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Abstract
Encapsulated islets or stem cell-derived insulin-producing cells in bioartificial pancreas (BAP) devices hold promise for treating type 1 diabetes, but their efficacy is hampered by mass transport limitations, particularly oxygen diffusion. This paper introduces SHARP, a computational platform using the stochastic finite element method to model oxygen transport and its impact on cell survival and insulin secretion in BAP devices, accounting for islet size distribution and random localization. The platform reveals the significant influence of islet size distribution variance on device potency. SHARP is then used to optimize device structures and estimate curative cell doses, leading to a new device-specific islet equivalence conversion table and a surrogate machine learning model (SHARP-ML) for rapid prediction of these coefficients.
Publisher
Nature Communications
Published On
Oct 13, 2022
Authors
Alexander U. Ernst, Long-Hai Wang, Scott C. Worland, Braulio A. Marfil-Garza, Xi Wang, Wanjun Liu, Alan Chiu, Tatsuya Kin, Doug O’Gorman, Scott Steinschneider, Ashim K. Datta, Klearchos K. Papas, A. M. James Shapiro, Minglin Ma
Tags
bioartificial pancreas
type 1 diabetes
oxygen transport
cell survival
insulin secretion
computational platform
stochastic finite element method
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