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In this article, we introduce a novel approach to solving parameterized models of cardiac action potentials (CAPs) by combining meta-learning techniques with systems biology-informed neural networks (SBINNs). The proposed method, hyperSBINN, effectively addresses the challenge of predicting the effects of various compounds at different concentrations on CAPs, outperforming traditional differential equation solvers in speed. Our model efficiently handles scenarios with limited data and complex parameterized differential equations. The hyperSBINN model demonstrates robust performance in predicting APD90 values, indicating its potential as a reliable tool for modeling cardiac electrophysiology and aiding in preclinical drug development. This framework represents an advancement in computational modeling, offering a scalable and efficient solution for simulating and understanding complex biological systems.<\/jats:p>","DOI":"10.1177\/15578666251410587","type":"journal-article","created":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T13:51:49Z","timestamp":1769781109000},"page":"281-300","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment"],"prefix":"10.1177","volume":"33","author":[{"given":"Inass","family":"Soukarieh","sequence":"first","affiliation":[{"name":"Sanofi, Digital R&amp;D, Vitry-Sur-Seine, France."},{"name":"Universit\u00e9 Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, Paris, France."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gerhard","family":"Hessler","sequence":"additional","affiliation":[{"name":"Sanofi, R&amp;D Preclinical Safety, Industriepark Hoechst, Frankfurt am Main, Germany."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Herv\u00e9","family":"Minoux","sequence":"additional","affiliation":[{"name":"Sanofi, Digital R&amp;D, Vitry-Sur-Seine, France."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcel","family":"Mohr","sequence":"additional","affiliation":[{"name":"Sanofi, R&amp;D Preclinical Safety, Industriepark Hoechst, Frankfurt am Main, Germany."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Friedemann","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Sanofi, R&amp;D Preclinical Safety, Industriepark Hoechst, Frankfurt am Main, Germany."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Wenzel","sequence":"additional","affiliation":[{"name":"Sanofi, R&amp;D Preclinical Safety, Industriepark Hoechst, Frankfurt am Main, Germany."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre","family":"Barbillon","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, Paris, France."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hugo","family":"Gangloff","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, Paris, France."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre","family":"Gloaguen","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Bretagne Sud, UMR CNRS 6205, LMBA, Vannes, France."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,1,30]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-019-0193-y"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/0960-0779(95)00089-5"},{"key":"e_1_3_3_4_1","article-title":"Cardiac transmembrane ion channels and action potentials: Cellular physiology and arrhythmogenic behavior","author":"Andr\u00e1s V","year":"2021","unstructured":"Andr\u00e1s V, , Tomek J, , Nagy N, et al. 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