Engineering better treatments for diabetes : from next-gen insulin drugs to autonomous insulin delivery
Abstract/Contents
- Abstract
- Insulin was first isolated a century ago, yet commercial formulations of insulin and its analogues for hormone replacement therapy falls short of mimicking the endogenous glycemic control that occurs in non-diabetic individuals. Moreover, diabetes management is increasingly relying automated insulin delivery using closed-loop systems to improve glucose management and reduce patient burden. However improvements in insulin formulations, sensors, and algorithms are required to shift from hybrid systems to fully autonomous delivery. Insulin formulations that better mimic secretion from the beta-cells, by enabling more rapid insulin absorption kinetics and/or co-delivering complementary hormones (i.e. amylin), would improve diabetes management. However, formulation innovation is complicated by the poor stability of insulin monomers and amylin. During my time in the Appel lab, I have developed two polymeric excipient platforms (non-covalent PEGylation and amphiphilic copolymer excipients) that can be used to increase the stability of insulin in formulation. Using these designer excipients, I have developed three enhanced insulin formulations: (i) an ultrafast monomeric insulin lispro (ii) an insulin-amylin co-formulation and (iii) an ultra-stable insulin for improved global access. These three enhanced insulin formulations are promising candidates for improving glucose control and reducing burden for patients with diabetes. Beyond formulation engineering, through collaborations I have investigated the use of open-source algorithms in a full closed-loop setting as well as helped to develop a continuous real-time ELISA microfluidic device for continuous monitoring of insulin and glucose. Together, this collection of work describes the development of new technologies towards insulin delivery with the goal of improving glucose management in patients with diabetes.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Maikawa, Caitlin Laura |
|---|---|
| Degree supervisor | Appel, Eric (Eric Andrew) |
| Thesis advisor | Appel, Eric (Eric Andrew) |
| Thesis advisor | Cochran, Jennifer R |
| Thesis advisor | Maahs, David |
| Degree committee member | Cochran, Jennifer R |
| Degree committee member | Maahs, David |
| Associated with | Stanford University, Department of Bioengineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Caitlin L. Maikawa. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/zj411yx1243 |
Access conditions
- Copyright
- © 2021 by Caitlin Laura Maikawa
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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