this limitation would be to develop highly specific reporter lines using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology to enable precise tracking of cell populations during organoid differentiation [101, 102]. With the application of these techniques, researchers can generate more defined cellular constructs by dissociating organoids during differentiation when nephronNPCs emerge, sorting cells and reaggregating an optimal number, and adding other relevant cell types [70, 103], resulting in improved cellular composition and functionality of resulting CIVMs.

A key conceptual distinction in developing kidney organoid–based platforms lies in the difference between bottom‐up and top‐down engineering strategies [104, 105]. Bottom‐up approaches focus on controlling the microenvironment through defined reagents and biomaterials to guide self‐organization and improve maturation (Figure 2a) [87]. In contrast, top‐down approaches impose structure by arranging predefined cellular components, such as organoid‐derived cells, in tubular or compartmentalized architectures (Figure 2b) [93]. Each pathway has distinct implications for reproducibility and standardization. While bottom‐up methods rely on well‐defined materials and culture parameters, the top‐down workflows require standardization of cell‐sorting and device fabrication parameters [106]. Recognizing these complementary approaches provides a clearer framework for aligning emerging technologies with reproducibility and standardization goals.

FIGURE 2.

Bottom‐up and top‐down engineering approaches for kidney organoids. (a) Bottom‐up approach showing kidney organoids encapsulated in supramolecular ureido‐pyrimidinone (UPy) hydrogels. Adapted from Van Sprang et al., 2024 [87], distributed under the Creative Commons CC BY license. (b) Top‐down approach using MACS‐sorted LTL⁺ kidney‐organoid‐derived cells seeded into a 3D proximal tubule‐on‐chip model, demonstrating enhanced drug uptake. Adapted from Aceves et al., 2022 [93], distributed under the Creative Commons Attribution 4.0 International License.

2.4. Strategies to Improve Scalability, Reproducibility, and off‐the‐Shelf Availability of Kidney Organoids

Manual culture methods for kidney organoids require highly skilled personnel and are usually time‐consuming, limiting reproducibility and scalability. Automation can ease these challenges by introducing process consistency, reducing labor costs, and ensuring product quality. Bioprinting techniques offer a fast, automated, and reproducible method to generate a large volume of uniform kidney organoids [107, 108]. Frequently, bioprinting approaches exploit the combination of cells with biomaterials, termed bioinks, to enable more precise fabrication and structural support for cellular constructs [109, 110]. Alongside bioprinting, automated liquid handlers and bioreactors streamline organoid generation while reducing contamination risks [111]. Additionally, culturing iPSCs in microwell arrays [35, 112], or stirring bioreactors enables large‐scale expansion without requiring a transition from 2D to 3D culture formats [25, 113]. Together, these scalable platforms reduce operator‐dependent variability and streamline workflows, thereby improving the overall reproducibility of kidney organoid production (Figure 3).

FIGURE 3.

Enabling technologies to enhance the scalability and reproducibility of kidney organoids. (a) A bioreactor‐based method for generating kidney organoids from pluripotent stem cells, in which ∼1 mL of medium supports ∼50 organoids. This limits a 6‐well plate to ∼900 organoids (3 mL per well), while a 125‐mL spinner flask enables scaling up to 6,250 organoids. Graphical abstract used with permission from Przepiorski et al., 2018 [25], (Creative Commons CC BY‐NC‐ND license). (b) Microfluidic bioprinting as a platform for producing hiPSC‐derived renal organoids. Adapted from Formica et al., 2025 [110], (Creative Commons Attribution 4.0 license). (c) Scalable production of uniform and mature organoids using a 3D geometrically engineered permeable membrane system. Figure from Kim et al., 2024 [112], (Creative Commons CC BY‐NC‐ND license https://creativecommons.org/licenses/by‐nc‐nd/4.0/). (d) 3D bioprinting of human iPSC‐derived kidney organoids using a low‐cost, high‐throughput customizable bioprinting system capable of dispensing precise, low‐volume droplets with high reproducibility. Figure adapted with permission from Shin et al., 2024 [108], (Creative Commons CC BY‐NC‐ND license).

Beyond process efficiency, bioprinting also offers potential solutions to biological limitations inherent in current organoid systems. The random organization of kidney organoids is also a significant limitation, as they fail to replicate the highly organized arrangement of nephrons and integrated vasculature, limiting their structural relevance and hence functionality. This disorganization also impacts reproducibility and access to the apical side of tubules, where the filtrate flows through, and reabsorption occurs. To address these challenges, researchers are utilizing 3D printing of tubular structures seeded with kidney organoid‐derived cells, with improved apical‐basolateral cellular organization [93, 114]. Among the various bioprinting approaches, co‐axial bioprinting has emerged as a promising technique to create hollow tubular structures that mimic native nephron architecture [115, 116, 117]. Regulatory agencies require a defined range of operating conditions that ensure product quality and consistency [86]. Recent round‐robin tests have highlighted key challenges in bioprinting standardization, emphasizing the need for harmonized protocols [51].

While scalable production platforms address key manufacturing challenges, the prolonged culture times associated with kidney organoid differentiation remain another significant obstacle. To address this, researchers are developing cryopreservation protocols for both nephron progenitor cells (NPCs) and fully differentiated kidney organoids [118, 119, 120, 121]. The biobanking of such cells should follow established regulatory requirements to ensure quality management, traceability, and compliance for preclinical and translational applications [122], thereby enabling the generation of an “off‐the‐shelf” cell source with improved reproducibility for drug screening.

2.5. Strengthening Reproducibility Through Standardization: Promise and Pitfalls

Reproducibility in kidney organoid research is influenced by multiple interconnected factors, including variability in pluripotent stem cell source and quality, differences in differentiation protocols, batch‐to‐batch inconsistency of biomaterials, operator‐dependent handling steps, and heterogeneity in culture environments and readouts. Standardization efforts such as ISSCR guidance on cell line characterization, GMP principles for reagent traceability, OECD GIVIMP recommendations for SOPs and assay qualification, and emerging guidelines target distinct aspects of kidney organoid–specific reproducibility challenges (Table 4). While these initiatives collectively help reduce technical, biological, and protocol‐driven variability, it is equally important to acknowledge the potential drawbacks of over‐standardization. As highlighted in recent reports [49, 123], overly prescriptive standards introduced too early can limit adaptability across diverse experimental contexts, constrain methodological innovation, and risk locking the field into suboptimal practices. Achieving robust standardization, therefore requires a balanced approach that establishes essential quality and reporting criteria while maintaining sufficient flexibility to accommodate advancing technologies and evolving scientific questions.

TABLE 4.

Summary of key existing and proposed guidelines relevant to standardization of kidney organoid research.

Guideline / Organization	Scope	Key Requirements / Recommendations	Relevance to Kidney Organoid Standardization	Ref
ISSCR Standards for Human Stem Cell Use	Stem cell derivation, characterization, culture quality, genetic stability	Pluripotency validation Genomic integrity testing Documentation of cell line provenance Minimum reporting standards	Ensures consistent PSC sourcing, quality control, genetic stability, and documentation, critical for reducing variability across organoid studies.	[58]
OECD Good In Vitro Method Practices	Quality management of in vitro models for regulatory use	Standard operating procedures (SOPs) Reagent traceability Operator training Assay qualification and QC Data integrity	Provides a foundational framework for reproducibility and regulatory readiness of organoid‐based assays.	[52]
GMP Guidelines	Manufacturing standards for cell‐based products and reagents	Defined materials and batch traceability Process control Environmental monitoring Documentation and validation steps	Encourages use of defined, traceable reagents and consistent workflows for organoid generation, especially relevant for future translational applications.	[179, 180, 181]
Guidelines for Manufacturing and Application of Kidney Organoids	Kidney organoid generation and nephrotoxicity screening	Minimum reporting standards Characterization markers Recommended culture conditions Baseline functional assays	Provides the first kidney‐specific benchmark for organoid differentiation and quality assessment, supporting cross‐study comparability.	[10]
Organ‐on‐Chip Standardization Roadmap	Manufacturing, materials, reporting standards for OoC platforms	Chip material characterization Perfusion parameters QC metrics Inter‐lab validation practices	Relevant for integration of organoids with microphysiological systems, promoting interoperability and regulatory confidence.	[49]
Biomaterials Standardization Principles	Standards for engineered biomaterials used in biomedical applications	Mechanical/chemical specification Batch‐to‐batch consistency Documentation of synthesis Sterility and endotoxin QC	Aligns biomaterial use in kidney organoid culture and bioprinting with reproducibility and regulatory expectations.	[182]
FDA‐EMEA / Predictive Safety Testing Consortium (PSTC) Biomarker Qualification Dialogue	Qualification of renal safety biomarkers for non‐clinical & clinical drug‐development	Defined biomarkers for renal injury (e.g., KIM‐1, cystatin C, clusterin) Framework for evidentiary standards for biomarker performance: sensitivity, specificity, context of use, validation Submission of a large dataset from non‐clinical toxicology studies to regulatory agencies	Helps set performance and reporting criteria for nephrotoxicity read‐outs in kidney in vitro models, underscoring the regulatory relevance of incorporating biomarkers (via organoids) that align with qualified biomarkers in drug screening.	[124]
OECD Adverse Outcome Pathway (AOP) Framework	Mechanistic, pathway‐based framework linking molecular initiating events (MIEs) to organ‐level toxicity outcomes	Identification of molecular initiating events Definition of key events (KEs) and key event relationships (KERs) Structured evidence evaluation Use of AOPs for assay development, validation, and regulatory decision‐making	Positions the kidney organoids within mechanistic, regulatory‐accepted frameworks for nephrotoxicity. Enables mapping organoid readouts (e.g., injury markers, transcriptomic signatures, functional decline) to define key events in renal AOPs, improving regulatory relevance, standardization, and fit‐for‐purpose validation of organoid‐based assays.	[159, 160, 183]

3. Enhancing Interpretation: Complementary Technologies for Extrapolating Data From Kidney Organoids in Nephrotoxicity Screening

Kidney organoids offer a promising platform for nephrotoxicity screening, given their ability to recapitulate key structural and functional features of the human kidney. However, their complexity, heterogeneity, and 3D architecture present challenges in data acquisition, interpretation, and reproducibility. To overcome these hurdles, researchers are employing complementary technologies to enhance the resolution, accuracy, and predictive power of nephrotoxicity assessments.

This section explores the integration of novel nephrotoxicity biomarkers, bioengineered reporter lines, high‐resolution imaging techniques, deep‐learning‐based image analysis, multi‐omics strategies, and in silico modeling (Figure 4). By combining these approaches, researchers aim to refine organoid‐based toxicity readouts, improve cross‐study comparability, and advance their utility as standardized preclinical models for drug safety testing.

FIGURE 4.

Emerging technologies that advance kidney organoid data extrapolation and interpretation for nephrotoxicity screening in the drug development process. Schematic overview of five complementary technology domains: novel translational biomarkers (e.g. KIM‐1, NGAL, kidney‐enriched microRNAs) measured in organoid supernatants or lysates to quantify tubular injury; bioengineering tools (CRISPR/Cas9, PiggyBac, reporter cell lines) enabling lineage tracing, pathway‐specific reporters and targeted manipulation of nephron cell populations; advanced microscopy (confocal, light‐sheet and high‐content imaging) supporting 3D morphometric analysis and automated quantification of structural and injury phenotypes; multi‐omics platforms (transcriptomics, proteomics, metabolomics) providing systems‐level signatures of nephrotoxic mechanisms; and in silico and computational models that integrate organoid‐derived data with pharmacokinetic information for in vitro–in vivo extrapolation and prediction of human nephrotoxicity. Created in BioRender. Kearney, H. (2025) https://BioRender.com/w6qzaom.

3.1. Novel Nephrotoxicity Biomarker Validation

In recent years, there has been an increased effort to identify and validate novel biomarkers for nephrotoxicity in clinical nephrology, most notably KIM‐1, NGAL, and microRNAs [124, 125, 126, 127]. Researchers can leverage these emerging biomarkers to improve accuracy in toxicity readouts from kidney organoids [128]. Several groups have demonstrated that exposing kidney organoids to drugs known to be nephrotoxic results in expression of these novel kidney injury markers [129]. For example, cisplatin induces DIKI biomarker expression, DNA damage, and cell death in kidney organoids [128, 130]. Furthermore, with the induction of kidney injury markers, researchers have gone one step further by studying repair mechanisms in PSCs‐derived kidney organoids, showing their usefulness not only as toxicity models but also as disease models for identification of target pathways for treatment of DIKI [131]

3.2. Bioengineering Reporter Cell Lines and Disease Models

The use of single, double, and triple fluorescent reporter iPSC lines has proven instrumental in facilitating the isolation of specific cell types from kidney organoids post‐differentiation, while also serving as a dynamic monitoring tool of their maturation [35, 41, 132]. This initial step has significantly contributed to refining differentiation and maturation protocols, ultimately improving reproducibility across experiments.

Building upon this approach, fluorescent tags linked to injury‐specific markers can be incorporated as biosensors to enable real‐time tracking of nephrotoxicity‐related cellular stress responses. This advancement allows for early detection of injury pathways, enhancing the precision of kidney organoid‐based drug screening and toxicity assays. These reporter cell lines enable dynamic assessment of key toxicity markers, such as oxidative stress [133], cellular metabolism [134], mitochondrial dysfunction, and early apoptotic events [113], allowing for a more nuanced understanding of DIKI. In combination with high content imaging platforms, these bioengineered fluorescent reporter iPSC‐derived kidney organoid models can provide real‐time, qualitative data, improving sensitivity and specificity of toxicity readouts. In addition, the development of multi‐parametric reporter cell lines, capable of simultaneously tracking multiple cellular stress pathways and facilitating cell population purification through sorting techniques, holds promise for increasing the predictive accuracy during preclinical drug testing [135].

Future advancements in CRISPR‐based gene editing could further refine these systems by enabling precise control over reporter expression [136], and facilitating the generation of accurate disease models for studying nephrotoxicity in populations with hereditary diseases [77, 102]. Recent genome‐wide CRISPR screening efforts in human kidney organoids have further uncovered key developmental and disease‐related regulators of nephrogenesis, offering a powerful framework to identify genetic determinants of renal development and pathology [121]. Applying these approaches to organoids derived from genetically engineered or patient‐specific iPSCs offers a route to model pre‐existing renal disease states, which is highly relevant given that patients with chronic kidney disease, diabetes, or congenital nephron deficits exhibit increased susceptibility to DIKI [137]. By creating bio‐engineered disease models with patients' genetic backgrounds, researchers can directly assess how underlying pathology alters injury trajectories and drug responses. This offers a more clinically relevant platform for evaluating treatment safety in vulnerable populations.

3.3. Advancements in Imaging Techniques and Computational Image Analysis

Advancements in microscopy have significantly enhanced the ability to extract detailed, real‐time qualitative data from kidney organoids, enabling more accurate and dynamic assessments of their development and function. Techniques such as fluorescent live‐cell, confocal, multiphoton, or light‐sheet microscopy allow for high‐resolution, real‐time visualization of cellular interactions and overall structural organization [138]. Similarly to the other techniques, standardization of microscope instruments and subsequent data analysis needs to be considered. ISO documentation provides comparable specifications from different microscope manufacturers, which allows users to compare and monitor the imaging performance of their confocal microscopes [73]. Furthermore, calibration of instruments with classical reference standards, such as wavelength and spectral responsivity, ensures equipment produces uniform readouts [139, 140].

Additionally, the integration of advanced microscopes with robotics and quantitative analysis tools facilitates HT application, enhancing the utility of organoid‐based models in the early stages of the DDP [19, 45, 141]. However, with increased output and generation of large 3D image data sets bring their own challenges for data analysis. To this end, deep learning networks play a pivotal role in enhancing the accuracy and throughput of high‐content screening platforms of organoids by enabling automated analysis of complex patterns from large‐scale image‐based datasets [142, 143]. Neural networks are being trained to evaluate kidney organoid maturity [144], as well as nephrotoxicity effects by capturing changes in cell morphology and nucleus texture along with mRNA levels of kidney injury markers [129]. These innovative software solutions provide valuable quantitative insights into morphological features and protein expression, which can be used to evaluate kidney organoids maturation and nephrotoxicity following drug exposure. Other multiphysics simulation software, such as COMSOL, allows researchers to calculate functional processes such as fluid flow in vascularized kidney organoids [39].

3.4. Multi‐Omics and Integration of Deep Learning Strategies

Transcriptomics is playing a crucial role in improving kidney organoid protocols by providing in‐depth insights into gene expression profiles at various stages of organoid development [38]. By analyzing transcriptomic data, researchers can identify key markers and signaling pathways associated with nephron differentiation and maturation [33, 145]. Comparisons with primary native tissue provide a critical means of assessing how closely organoids replicate in vivo kidney states, thereby supporting their validation as CIVMs [38]. Large‐scale single‐cell RNA sequencing (scRNA‐seq) profiling has shown that transcriptomic benchmarking can measure organoid reproducibility, revealing consistent major cell classes and variable off‐target populations, underscoring the value of transcriptomics for protocol refinement [37]. Other studies using scRNA‐seq have demonstrated measurable improvements in protocol optimization, including reduced off‐target populations and enhanced nephron segmentation accuracy, highlighting the direct impact of transcriptomic feedback on organoid reproducibility [145]. In addition, new computational tools, such as DevKidCC [62], enable standardized and unbiased classification of cell identities across datasets, facilitating direct comparisons between differentiation protocols and revealing differences in nephron patterning, stromal composition, and off‐target populations [33]. Context‐of‐use assays further ensure that these models are functionally predictive for nephrotoxicity screening, enhancing reproducibility and integration into the DDP [146].

In addition, integrating proteomics data introduces an additional layer of complexity that supports validation of kidney organoid development [28], and offers a valuable readout for toxicity screening by capturing comprehensive molecular changes in response to drug treatment [18]. Proteomic profiling of kidney organoids offers a powerful means to map active molecular pathways, link protein‐level changes to phenotypic outcomes, and identify toxicity‐associated biomarkers, thereby deepening our understanding of renal physiology and pathology in a human‐relevant system [147].

With such approaches, it is now possible to track the activation or suppression of specific genes and proteins associated with cellular stress, inflammation [148], and injury repair pathways [131]. Multi‐omics analysis can provide early and sensitive indicators of toxicity, offering a more detailed and dynamic assessment of both development and drug‐induced effects on kidney organoids [149, 150, 151]. Importantly, these approaches allow researchers to assess not only discrete biomarkers but the full spectrum of gene expression changes, pathway activation states, and protein‐level injury signatures, yielding a much more comprehensive and mechanistic insight in the injury profile than traditional toxicity assays. Given the dynamic nature of multi‐omics data acquisition and the continuous evolution of analytical pipelines, adherence to standardized frameworks, such as those developed by ISO, is essential for tracking and maintaining result concordance [152]. Establishing common data formats, quality thresholds, and reporting practices is particularly important for multi‐center efforts where analytical variability can obscure true biological effects. This would not only facilitate enhanced reproducibility but also improve cross‐study comparisons and the broader integration of kidney organoid models into preclinical research for regulatory assessments.

3.5. In Silico Models and Adverse Outcome Pathways for Nephrotoxicity

In silico models are increasingly being utilized to predict nephrotoxicity by leveraging advanced computational tools to simulate and analyze the chemical and biological processes underlying kidney function and drug‐induced toxicity. These models incorporate vast datasets from various sources, including chemical drug structures, biological transcriptomic, and proteomic data, to construct predictive frameworks that can identify potential nephrotoxins [129, 153, 154, 155, 156]. Furthermore, in silico models were also proposed to tackle obstacles from in vitro to in vivo translation. The basic principles of pharmacokinetics, pharmacology, and physiology have long been utilized as the foundation of interspecies translation, and several in silico tools have been established in drug development studies [20, 157].

Adverse outcome pathways (AOPs) are being established to provide a standardized framework that links molecular initiating events (MIE) through a series of key events (KE) to adverse outcomes observed in toxicity. This systematic approach facilitates the organization and integration of mechanistic knowledge from systems biology and toxicology [158]. In the context of nephrotoxicity, AOP frameworks capture well‐established mechanisms at the proximal tubule epithelium; the primary site of DIKI [159]. These pathways are mapped in accordance with OECD guidelines and harmonized terminology as provided by the Collaborative Adverse Outcome Pathway Wiki. Integrating AOP‐derived insights into in silico/in vitro model systems creates a synergistic approach that enhances the overall predictability of nephrotoxicity. This convergence of AOP frameworks, computational modeling, and experimental assays using more physiologically relevant CIVMs [160], represents a promising strategy for advancing predictive toxicology, reducing reliance on animal models and repeated dose toxicity studies [161, 162].

Various combinations of these advanced endpoint analysis tools are being employed to enhance the characterization of kidney organoids, offering valuable insights into their structural and functional properties, as well as their potential for assessing and predicting nephrotoxicity. However, caution is needed when applying these technologies, as variability in protocols and methodologies can influence data interpretation and comparability [140]. Establishing cross‐laboratory best practices and standardized approaches will further amplify the potential of kidney organoids as robust, predictive in vitro models.

4. Concluding Remarks and Future Perspectives

Kidney organoids represent a promising next‐generation in vitro model for nephrotoxicity screening. Their ability to recapitulate key aspects of kidney development, transporter expression, and nephron functionality has positioned them as valuable tools in the DDP [9]. Recent advances in enabling‐technologies enhance the physiological relevance of kidney organoids by improving their maturation and vascularization, while also addressing practical challenges such as consistent reproducibility and scalability [109]. Furthermore, the combination with advanced data analysis technologies gives researchers the tools to improve the DDP workflow (Figure 5a). For kidney organoids to be fully integrated into toxicity screening, standardization challenges must be addressed by establishing cell sourcing guidelines [58], and SOPs for kidney organoid generation [10], as well as for other supporting technologies [51]. Ongoing collaborative efforts among regulatory agencies, industry, and research organizations are essential for the establishment of universal guidelines to facilitate industry adaptation and ensure regulatory acceptance (Table 4). However, given the rapid advances in stem cell technologies and organoid engineering, these frameworks must be continuously updated to remain fit‐for‐purpose. Importantly, beyond universal guidelines, there is a pressing need for a kidney‐specific CIVM framework that defines standardization criteria for the generation and application of kidney organoids in drug development, thereby ensuring both scientific robustness and regulatory acceptance (Figure 5b).

FIGURE 5.

(a) Comparison of the traditional approach to the drug development process, defined by several key stages, and an envisioned modern approach. The implementation of CIVMs (organoids, tubuloids, OoCs), in silico models, and new technologies is expected to reduce the length of time, and number of drug candidates needed at each stage of the process, while also providing new drug therapies to cover a broader diversity of patient population. (b) Defining consensus on kidney organoid models by establishing a unified framework for generating kidney organoids with consistent structure and function considering standardization at each phase of organoid culture, data acquisition, and interpretation for prediction of nephrotoxicity and refinement of model design. See also Table 4 for a summary of key regulatory and standardization guidelines relevant to this framework. Created in BioRender. Kearney, H. (2025) https://BioRender.com/8vpk6rg.

Emerging technologies are transforming how we extract meaningful data from kidney organoids, enhancing their utility in drug toxicity screening. Bioengineered reporter lines facilitate precise characterization of organoid cell types and can also be utilized to automate toxicity screening through high‐content imaging platforms [113, 133, 134]. Automated high‐content screening platforms incorporating robotics and advanced microscopy improve the scalability and efficiency of nephrotoxicity screening [129]. Multi‐omics data support the development and validation of kidney organoid models, and provides deeper and more precise insights into nephrotoxicity and injury repair pathways. Analyzing these large datasets using deep learning algorithms further streamlines the process, enabling data‐driven predictions and improving drug safety evaluation. Furthermore, the establishment of in silico/AOP models provides mechanistic insights into nephrotoxicity by integrating computational modeling with standardized adverse outcome pathways, enhancing predictive accuracy [161]. Additionally, in silico modeling can guide the refinement of in vitro model design by identifying the essential nephron segments needed for a simplified yet effective models, improving both relevance and practicality [163].

Kidney organoids are rapidly evolving and are set to become critical components of next‐generation in vitro kidney models in the DDP. Technological innovations continue to refine their complexity, reproducibility, and functional maturity, giving these models the potential to redefine preclinical nephrotoxicity testing by reducing reliance on animal studies, and accelerating the development of safer drugs. Ultimately, advancing kidney organoids as robust, scalable, and predictive platforms for DIKI research will require a collaborative effort in standardizing multiple technologies and integrating them into drug development pipelines.

Conflicts of Interest

The authors declare no conflicts of interest.