Parameters estimation approach for the MEA/hiPSC-CM asaays

• Main Authors: Bouyssier, Julien, Zemzemi, Nejib
• Format: Conference Proceeding
• Language: English
• Subjects: Computational modeling; Cost function; Drugs; Electric potential; Electrodes; Mathematical model; Stem cells
• ISSN: 2325-887X
• DOI: 10.22489/CinC.2017.063-126

We propose a mathematical approach for the analysis of drugs effects on the electrical activity of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) based on multi-electrode array (MEA) experiments. Our goal is to produce an in silico tool able to simulate drugs action in MEA/hiPSC-CM assays and to fit the drug model parameters to the experimental data. The electrical activity of the stem cells at the ion-channel level is modeled using the Paci et al. (2013) transmembrane potential model. We use the bidomain model in order to describe the propagation of the electrical wave in the stem cells preparation. The field potential (FP) measured by the MEA is modeled by the extracellular potential of the bidomain equations. First, we propose a strategy allowing to generate FPs in good agreement with the experimental data. Second, we introduce a drug/ion channels interaction based on a pore block model. Results show that the model reflects properly the main effects of the drug on the FP. In order to estimate the parameters of the drug model, we define a cost function minimizing the gap between the model and the observed FPs. We use an optimization algorithm based on a gradient descent method where the cost function gradient is computed using an adjoint approach. We generated field potential for the five drugs with fixed gold standard IC50 and drug dose values. Then, supposing that one of the gold standard parameters is not known and adding 10% gaussian noise, the algorithm is able to estimate this parameter with more than 95% of accuracy. This approach could also be used in the future to optimize drug doses in order to achieve desired therapeutic effects.