Rational Design and Efficacy of Glucose‐Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models
Name
nihms-1915464.pdf
Description
Accepted version
Size
2.36 MB
Format
Adobe PDF
Checksum (MD5)
6f44024cc8813a7eff4fc059b8b3abc7
Author(s)
Yang, Sungyun
Yang, Jing Fan
Gong, Xun
Weiss, Michael A
Strano, Michael S
Date Issued
June 15, 2023
Journal
Advanced Healthcare Materials
Publisher
Wiley
Citation
Yang, Sungyun, Yang, Jing Fan, Gong, Xun, Weiss, Michael A and Strano, Michael S. 2023. "Rational Design and Efficacy of Glucose‐Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models." Advanced Healthcare Materials, 12 (25).
Version
Author's final manuscript
Abstract
Glucose‐responsive insulins (GRIs) use plasma glucose levels in a diabetic patient to activate a specifically designed insulin analogue to a more potent state in real time. Alternatively, some GRI concepts use glucose‐mediated release or injection of insulin into the bloodstream. GRIs hold promise to exhibit much improved pharmacological control of the plasma glucose concentration, particularly for the problem of therapeutically induced hypoglycemia. Several innovative GRI schemes are introduced into the literature, but there remains a dearth of quantitative analysis to aid the development and optimization of these constructs into effective therapeutics. This work evaluates several classes of GRIs that are proposed using a pharmacokinetic model as previously described, PAMERAH, simulating the glucoregulatory system of humans and rodents. GRI concepts are grouped into three mechanistic classes: 1) intrinsic GRIs, 2) glucose‐responsive particles, and 3) glucose‐responsive devices. Each class is analyzed for optimal designs that maintain glucose levels within the euglycemic range. These derived GRI parameter spaces are then compared between rodents and humans, providing the differences in clinical translation success for each candidate. This work demonstrates a computational framework to evaluate the potential clinical translatability of existing glucose‐responsive systems, providing a useful approach for future GRI development.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
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Creative Commons Attribution-Noncommercial-ShareAlike
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DOI of Published Version
10.1002/adhm.202300587
