Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Trends Pharmacol Sci. 2020 Nov 26;42(1):31–44. doi: 10.1016/j.tips.2020.11.002

Developing Insulin Delivery Devices with Glucose-Responsiveness

Zejun Wang 1,2, Jinqiang Wang 1,2, Anna R Kahkoska 3, John B Buse 3,*, Zhen Gu 1,2,4,*
PMCID: PMC7758938  NIHMSID: NIHMS1650096  PMID: 33250274

Abstract

Individuals with Type 1 and advanced Type 2 diabetes require daily insulin therapy to maintain blood glucose levels in normoglycemic ranges to prevent associated morbidity and mortality. Optimal insulin delivery should offer both precise dosing in response to real-time blood glucose levels as well as a feasible and low-burden administration route to promote long-term adherence. A series of glucose-responsive insulin delivery mechanisms and devices have been reported to increase patient compliance while mitigating the risk of hypoglycemia. This review discusses the currently available insulin delivery devices, the recent developments towards generation of glucose-responsive delivery systems and provides commentary on the opportunities and barriers ahead regarding the integration and translation of current glucose-responsive insulin delivery designs.

Keywords: Drug delivery, Glucose-responsive, Insulin administration device, Diabetes treatment

Current Insulin Delivery Devices

Diabetes mellitus is a disorder of glucose metabolism that occurs secondary to the destruction of the insulin-producing β-cells of the pancreas (Type 1 diabetes, see Glossary) [1] or peripheral insulin resistance associated with decline in β-cell function over time (Type 2 diabetes [2]). Insulin is a polypeptide hormone secreted by β-cells that at higher levels promotes the transport and storage of glucose from the bloodstream into muscle, fat, and liver and at lower levels regulates the release of glucose and lipids from storage deposits. The storage of fuels is essential to provide energy for body activities between meals and during periods of fasting. In healthy individuals, β-cells sense rising serum glucose concentrations after meals and release insulin, and in the fasting state, provides basal insulin levels to restrain glycogenolysis and lipolysis. Elevated plasma glucose levels promote insulin secretion while low glucose levels inhibit insulin secretion. Therefore, exogenous and continuous administration of insulin remains central to the treatment of type 1 diabetes and advanced type 2 diabetes, the goal of which is to emulate the β-cell glucose-responsiveness to achieve normoglycemic or near-normoglycemic blood glucose levels [3]. However, insulin dosing is highly individualized and varies within an individual based on dietary intake, physical activity, general health state, stress, sleep, and other hormone levels [4]. Unfortunately, inadequate control of blood glucose levels can lead to prolonged periods of hyperglycemia (high blood sugar), which is associated with an increased risk for both chronic complications such as cardiovascular disease, neuropathy, nephropathy, and retinopathy, as well as acute episodes of life-threatening hypoglycemia (low blood sugar) [5].

Various insulin delivery devices have been developed to deliver bioactive insulin [6, 7] in order to maintain normoglycemic blood glucose levels. The major insulin delivery devices that are currently in use are discussed below and listed in Table 1 [8].

Table 1.

Advantages, limitations, and representative technologies of insulin delivery routes currently in use and under investigation/ development are listed.

Stage Insulin Advantages Limitations Representative References

delivery routes technologies

Currently in use Subcutaneous Widely used;
Approved for insurance coverage
Painful administration;
Possible bleeding, bruising, lipohypertrophy, lipoatrophy
Insulin syringes;
Insulin pen;
Insulin jet injectors;
Insulin pump
[8]

Pulmonary Large absorption area;
Highly vascularized;
Low enzymatic activity;
Higher transmucosal bioavailability;
Rapid and no need for enhancers
Side effect such as cough;
Potential lung cancer risk;
Clearance by alveolar macrophages
Exubera®
Afrezza®
Dance 501
[28, 118]

Under investigation Ocular Fewer immunological reactions;
Convenient administration;
Fast systemic absorption
Requires enhancer Gelfoam® [33, 119]

Nasal Potential bypass of hepatic first-pass metabolism;
Low enzymatic activity
Small surface area;
Possible irritation of nasal mucosa;
Absorption varies between individuals
Nasulin™ [34]

Buccal Easy removal;
Fast-flowing blood supply;
Highly acceptable to patients;
Direct access to the systemic circulation
Small absorption surface area;
Low permeability;
Unfavorable taste;
Choking hazard;
Absorption affected by saliva or drinking
Oral-Lyn™;
RapidMist™
[120, 121]

Oral Highly acceptable to patients;
Convenient administration;
Reduced peripheral hyperinsulinemia
Low permeability;
Enzymatic degradation;
Transit time delay;
High dosage required
Capsulin™ [45]

Transdermal Easy removal to terminate dosing;
Convenient administration;
Large surface area
Possible irritation to application sites Chemical enhancers;
Microneedles;
Iontophoresis;
Electrophoresis;
Sonophoresis
[46]

Insulin Syringes

Insulin delivery via syringe requires patients to manually fill insulin from a vial and subcutaneously inject the required dose. Compared to other insulin delivery devices such as insulin pens and pumps (reviewed below), syringes are associated with the lowest cost. These syringes are equipped with fine needles that have special coatings such as diamond-like carbon (DLC) coatings [9] and metallic glass coatings [10], which confer favorable properties including reduced friction, improved biocompatibility, resistance to corrosion, and antibacterial ability. Standard injections with the syringes require multiple skin punctures, which can be partially addressed with an i-Port Advance® insulin injection port. It is a small and discrete patch that sticks to you like an adhesive bandage, which is changed every three days. It could be self-applied to the skin site simply by squeezing the insertion device that comes with the port, leaving a soft, flexible cannula underneath the skin [11]. Each dose of insulin is injected with a regular syringe (needle size 5–8 mm) through the septum of the immobilized port avoiding direct skin contact of a needle and then subcutaneously delivered through the cannula of the port. This means you don’t need to poke your skin every time you take a shot and can wear it without affecting normal daily activities.

Insulin Pens

Insulin pens resemble oversized ink pens. These devices are pre-filled with insulin and are used with disposable pen needles. Insulin dosing is achieved by a dial or dose knob, thereby offering more accurate dosing than manual filling of a syringe [6]. In 1985, Novo Nordisk launched the first insulin pen named the NovoPen [12]. Through decades of refinements, digital “smart pens” have now been designed with memory functions, such as the HumaPen Memoir, the first digital insulin pen with memory [13]. They also enable wireless connection (Bluetooth and near-field communication) with smartphones (e.g., InPen System from Companion Medical) for assistance with insulin dose calculation, recording and data management [14].

Insulin Jet Injectors

Jet injectors are needle-less devices that produce high-pressure air jets which deliver a stream of vaporized insulin through the skin. In such delivery devices, users deliver insulin by pressing a button on the device. The pressure is adjustable based on the injection site, which can be optimized to minimize skin trauma or bruising [15]. It has been suggested that this method may enhance early insulin absorption and glycemic control [16]. The device is relatively larger, more costly than regular insulin shots, therefore has not been widely adopted. However there are no needle disposal issues and may particularly benefit those with severe insulin-induced lipoatrophy or needle phobia [1719].

Insulin Infusion Pumps

Insulin pumps are small, computerized devices resembling a pager that continuously infuse insulin from a small reservoir in the device to a subcutaneous catheter that the user inserts on the abdomen, hip, arm, or leg. Similar to a combined basal-bolus regimen attained by injection of long-active and rapid-acting insulin (Box 1), the pump is preprogrammed to mimic the human pancreas by continuously delivering small doses of short-acting insulin (basal rate), while users can manually adjust the delivery of larger boluses of rapid-acting insulin during meals or for corrections [20]. In recent years, major efforts have been made to directly integrate real-time continuous glucose monitoring (CGM) devices with insulin pumps via algorithms meant to prevent insulin-induced hypoglycemia [21] and modulate basal rates to offer glucose-responsive hybrid closed-loop insulin delivery [22, 23] (see section on Artificial Pancreas Devices below for details).

BOX 1. Different types of insulin in use.

The four major types of insulin listed below are classified based on how quickly they respond, when the peaks occur, and the duration after injection (Box 1, Figure I).

Rapid-acting insulin starts working in 15 minutes post-injection, the peak occurs in 1 or 2 hours, and lasts for 2–4 hours. Examples: insulin aspart (Fiasp, NovoLog) Insulin glulisine (Apidra), and insulin lispro (Admelog, Humalog)

Regular or short-acting insulin usually works within 30 minutes post-injection, peaks between 2–3 hours, and is effective for 3–6 hours. Examples: Human Regular (Humulin R, Novolin R, Velosulin R)

Intermediate-acting insulin generally reaches the bloodstream in 2–4 hours post-injection, peaks 4 to 12 hours later, and lasts for 12 to 18 hours. Examples: NPH (Humulin N, Novolin N, ReliOn)

Long-acting insulin reaches the bloodstream in 1–2 hours post-injection, does not peak, and is valid up to 24 hours. Examples: degludec (Tresiba), detemir (Levemir), and glargine (Basaglar, Lantus)

Insulin Inhalers

Insulin inhalers consist of a holding chamber and an insulin release unit. Single-dose blisters packed with insulin formulated as powder are loaded into a slot on the device and dispersed as an aerosol cloud, which is captured in a holding chamber. The user inhales the aerosol containing the insulin particles at the beginning of a slow, deep breath [24, 25].

However, the pulmonary route of insulin administration has been commercialized with limited success. In 2006, Exubera® became the first Food and Drug Administration (FDA)-approved inhaled insulin product, which delivers fine insulin powder to the lung of the user through an inhaler. However, it was withdrawn from the market, a year after it was approved [26]. During this short marketing period, the technology was viewed as cumbersome by users, with ongoing concerns about the need for pulmonary function testing, respiratory side effects, hypoglycemia, and a small number of associated lung cancer cases [27]. Another inhaled insulin product Afrezza® was launched in 2015 with a more discrete device and an enhanced pharmacodynamic pattern with faster onset of activity and shorter duration of action than other rapid-acting insulins that were more favorable for meal-associated and correction dosing. It also comes in the form of dry powder which becomes aerosolized when breathed through the inhaler. Additionally, Dance 501 inhaler, which delivers a novel gentle mist of human insulin formulation through inhalation, has showed rapid onset of action and no severe damage to lung functions in phase II clinical trial (Clinical Trials Noi.: NCT04100473) [28]. These efforts are promising to enhance the safety of inhaled insulin and gradually expand market uptake.

Challenges associated with current insulin delivery system

The subcutaneous insulin delivery system, which is covered by insurance remains the most widely used modality of insulin delivery currently. However, patient adherence are challenged by fear of needles, occurrence of bleeding, lipoatrophy, and the inconvenience of insulin injections. These disadvantages have distributed a market for pulmonary insulin delivery systems, which excel in high permeability of the large surface area of lungs, allowing rapid delivery of small particles into the systemic circulation without interruption from degrading peptidases. Nevertheless, adverse issues emerged including effects on pulmonary function, risks of lung cancer, and formation of insulin antibodies.

The challenges of current insulin delivery devices outlined above range from logistical challenges, side effects, and public embarrassment to device malfunction, all of which may complicate daily usage and limit efficacy in the long term. In addition, these modalities of insulin delivery require ongoing attention and engagement from patients, in addition to clinic-level efforts to ensure that patients can afford all required supplies and receive ongoing education [29]. For these reasons, the development of next-generation insulin delivery devices with decreased patient burden, improved efficacy and glycemic outcomes, and affordable pricing is appealing and could offer significant improvements on the currently available options. Understanding the advantages and limitations of various insulin delivery routes is imperative to the future design of new devices and efforts have been made to expand the delivery routes beyond the currently available subcutaneous and pulmonary delivery [3032]. These efforts are reviewed below.

Emerging Routes of Insulin Delivery

Ongoing efforts to expand the delivery routes have focused on the development of ocular [33], nasal [34, 35], buccal, oral [3638], and transdermal (delivery through skin) routes [39] (Table 1). The features of these routes are introduced below.

Apart from the ease of administration, the ocular route offers comparable systemic absorption rate to injections, less sensitive immunological reactions in the eye tissue as well as the ability to bypass first-pass gastrointestinal and liver effects [40]. However, this route suffers from low bioavailability caused by blinking and tearing [33]. Absorption could be increased with the assistance of enhancers, but can cause eye toxicity and local irritation [41].

The nasal mucosa can facilitate insulin absorption directly through the nasal cavity to the systemic circulation under the assistance of absorption enhancers or promoters, which modulate insulin permeability or prolong its residence time. Unfavorable aspects include small surface area and possible nasal irritation [34, 42].

Buccal [43] insulin is administered and rapidly absorbed directly via the buccal mucosa located in the cheeks to the bloodstream. Trans-buccal delivery systems are easy to apply and remove, which is highly acceptable to patients. For example, Generex Biotechnology (Toronto, Canada) introduced a buccal system to spray insulin through a liquid aerosol formulation accompanied by enhancers, stabilizers, and a non-chlorofluorocarbon propellant via a metered-dose aerosol applicator (Oral-Lyn). Repeated doses may be required as insulin absorption suffers from the small absorption surface, low permeability, and action of saliva and drinking.

Regarding recent oral insulin device design, Abramson et al. developed an ingestible self-orienting millimeter-scale applicator (SOMA) with reorientation ability to directly deliver insulin through the gastric mucosa while avoiding perforation [37]. They further designed an ingestible and dissolvable microneedle injector that orally delivers insulin into intestinal tissue using a set of unfolding arms [38]. Oral insulin delivery is ideal for its convenience and high patient acceptability. However, high doses are required as only minimum of the oral insulin could make its way to the systemic circulation due to physical, chemical, and biological barriers [44, 45].

Transdermal route requires facilitation from chemical substances, electric current, ultrasound techniques, or microneedle array patches to penetrate or weaken the intrinsic barrier of the human skin against foreign proteins [46]. Chemical enhancers [47, 48] such as propylene glycol, ethanol, oleic acid, surfactants, and membrane-permeable peptides function by disrupting the highly ordered lipid bilayer in stratum corneum, which leads to the formation of nanosized lipid-packing defects that enhance insulin translocation but may also degrade the natural protective barrier [49]. Iontophoresis achieves transdermal delivery of insulin by creating an electrical potential between the electrode-attached skin surface and the capillaries underneath. Use of low-frequency ultrasound or sonophoresis has also been demonstrated to assist passage of insulin through the skin by providing an ultrasound wave-triggered resonating mechanical force that induces hyperthermia or collapse cavitation (formed by rapid expansion and collapse of gaseous bubbles in response to ultrasonic) [50]. Finally, microneedle-mediated drug delivery systems deliver insulin at the epidermal and dermal layer by temporally disrupting the stratum corneum and can be achieved with different materials and structures, including solid microneedles, hollow microneedles, dissolving/biodegradable microneedles, and bioresponsive microneedles [39, 46]. To this end, an upgraded glucose-responsive insulin delivery microneedle patch fabricated by in situ photopolymerization of insulin, N-vinylpyrrolidone monomers, crosslinkers, and the glucose-sensing 3-(acrylamido) phenylboronic acid have achieved 100% insulin loading efficiency and 20 wt% (percentage by weight) loading capacity that facilitated blood glucose regulation in mice and minipigs [51]. This insulin delivery modality offers a painless platform with convenient administration and easy removal for treating diabetes [52]. This method can however cause skin irritation to the application sites [53, 54].

These under-developing routes and the associated devices are favorable in administration convenience and patient compliance, but lack in glucose-responsive features. Thus, integrating the novel insulin delivery strategies with formulations responsive to glycemic variations will potentially generate an ideal glucose-responsive insulin delivery device.

Glucose-Responsive Insulin Delivery

To dynamically maintain normoglycemia and reduce the risk of hypoglycemia, insulin delivery formulations and devices have been developed to respond to changes in the serum glucose levels in real-time and can be classified into three major categories. The first category includes the family of artificial pancreas devices (APDs, Figure 1A), which integrate CGM data with insulin pumps using internal or external controller algorithms. The second category comprises of synthetic designs which encapsulate insulin within a glucose-sensitive matrix that swells or shrinks in the presence or absence of glucose to release insulin (Figure 1B). The third category is the molecular glucose-responsive insulin delivery, which involves the engineering or modification of the insulin molecule such that it acquires intrinsic glucose-responsive activity (Figure 1C) [55]. Each category of glucose-responsive insulin delivery is discussed in detail below.

Figure 1. Three types of glucose-responsive devices or modules for insulin delivery.

Figure 1.

(A) The components and closed-loop mechanism of artificial pancreas devices. (B) The design of a matrix-based insulin delivery device. (C) The bioconjugation strategies for engineering glucose-responsive insulin molecules.

Artificial Pancreas Devices

Conventional insulin pump therapy (briefly discussed above) requires users to calculate and deliver all insulin doses manually, incorporating information about current blood glucose levels, dietary intake, physical activity, and general health state [4]. The APDs aim to improve on insulin pump therapy by automating insulin delivery in response to glucose levels with minimal to no involvement from users [56]. Generally speaking, APDs consists of a CGM and insulin infusion pump connected by a closed-loop computer-controlled algorithm [57]. The core of APD is the algorithm used to calculate insulin dosage with all available data in real time. Typically, the algorithms use CGM data as well as information provided by individuals regarding carbohydrate intake and physical activity and are based on traditional control engineering theory. Devices that require such patient input are often referred to as hybrid closed-loop systems [58, 59]. In 2016, the Medtronic’s MiniMed 670G System (Medtronic, Fridley, MN) became the first FDA approved hybrid closed-loop APD [60]. A second device, Control-IQ (Tandem Diabetes, San Diego, CA) was approved recently while several others are in development [56, 61]. However, these systems still rely on manual input regarding meal and exercise activities. Fully automated closed-loop devices, including single hormone (insulin-only) and dual hormone (insulin and glucagon) delivery systems, are currently under development [62].

Other efforts have explored the use role for artificial intelligence (AI) in diabetes management over the past few years [63]. This includes AI-powered CGM systems (such as the FDA approved Medtronic’s Guardian Connect) that makes blood glucose predictions through predictive algorithm to alert the patient of hypoglycemia or hyperglycemia so that actions could be taken in advance to gain normal glucose level control. In addition, AI technology could analyze how the user’s blood glucose levels respond to adverse glycemic events and activities, to provide the patient with personalized management advice and lifestyle support [6466].

Matrix-Based Insulin Delivery

Matrix-based insulin delivery devices consist of three aspects: a glucose-sensing motif, a stimuli-responsive material and a system for insulin release [67, 68]. Current glucose-responsive drug delivery systems predominantly rely on the specific recognition or affinity between glucose molecules and the glucose-sensitive motifs and can broadly be classified into 3 systems: glucose oxidase (GOx)-based [69], glucose-binding proteins [70] or aptamers mediated [71], and phenylboronic acid (PBA)- based systems [51, 72, 73].

GOx-Based System

GOx is a natural glucose specific catalytic enzyme that catalyzes the oxidation of glucose to hydrogen peroxide and gluconic acid in the presence of oxygen. GOx- based systems consist of insulin and GOx loaded into stimuli-sensitive material such as membranes, hydrogels, or microcapsules [74]. Alternatively, nanosized particles such as metal-organic frameworks, mesoporous silica nanoparticles, acetylated-dextran nanoparticles, and polymersome-based nanovesicles are also utilized to accommodate GOx [75, 76]. The insulin release is triggered by change in pH associated with generation of H2O2 [77] during the catalytic oxidation of glucose. This is typically accomplished via the protonation-induced volume change of the synthetic system, such as swelling and shrinking of membranes, hydrogels, or microcapsules [74]. While acid-labile chemistries are relatively slow, hypoxia- and peroxide- sensitive chemistries have been leveraged as insulin release stimulus to achieve a faster response in the GOx-based glucose-responsive systems.

The advantages of these systems are that the enzymatic reaction is glucose specific, and the production of stimulus (changes in pH) is positively correlated to glucose concentration, which is an ideal feature for accurate detection of glucose concentration. Hence the system has been employed in glucose meters [78, 79]. Furthermore, the system can be easily coupled with mediators or immobilized with nanomaterials to assist signal transfer from the enzyme to the working electrode and enhance sensing performance [80, 81].

However, the side product H2O2 is toxic to surrounding tissues, while the pH changes induced by gluconic acid do not occur rapidly in physiological environments. To remedy this, a peroxidase enzyme, such as catalase and catalase mimetic nanoparticles are usually co-loaded to alleviate toxic H2O2 generation [82]. Moreover, the activity of GOx is sensitive to environmental changes and degradation. Hence these systems suffer from degradation and diminished GOx activity over time which interferes with the sensitivity of glucose sensing and the efficiency of insulin release [83].

Glucose-Binding Proteins or Aptamers

Lectins are a family of carbohydrate-binding proteins that serve as natural receptor-based glucose-sensing moieties. Concanavalin A (ConA, a plant lectin purified from jack beans) is a glucose binding protein that can reversibly bind to both glucose and mannose. In Con-A based glucose-responsive insulin delivery systems, Con A are immobilized in insulin-loaded polymeric matrixes through the pendant saccharide moieties [84, 85]. Upon activation with elevated glucose levels, four ConA proteins are associated, forming a tetramer aggregate with four glucose molecule binding sites. The rapid binding of glucose to these Con A binding sites competitively replaces the saccharide moieties on the materials, resulting in the breakdown of the original compact structure and release insulin [67]. However, upon dissipation of the matrix network, increased free ConA may lead to risks of immunogenicity as well as the system losing its glucose-responsiveness [86]. The loss of glucose-responsiveness may be prevented by immobilizing the Con A protein to the insulin loaded polymeric scaffold, typically by covalent attachment [87]. Alternatively, utilizing synthetic glucose receptors with comparable glucose binding affinity (Ka ~ 18,000 M−1) to substitute natural lectins could potentially improve the glucose-responsiveness and avoid the immunogenicity of the insulin delivery systems [88]. The high specificity and affinity between glucose and ConA entrust these insulin delivery systems with exceptional glucose-responsiveness. Drawbacks such as poor solubility and low stability associated with ConA can be addressed by modification with hydrophilic polymers [89, 90].

Aptamers represent an alternative for antibodies, which are selected from a random sequence pool to specifically bind to a target molecule. Glucose-binding aptamers experience glucose-induced conformational changes before and after binding. When coupled with field-effect transistors it has been utilized for high sensitive detection of glucose [91]. This unique property could be further explored as a glucose-responsive trigger for insulin delivery.

PBA-Based Systems

Phenylboronic acid (PBA) is a synthetic glucose-binding compound with affinity to glucose in the physiological glucose concentration range. It is highly stable and durable in the physiological environment and can form a reversible covalent complex with polyol molecules such as glucose, poly(vinyl alcohol) (PVA), and dextran in aqueous solution. In aqueous milieu, there is a dynamic balance between the uncharged trigonal planar state of PBA and an anionic tetrahedral form of PBA. Upon glucose binding to the anionic tetrahedral structure, the equilibrium shifts toward the anionic form of PBA with enhanced hydrophilicity and increased negative charge density [92, 93]. PBA and its derivatives are frequently employed as structural elements to achieve glucose-responsiveness in insulin encapsulating materials such as membranes, bulk hydrogels, microgels, liposomes, micelles and nanomaterials [94]. The diffusion of the insulin molecules is achieved by swelling of the materials in the presence of glucose as PBA moieties undergo volume expansion and enlarged matrix porosity [95]. Specifically, glucose binding promotes the anionic tetrahedral form of PBA moieties, which increases the hydrophilic property of the synthetic system. Electrostatic repulsion created by adjacent negatively charged PBA molecules on the backbone further increases the expansion of the system [96]. While the advantages of the system involve ease of chemical modifications, diversity of matrix composition, and adjustability of the insulin release mechanism, the limitations are low specificity to glucose where the system can be disrupted by other saccharides in the blood. The safety and toxicity of the PBA-based system requires further evaluation [97, 98].

Molecular Glucose-Responsive Insulin

Molecular glucose-responsive insulin represents another important strategy that focuses on the modification of insulin to generate engineered insulin analogs with glucose-dependent properties [73, 99101] (Figure 2c). The intent of these designer analogs is to increase the safety margin of insulin treatment associated with overdosage delivery-induced hypoglycemia and mitigate the need for other glucose-responsive insulin delivery devices or formulations. Although such concepts have only recently emerged, these molecular glucose-responsive insulin systems represent an attractive future research target based on anticipated convenience and cost-effectiveness.

An early attempt to engineer glucose-response insulin coupled insulin with GOx through a disulfide bond, which is broken upon the enzymatic oxidization of glucose in vitro [102]. The resulting molecule liberated insulin exclusively upon exposure to hyperglycemic conditions due to the low Km of GOx for glucose. However, the byproduct H2O2was associated with tissue irritation due to the generation of reactive oxygen species (ROS). Hoeg-Jensen et al. demonstrated the coupling of PBA derivatives to insulin with retained biological activity [103]. They further conjugated boronate-polyols with insulin to reversibly form soluble high molecular weight hexamer-hexamer self-assemblies, which was shown to release insulin in response to carbohydrate intake [101]. Chou et al. synthesized a class of insulin derivatives covalently conjugated with an aliphatic moiety and a PBA moiety [73]. Here, the aliphatic domain serves as an anchoring site for serum albumin or other hydrophobic components to achieve prolonged half-life in the systemic circulation, while the PBA domain confers glucose-responsive activity at physiologic pH. The modified insulin showed enhanced insulin release in response to a glucose challenge with the reduced risk of hypoglycemia in vivo.

In 2010, researchers from Merck modified insulin with carbohydrate groups to generate an insulin analog known as MK-2640, which shows an affinity for the insulin receptor as well as for the lectin receptor mannose receptor C-type 1 (MRC1). At normoglycemia or during hypoglycemia, MK-2640 competitively binds to MRC1 over glucose, resulting in insulin clearance via endocytosis and lysosomal degradation [104]. MK-2640 initiated the first phase I human clinical trial associated with smart insulin in 2014 (Clinical Trials No: NCT02269735), which failed in 2016 due to a lack of efficacy. More recent attempts have been made to conjugate insulin with glucose transporter (Glut) inhibitor which has been shown to retain anti-hyperglycemic effects while mitigating hypoglycemia [105, 106]. This insulin analog can reversibly and dynamically bind to insulin receptors as well as endogenous Glut, with free concentrations determined by the surrounding glucose concentration. Increased blood glucose levels result in more free insulin analog available to bind to the insulin receptors while freeing Glut on the cell membrane to promote the clearance of blood glucose [105]. When the insulin analog is delivered in excessive doses, the glucose transport activity of free Glut is attenuated by the formation of the insulin analog-Glut complex, thereby preventing hypoglycemia.

To improve biocompatibility, Glut expressing erythrocytes rather than synthetic matrix modified with glucose binding molecules have been used to load and deliver these glucose-responsive insulin derivatives. These have also been validated during glucose tolerance tests in vivo [107].

Conclusions and Future Perspectives

Here we reviewed the current devices for insulin delivery, the exploration of alternative routes in addition to the subcutaneous and pulmonary routes in use, and the glucose-responsive strategies including artificial pancreas devices, synthetic system-based delivery and molecular design of insulin analogs. Currently available insulin delivery devices such as insulin syringes, insulin pens, insulin jet injectors, insulin infusion pumps, and inhalers are generally inadequate to offer satisfactory glucose-responsive insulin delivery. A fully glucose-responsive insulin delivery may improve outcomes associated with insulin therapy in type 1 and advanced type 2 diabetes via the development of insulin delivery systems that are able to accommodate to inter- and intrapersonal variability in blood glucose levels and insulin needs while decreasing the risk for hypoglycemia and overall patient burden [108]. However, there remain several key issues in the future design or translation of glucose-responsive insulin delivery systems that must be addressed prior to use in the clinic. These critical questions includes biocompatibility and simplified administration of wearable or implantable systems, the assessment of long-term treatment efficacy of insulin formulations, as well as safeguard to risks of hypoglycemia. To exploit insulin delivery feasibility of alternative routes, it is essential to seek the optimal integration of glucose-responsive insulin formulations and artificial intelligence with intentionally designed devices and for their release (see Outstanding Questions).

Outstanding Questions.

  • Are there other new glucose-sensing elements to be exploited in the design of insulin delivery devices?

  • Is it feasible to develop glucose responsive insulin delivery devices that are implantable?

  • What are the logistics and benefits associated with integrating glucagon delivery as a further “safeguard” for hypoglycemia?

  • Is it possible to combine cell therapy with glucose-responsive insulin delivery devices?

  • Is it possible to engineer robust, oral insulin delivery in a glucose-responsive manner?

(1) To improve the ease of use and acceptability of APDs, efforts should be made to simplify device interfaces and eliminate tubing and wires that are connected to the body. Ideally, implantable components could be incorporated to free patients from specific burdens associated with external devices [109], which necessitates the development of inflammation and fibrosis-resistant materials.

(2) Ideally, devices should be developed to adapt to glucose-responsive modules with different sizes, viscosity, and other material properties [110]. For example, hydrogels are large in size with low fluidity and therefore require a device that can provide pretreatment of the formulation (i.e., blending with the delivery solution) for ease of administration. While glucose-responsive insulin molecules could be easily injected, they would require regular and frequent administration over the day and night; therefore, delivery devices with precise control of dosing could enable daily use [111, 112]. For microneedle-based formulations, the use of stamp-like applicators could improve the application process with standardized force upon skin penetration.

(3) Ongoing development and applications of machine-learning techniques to generate algorithms capable of adapting to diverse therapeutic factors and lifestyle-related blood glucose fluctuations may offer optimized outcomes associated with APDs, including both hybrid closed-loop systems and fully-automated insulin delivery systems. [113].

(4) Continued efforts to develop and disseminate a dual or multiple hormone device incorporating insulin, amylin, GLP-1 (glucagon-like peptide 1), GIP (gastric inhibitory polypeptide), and glucagon could replicate the full functionality of the human pancreas and potentially co-optimize the treatment of hyperglycemia with the reduction of the risk of hypoglycemia and favorable effects on body weight [114].

(6) Combining artificial or engineered pancreatic beta cells with well-established delivery devices may provide a solution for glucose mediated-insulin delivery without preservation difficulties [115] or the need for human graft donors in the future [116]. Alternatively, using devices that provide long-term cell culturing environment with semi-permeable biomaterials could accommodate and isolate pancreatic β-cells. This design would allow for the diffusion of hormones secreted by pancreatic β-cells while preventing the immunologic destruction associated with directly transplanted insulin-secreting cells [117].

In summary, the advancement of glucose-responsive insulin delivery devices relies on the development of glucose-responsive insulin analogs or synthetic formulations, incorporation of AI technology, and device engineering. More importantly, it is the smart integration of the above-mentioned elements.

Box 1, Figure I:

Box 1, Figure I:

Schematic showing peak and duration performance of the four major types of insulin, classified based on how quickly they respond, when the peaks occur, and the duration after injection

Highlights.

  • Understanding the mechanism, advantages, and limitations of various insulin delivery routes is imperative for the future design and optimization of innovative delivery devices.

  • Incorporating glucose-responsive modules with drug delivery devices could promote self-regulated insulin delivery in response to the real-time, metabolic needs of patients, thereby mitigating exposure to both hyperglycemia and hypoglycemia.

  • There have been major advances in the development of glucose-responsive insulin delivery devices, including efforts to design artificial pancreas devices, synthetic system-based glucose-responsive mechanisms, and engineered molecular glucose-responsive insulin.

  • Integration of minimal-invasive delivery strategies is essential for reducing the day-to-day burden of insulin therapy to improve patient adherence and glycemic outcomes.

ACKNOWLEDGEMENTS

This work was supported by the grants from NIH (grant no. R01 DK112939 01A1); JDRF (3-SRA-2015-117-Q-R, 1-PNF-2019-674-S-B); American Diabetes Association (grant no. 1-15-ACE-21); and National Science Foundation (grant no. 1708620). ARK is supported by the National Institute Of Diabetes And Digestive And Kidney Diseases of the National Institutes of Health under Award Number F30DK113728. JBB is supported by grants from the National Institutes of Health (UL1TR002489, UC4DK108612, P30DK124723). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

GLOSSARY

Aptamer

oligonucleotide or peptide molecules that can specifically bind to a target molecule.

Basal-bolus regimen

a person with diabetes taking the combination of a long-acting basal insulin with a rapid-acting insulin throughout the day.

Glucagon

a hormone secreted by α-cells of the pancreas that increases glucose and fatty acids concentration in the bloodstream.

Glucose oxidase

an enzyme that catalyzes the oxidation of glucose to hydrogen peroxide and gluconic acid in the presence of oxygen.

Glycogenolysis

a biochemical process that breaks down glycogen into glucose-6-phosphate during lack of glucose.

Lipoatrophy

loss of subcutaneous fat tissue.

Reactive oxygen species (ROS)

Chemically reactive molecules that contains oxygen and are known to cause damage to DNA, RNA, and proteins in a cell.

Stratum corneum

the horny outermost layer of the skin, made up of very resilient and specialized skin cells and keratin.

Type 1 diabetes

a chronic condition characterized of high blood glucose due to little or no insulin production by pancreas.

Type 2 diabetes

a chronic condition characterized by high blood glucose due to impaired glucose tolerance, even with insulin.

Footnotes

DISCLAIMER STATEMENT

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

RESOURCE

i) https://clinicaltrials.gov/

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

REFERENCES

  • 1.Atkinson MA and Eisenbarth GS (2001) Type 1 diabetes: New perspectives on disease pathogenesis and treatment. Lancet 358 (9277), 221–229. [DOI] [PubMed] [Google Scholar]
  • 2.Stumvoll M et al. (2005) Type 2 diabetes: Principles of pathogenesis and therapy. Lancet 365 (9467), 1333–1346. [DOI] [PubMed] [Google Scholar]
  • 3.Yu JC et al. (2016) Stimuli-responsive delivery of therapeutics for diabetes treatment. Bioeng. Transl. Med. 1 (3), 323–337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Majeed W and Thabit H (2018) Closed-loop insulin delivery: Current status of diabetes technologies and future prospects. Expert Rev. Med. Devices 15 (8), 579–590. [DOI] [PubMed] [Google Scholar]
  • 5.American Diabetes, A. (2009) Diagnosis and classification of diabetes mellitus. Diabetes Care 32 Suppl 1, S62–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Pisano M (2014) Overview of insulin and non-insulin delivery devices in the treatment of diabetes. P T 39 (12), 866–76. [PMC free article] [PubMed] [Google Scholar]
  • 7.Meneghini LF and McNulty JN (2017) Role of devices in insulin delivery. Diabetes Technol. Ther. 19 (2), 76–78. [DOI] [PubMed] [Google Scholar]
  • 8.Shah RB et al. (2016) Insulin delivery methods: Past, present and future. Int. J. Pharm. Invest. 6 (1), 1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Dearnaley G and Arps JH (2005) Biomedical applications of diamond-like carbon (dlc) coatings: A review. Surf. Coat. Technol. 200 (7), 2518–2524. [Google Scholar]
  • 10.Chu JP et al. (2016) Non-stick syringe needles: Beneficial effects of thin film metallic glass coating. Sci. Rep. 6, 31847. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Khan AM and Alswat KA (2019) Benefits of using the i-port system on insulin-treated patients. Diabetes Spectr. 32 (1), 30–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Rex J et al. (2006) A review of 20 years’ experience with the novopen family of insulin injection devices. Clin. Drug Investig. 26 (7), 367–401. [DOI] [PubMed] [Google Scholar]
  • 13.Ignaut DA and Venekamp WJRR (2007) Humapen (r) memoir (tm): A novel insulin-injecting pen with a dose-memory feature. Expert Rev. Med. Devices 4 (6), 793–802. [DOI] [PubMed] [Google Scholar]
  • 14.Bailey TS and Stone JY (2017) A novel pen-based bluetooth-enabled insulin delivery system with insulin dose tracking and advice. Expert Opin. Drug Delivery 14 (5), 697–703. [DOI] [PubMed] [Google Scholar]
  • 15.Barolet D and Benohanian A (2018) Current trends in needle-free jet injection: An update. Clin. Cosmet. Investig. Dermatol. 11, 231–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Engwerda EEC et al. (2013) Needle-free jet injection of rapid-acting insulin improves early postprandial glucose control in patients with diabetes. Diabetes Care 36 (11), 3436–3441. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Baxter J and Mitragotri S (2006) Needle-free liquid jet injections: Mechanisms and applications. Expert Rev. Med. Devices 3 (5), 565–574. [DOI] [PubMed] [Google Scholar]
  • 18.Mitragotri S (2006) Innovation - current status and future prospects of needle-free liquid jet injectors. Nat. Rev. Drug Discovery 5 (7), 543–548. [DOI] [PubMed] [Google Scholar]
  • 19.Gentile S et al. (2016) Lipodystrophy in insulin-treated subjects and other injection-site skin reactions: Are we sure everything is clear? Diabetes Ther. 7 (3), 401–409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.McAdams BH and Rizvi AA (2016) An overview of insulin pumps and glucose sensors for the generalist. Journal of Clinical Medicine 5 (1), 5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Forlenza GP et al. (2018) Predictive low-glucose suspend reduces hypoglycemia in adults, adolescents, and children with type 1 diabetes in an at-home randomized crossover study: Results of the prolog trial. Diabetes Care 41 (10), 2155–2161. [DOI] [PubMed] [Google Scholar]
  • 22.Bergenstal RM et al. (2016) Safety of a hybrid closed-loop insulin delivery system in patients with type 1 diabetes. JAMA 316 (13), 1407–1408. [DOI] [PubMed] [Google Scholar]
  • 23.El-Khatib FH et al. (2017) Home use of a bihormonal bionic pancreas versus insulin pump therapy in adults with type 1 diabetes: A multicentre randomised crossover trial. Lancet 389 (10067), 368–368. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Selam JL (2005) Inhaled insulin for the treatment of diabetes: Projects and devices. Expert Opin. Pharmacother. 4 (8), 1373–1377. [DOI] [PubMed] [Google Scholar]
  • 25.Son YJ and McConville JT (2008) Advancements in dry powder delivery to the lung. Drug Dev. Ind. Pharm. 34 (9), 948–959. [DOI] [PubMed] [Google Scholar]
  • 26.Bailey CJ and Barnett AH (2007) Why is exubera being withdrawn? BMJ 335 (7630), 1156–1156. [Google Scholar]
  • 27.Oleck J et al. (2016) Commentary: Why was inhaled insulin a failure in the market? Diabetes Spectr. 29 (3), 180–184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Zijlstra E et al. (2019) 1085-p: Dance 501 inhaled human insulin (inh): Linear dose response, earlier onset of action, and higher early effect than s.C. Insulin lispro (lis). Diabetes 68 (Supplement 1), 1085–p. [Google Scholar]
  • 29.Powers MA and Marrero DG (2016) Diabetes self-management education and support in type 2 diabetes: A joint position statement of the american diabetes association, the american association of diabetes educators, and the academy of nutrition and dietetics. Diabetes Care 39 (1), E17–E17. [DOI] [PubMed] [Google Scholar]
  • 30.Lassmann-Vague V and Raccah D (2006) Alternatives routes of insulin delivery. Diabetes Metab. 32 (5 Pt 2), 513–22. [DOI] [PubMed] [Google Scholar]
  • 31.Pandey M et al. (2018) Recent updates on novel approaches in insulin drug delivery: A review of challenges and pharmaceutical implications. Curr. Drug Targets 19 (15), 1782–1800. [DOI] [PubMed] [Google Scholar]
  • 32.Heinemann L et al. (2001) Alternative routes of administration as an approach to improve insulin therapy: Update on dermal, oral, nasal and pulmonary insulin delivery. Curr. Pharm. Des. 7 (14), 1327–1351. [DOI] [PubMed] [Google Scholar]
  • 33.Lee YC et al. (2002) Review on the systemic delivery of insulin via the ocular route. Int. J. Pharm. 233 (1–2), 1–18. [DOI] [PubMed] [Google Scholar]
  • 34.Nazar H and Tsibouklis J (2012) Towards the nasal delivery of insulin. Ther. Deliv. 3 (11), 1241–3. [DOI] [PubMed] [Google Scholar]
  • 35.Djupesland PG (2013) Nasal drug delivery devices: Characteristics and performance in a clinical perspective-a review. Drug Delivery Transl. Res. 3 (1), 42–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Banerjee A et al. (2018) Ionic liquids for oral insulin delivery. Proc. Natl. Acad. Sci. U. S. A. 115 (28), 7296–7301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Abramson A et al. (2019) An ingestible self-orienting system for oral delivery of macromolecules. Science 363 (6427), 611–615. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Abramson A et al. (2019) A luminal unfolding microneedle injector for oral delivery of macromolecules. Nat. Med. 25, 1512–1518. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Lee H et al. (2018) Device-assisted transdermal drug delivery. Adv. Drug Delivery Rev. 127, 35–45. [DOI] [PubMed] [Google Scholar]
  • 40.Christie CD and Hanzal RF (1931) Insulin absorption by the conjunctival membranes in rabbits. J. Clin. Invest. 10 (4), 787–793. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Xuan B et al. (2005) Alternative delivery of insulin via eye drops. Diabetes Technol. Ther. 7 (5), 695–8. [DOI] [PubMed] [Google Scholar]
  • 42.Hinchcliffe M and Illum L (1999) Intranasal insulin delivery and therapy. Adv. Drug Delivery Rev. 35 (2–3), 199–234. [DOI] [PubMed] [Google Scholar]
  • 43.Bernstein G (2006) Buccal delivery of insulin: The time is now. Drug Dev. Res. 67 (7), 597–599. [Google Scholar]
  • 44.Crane CW and Luntz GR (1968) Absorption of insulin from the human small intestine. Diabetes 17 (10), 625–7. [DOI] [PubMed] [Google Scholar]
  • 45.Gedawy A et al. (2018) Oral insulin delivery: Existing barriers and current counter-strategies. J. Pharm. Pharmacol. 70 (2), 197–213. [DOI] [PubMed] [Google Scholar]
  • 46.Zhang Y et al. (2019) Advances in transdermal insulin delivery. Adv. Drug Delivery Rev. 139, 51–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Karande P et al. (2004) Discovery of transdermal penetration enhancers by high-throughput screening. Nat. Biotechnol. 22 (2), 192–197. [DOI] [PubMed] [Google Scholar]
  • 48.Ongpipattanakul B et al. (1991) Evidence that oleic-acid exists in a separate phase within stratum-corneum lipids. Pharm. Res. 8 (3), 350–354. [DOI] [PubMed] [Google Scholar]
  • 49.An YH et al. (2020) Recent advances in the transdermal delivery of protein therapeutics with a combinatorial system of chemical adjuvants and physical penetration enhancements. Advanced Therapeutics 3 (2), 1900116. [Google Scholar]
  • 50.Mitragotri S and Kost J (2004) Low-frequency sonophoresis: A review. Adv. Drug Delivery Rev. 56 (5), 589–601. [DOI] [PubMed] [Google Scholar]
  • 51.Yu J et al. (2020) Glucose-responsive insulin patch for the regulation of blood glucose in mice and minipigs. Nat. Biomed. Eng. 4 (5), 499–506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Jin X et al. (2018) Insulin delivery systems combined with microneedle technology. Adv. Drug Delivery Rev. 127, 119–137. [DOI] [PubMed] [Google Scholar]
  • 53.Kanikkannan N (2002) Iontophoresis-based transdermal delivery systems. Biodrugs 16 (5), 339–47. [DOI] [PubMed] [Google Scholar]
  • 54.Prausnitz MR et al. (2004) Current status and future potential of transdermal drug delivery. Nat. Rev. Drug Discov. 3 (2), 115–24. [DOI] [PubMed] [Google Scholar]
  • 55.Rege NK et al. (2017) Development of glucose-responsive ‘smart’ insulin systems. Current Opinion in Endocrinology & Diabetes and Obesity 24 (4), 267–278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Trevitt S et al. (2016) Artificial pancreas device systems for the closed-loop control of type 1 diabetes: What systems are in development? J. Diabetes Sci. Technol. 10 (3), 714–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Long MT et al. (2019) Perioperative considerations for evolving artificial pancreas devices. Anesth. Analg. 128 (5), 902–906. [DOI] [PubMed] [Google Scholar]
  • 58.Bequette BW (2013) Algorithms for a closed-loop artificial pancreas: The case for model predictive control. J. Diabetes Sci. Technol. 7 (6), 1632–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.American Diabetes, A. (2020) 7. Diabetes technology: Standards of medical care in diabetes-2020. Diabetes Care 43 (Suppl 1), S77–S88. [DOI] [PubMed] [Google Scholar]
  • 60.Smalley E (2016) Medtronic automated insulin delivery device gets fda nod. Nat. Biotechnol. 34 (12), 1220–1220. [DOI] [PubMed] [Google Scholar]
  • 61.Forlenza GP et al. (2019) Successful at-home use of the tandem control-iq artificial pancreas system in young children during a randomized controlled trial. Diabetes Technol. Ther. 21 (4), 159–169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Peters TM and Haidar A (2018) Dual-hormone artificial pancreas: Benefits and limitations compared with single-hormone systems. Diabet. Med. 35 (4), 450–459. [DOI] [PubMed] [Google Scholar]
  • 63.Bothe MK et al. (2013) The use of reinforcement learning algorithms to meet the challenges of an artificial pancreas. Expert Rev. Med. Devices 10 (5), 661–673. [DOI] [PubMed] [Google Scholar]
  • 64.Bertachi A et al. (2018) Automated blood glucose control in type 1 diabetes: A review of progress and challenges. Endocrinologia Diabetes Y Nutricion 65 (3), 172–181. [DOI] [PubMed] [Google Scholar]
  • 65.Bailey TS et al. (2015) Clinical accuracy of a continuous glucose monitoring system with an advanced algorithm. J. Diabetes Sci. Technol. 9 (2), 209–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Herrero P et al. (2017) Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra- day variability. Comput. Methods Programs Biomed. 146, 125–131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Wang J et al. (2019) Glucose-responsive insulin and delivery systems: Innovation and translation. Adv. Mater, e1902004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Yang JH and Cao ZQ (2017) Glucose-responsive insulin release: Analysis of mechanisms, formulations, and evaluation criteria. J. Controlled Release 263, 231–239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Bankar SB et al. (2009) Glucose oxidase--an overview. Biotechnol. Adv. 27 (4), 489–501. [DOI] [PubMed] [Google Scholar]
  • 70.Sharon N and Lis H (1972) Lectins: Cell-agglutinating and sugar-specific proteins. Science 177 (4053), 949–59. [DOI] [PubMed] [Google Scholar]
  • 71.Nakatsuka N et al. (2018) Aptamer-field-effect transistors overcome debye length limitations for small-molecule sensing. Science 362 (6412), 319–324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.VandenBerg MA and Webber MJ (2019) Biologically inspired and chemically derived methods for glucose-responsive insulin therapy. Adv. Healthcare Mater. 8 (12), e1801466. [DOI] [PubMed] [Google Scholar]
  • 73.Chou DHC et al. (2015) Glucose-responsive insulin activity by covalent modification with aliphatic phenylboronic acid conjugates. Proc. Natl. Acad. Sci. U. S. A. 112 (8), 2401–2406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74.Qiu Y and Park K (2001) Environment-sensitive hydrogels for drug delivery. Adv. Drug Delivery Rev. 53 (3), 321–39. [DOI] [PubMed] [Google Scholar]
  • 75.Volpatti LR et al. (2020) Glucose-responsive nanoparticles for rapid and extended self-regulated insulin delivery. ACS Nano 14 (1), 488–497. [DOI] [PubMed] [Google Scholar]
  • 76.Shen D et al. (2020) Recent progress in design and preparation of glucose-responsive insulin delivery systems. J. Controlled Release 321, 236–258. [DOI] [PubMed] [Google Scholar]
  • 77.Zhang YQ et al. (2018) Bioresponsive microneedles with a sheath structure for h2o2 and ph cascade-triggered insulin delivery. Small 14 (14). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.Witkowska Nery E et al. (2016) Electrochemical glucose sensing: Is there still room for improvement? Anal. Chem. 88 (23), 11271–11282. [DOI] [PubMed] [Google Scholar]
  • 79.Bruen D et al. (2017) Glucose sensing for diabetes monitoring: Recent developments. Sensors 17 (8), 1866. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Lan T et al. (2016) Transforming the blood glucose meter into a general healthcare meter for in vitro diagnostics in mobile health. Biotechnol. Adv. 34 (3), 331–341. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.Willner B et al. (2006) Electrical contacting of redox proteins by nanotechnological means. Curr. Opin. Biotechnol. 17 (6), 589–596. [DOI] [PubMed] [Google Scholar]
  • 82.Kim MY and Kim J (2017) Chitosan microgels embedded with catalase nanozyme-loaded mesocellular silica foam for glucose-responsive drug delivery. ACS Biomater. Sci. Eng. 3 (4), 572–578. [DOI] [PubMed] [Google Scholar]
  • 83.Harris JM et al. (2013) Common causes of glucose oxidase instability in in vivo biosensing: A brief review. J. Diabetes Sci. Technol. 7 (4), 1030–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84.Pramudya I and Chung HY (2019) Recent progress of glycopolymer synthesis for biomedical applications. Biomater. Sci. 7 (12), 4848–4872. [DOI] [PubMed] [Google Scholar]
  • 85.Burek M and Wandzik I (2018) Synthetic hydrogels with covalently incorporated saccharides studied for biomedical applications-15 year overview. Polymer Reviews 58 (3), 537–586. [Google Scholar]
  • 86.Ballerstadt R et al. (2006) Concanavalin a for in vivo glucose sensing: A biotoxicity review. Biosens. Bioelectron. 22 (2), 275–284. [DOI] [PubMed] [Google Scholar]
  • 87.Rege NK et al. (2017) Development of glucose-responsive ‘smart’ insulin systems. Curr. Opin. Endocrinol. Diabetes Obes. 24 (4), 267–278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 88.Tromans RA et al. (2019) A biomimetic receptor for glucose. Nat. Chem. 11 (1), 52–56. [DOI] [PubMed] [Google Scholar]
  • 89.Wu WT and Zhou SQ (2013) Responsive materials for self-regulated insulin delivery. Macromol. Biosci. 13 (11), 1464–1477. [DOI] [PubMed] [Google Scholar]
  • 90.Mansoor S et al. (2019) Polymer-based nanoparticle strategies for insulin delivery. Polymers 11 (9), 1380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91.Nakatsuka N et al. (2018) Aptamer–field-effect transistors overcome debye length limitations for small-molecule sensing. Science 362 (6412), 319–324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92.VandenBerg MA and Webber MJ (2019) Biologically inspired and chemically derived methods for glucose-responsive insulin therapy. Adv Healthc Mater 8 (12), e1801466. [DOI] [PubMed] [Google Scholar]
  • 93.Antonio JPM et al. (2019) Boronic acids as building blocks for the construction of therapeutically useful bioconjugates. Chem. Soc. Rev. 48 (13), 3513–3536. [DOI] [PubMed] [Google Scholar]
  • 94.Mo R et al. (2014) Emerging micro-and nanotechnology based synthetic approaches for insulin delivery. Chem. Soc. Rev. 43 (10), 3595–3629. [DOI] [PubMed] [Google Scholar]
  • 95.Huang Q et al. (2019) Advances in phenylboronic acid-based closed-loop smart drug delivery system for diabetic therapy. J. Controlled Release 305, 50–64. [DOI] [PubMed] [Google Scholar]
  • 96.Cros MR (2016) Glucose-responsive insulin delivery systems. Endocrinol. Nutr. 63 (4), 143–144. [DOI] [PubMed] [Google Scholar]
  • 97.Wang C et al. (2019) Recent advances in phenylboronic acid-based gels with potential for self-regulated drug delivery. Molecules 24 (6), 1089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 98.Yang J and Cao Z (2017) Glucose-responsive insulin release: Analysis of mechanisms, formulations, and evaluation criteria. J. Control. Release 263, 231–239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99.Ito Y and Imanishi Y (1994) Protein device for glucose-sensitive release of insulin. Acs Sym Ser 545, 47–54. [Google Scholar]
  • 100.Brownlee M and Cerami A (1979) A glucose-controlled insulin-delivery system: Semisynthetic insulin bound to lectin. Science 206 (4423), 1190–1. [DOI] [PubMed] [Google Scholar]
  • 101.Hoeg-Jensen T et al. (2005) Reversible insulin self-assembly under carbohydrate control. J. Am. Chem. Soc. 127 (17), 6158–9. [DOI] [PubMed] [Google Scholar]
  • 102.Ito Y and Imanishi Y (1994) Protein device for glucose-sensitive release of insulin. ACS Symp. Ser. 545, 47–54. [Google Scholar]
  • 103.Hoeg-Jensen T et al. (2005) Insulins with built-in glucose sensors for glucose responsive insulin release. J. Pept. Sci. 11 (6), 339–346. [DOI] [PubMed] [Google Scholar]
  • 104.Kaarsholm NC et al. (2018) Engineering glucose responsiveness into insulin. Diabetes 67 (2), 299–308. [DOI] [PubMed] [Google Scholar]
  • 105.Wang J et al. (2019) Glucose transporter inhibitor-conjugated insulin mitigates hypoglycemia. Proc. Natl. Acad. Sci. U. S. A. 116 (22), 10744–10748. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 106.Wang J et al. (2019) A forskolin-conjugated insulin analog targeting endogenous glucose-transporter for glucose-responsive insulin delivery. Biomater. Sci. 7 (11), 4508–4513. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107.Wang C et al. (2017) Red blood cells for glucose-responsive insulin delivery. Adv. Mater. 29 (18). [DOI] [PubMed] [Google Scholar]
  • 108.Yin J and Luan S (2016) Opportunities and challenges for the development of polymer-based biomaterials and medical devices. Regener. Biomater. 3 (2), 129–135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 109.Bally L et al. (2017) Finding the right route for insulin delivery - an overview of implantable pump therapy. Expert Opin. Drug Delivery 14 (9), 1103–1111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 110.Guo X and Wang W (2017) Challenges and recent advances in the subcutaneous delivery of insulin. Expert Opin. Drug Delivery 14 (6), 727–734. [DOI] [PubMed] [Google Scholar]
  • 111.Easa N et al. (2019) A review of non-invasive insulin delivery systems for diabetes therapy in clinical trials over the past decade. Drug Discov. Today 24 (2), 440–451. [DOI] [PubMed] [Google Scholar]
  • 112.Cefalu WT (2004) Concept, strategies, and feasibility of noninvasive insulin delivery. Diabetes Care 27 (1), 239–246. [DOI] [PubMed] [Google Scholar]
  • 113.Contreras I and Vehi J (2018) Artificial intelligence for diabetes management and decision support: Literature review. J. Med. Internet Res. 20 (5), e10775. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 114.Yu JC et al. (2017) Insulin-responsive glucagon delivery for prevention of hypoglycemia. Small 13 (19), 1603028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 115.Cheng Y et al. (2019) Cold-responsive nanocapsules enable the sole-cryoprotectant-trehalose cryopreservation of beta cell-laden hydrogels for diabetes treatment. Small 15 (50), e1904290. [DOI] [PubMed] [Google Scholar]
  • 116.Chen Z et al. (2018) Synthetic beta cells for fusion-mediated dynamic insulin secretion. Nat. Chem. Biol. 14 (1), 86–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 117.Ye YQ et al. (2016) Microneedles integrated with pancreatic cells and synthetic glucose-signal amplifiers for smart insulin delivery. Adv. Mater. 28 (16), 3115–3121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 118.Patton J (2006) Pulmonary delivery of insulin. Curr. Med. Res. Opin. 22, S5–S11.16914071 [Google Scholar]
  • 119.Lee YC and Yalkowsky SH (1999) Systemic absorption of insulin from a gelfoam (r) ocular device. Int. J. Pharm. 190 (1), 35–40. [DOI] [PubMed] [Google Scholar]
  • 120.Heinemann L and Jacques Y (2009) Oral insulin and buccal insulin: A critical reappraisal. J. Diabetes Sci. Technol. 3 (3), 568–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 121.Bernstein G (2008) Delivery of insulin to the buccal mucosa utilizing the rapidmist system. Expert Opin Drug Deliv 5 (9), 1047–55. [DOI] [PubMed] [Google Scholar]

RESOURCES