Combining experiments with mathematical modeling to predict drug responses across cell types

  • Gong, Jingqi J. (PI)

Project Details

Description

Emerging as a convenient, reliable source of heart cells, human induced pluripotent stem cell derived cardiac myocytes (hiPSC-CMs) have the potential to transform many aspects of drug development. However, the potential of these cells is currently limited by their physiological differences with human adult myocytes (hAMs), largely due to the 'immature' phenotype. This limitation of the hiPSC-CM system makes it difficult to know, in general, whether pharmacological experiments performed in hiPSC-CMs will be predictive of changes in adult physiology. We hypothesize that combining rigorous, quantitative physiology studies with innovative mathematical modeling approaches can overcome these limitations and enhance the potential of hiPSC-CMs in drug development. There are two specific aims in this project: (1) Develop and experimentally validate a statistical model that identifies drug-altered ion channel activities based on cellular physiological recordings. (2) Develop a mathematical modeling framework that predicts drug responses across cell types. In Aim 1 we will develop and experimentally validate a statistical model that can predict which ionic currents have been modified by a particular drug, on the basis of physiological measurements (APs and CaTs) from hiPSC-CMs. In Aim 2 we will build a new mathematical model that can quantitatively predict how drugs influence human adult cardiac myocytes based on recordings from hiPSC-CMs. Taken together, the proposed research addresses the limitation of hiPSC-CMs and the challenge of translating drug responses across cell types, through combining physiological experiments with mathematical modeling approaches. In addition to being conceptually novel, the practical consequences of the proposed research can potentially improve drug development. (AHA Program: Predoctoral Fellowship)

StatusFinished
Effective start/end date1/07/1730/06/19

Funding

  • American Heart Association: $54,000.00

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