A predictive computational platform for optimizing the design of bioartificial pancreas devices.

ABSTRACT: The delivery of encapsulated islets or stem cell-derived insulin-producing cells (i.e., bioartificial pancreas devices) may achieve a functional cure for type 1 diabetes, but their efficacy is limited by mass transport constraints. Modeling such constraints is thus desirable, but previous efforts invoke simplifications which limit the utility of their insights. Herein, we present a computational platform for investigating the therapeutic capacity of generic and user-programmable bioartificial pancreas devices, which accounts for highly influential stochastic properties including the size distribution and random localization of the cells. We first apply the platform in a study which finds that endogenous islet size distribution variance significantly influences device potency. Then we pursu

SUBMITTER: Ernst AU 

PROVIDER: S-EPMC9561707 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature