Title: Synthesis of insulin pump controllers from safety specifications using Bayesian model validation

Authors: Sumit Kumar Jha; Raj Gautam Dutta; Christopher J. Langmead; Susmit Jha; Emily Sassano

Addresses: EECS Department, University of Central Florida, Orlando, FL 32816, USA ' EECS Department, University of Central Florida, Orlando, FL 32816, USA ' Computer Science Department and Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh PA, 15213, USA ' EECS Department, UC Berkeley, CA 94703, USA ' EECS Department, University of Central Florida, Orlando, FL 32816, USA

Abstract: Insulin pump controllers seek to alleviate the chronic suffering caused by diabetes that affects over 6% of the world population. The design of control laws for insulin pump controllers has been well studied. However, the parameters involved in the control law are difficult to synthesize. Traditionally, ad hoc approaches using animal models and random sampling have been used to construct these parameters. We suggest a synthesis algorithm that uses Bayesian statistical model validation to reduce the number of simulations needed. We apply this algorithm to the problem of insulin pump controller synthesis using in silico simulation of the glucose-insulin metabolism model.

Keywords: computational systems biology; diabetes; artificial pancreas; parameter synthesis; Bayesian models; statistical model checking; automated synthesis; insulin pump control; safety specifications; model validation; pump controllers; insulin pumps; simulation; bioinformatics; glucose-insulin metabolism.

DOI: 10.1504/IJBRA.2012.048964

International Journal of Bioinformatics Research and Applications, 2012 Vol.8 No.3/4, pp.263 - 285

Published online: 05 Dec 2014 *

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