Key result
An algorithm based on bidomain equations and an inverse problem strategy successfully deduced affected ion channels and provided accurate dose-response curves for four compounds from MEA signals.
A novel algorithm using bidomain equations and inverse problem strategy can automatically deduce ion channel effects from MEA signals in hiPSC-CMs, potentially improving safety pharmacology drug screening.
May enable automated MEA-hiPSC-CM analysis for drug screening; leaves open prospective validation before CiPA adoption.
OBJECTIVE: Multi electrodes arrays (MEAs) combined with cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CMs) can enable high- or medium-throughput drug screening in safety pharmacology. This technology has recently attracted a lot of attention, in particular from an international initiative named CiPA. But it is currently limited by the difficulty to analyze the measured signals. We propose a strategy to analyze the signals acquired by the MEA and to automatically deduce the channels affected by the drug. METHODS: Our method is based on the bidomain equations, a model for the MEA electrodes, and an inverse problem strategy. RESULTS: in silico MEA signals are obtained for two commercial devices and an example of early after depolarization is presented. Then, by processing real signals obtained for four different compounds, our algorithm was able to provide dose-response curves for potassium, sodium, and calcium channels. For ivabradine and moxifloxacin, the IC50 and dose-response curves are in very good agreement with known values. SIGNIFICANCE: The proposed strategy offers a possible answer to a major question raised by the community of safety pharmacology. By allowing a more automated analysis of the signals, our approach could contribute to promote the technology based on MEA and hiPSC-CMs and, therefore, improve reliability and efficiency of drug screening.
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Raphel et al. (2017) studied Safety pharmacology and drug screening. Algorithm based on bidomain equations and inverse problem strategy was evaluated on Dose-response curves for potassium, sodium, and calcium channels. An algorithm based on bidomain equations and an inverse problem strategy successfully deduced affected ion channels and provided accurate dose-response curves for four compounds from MEA signals.