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In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

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Standard

In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. / Paci, Michelangelo; Passini, Elisa; Klimas, Aleksandra; Severi, Stefano; Hyttinen, Jari; Rodriguez, Blanca; Entcheva, Emilia.

Computing in Cardiology 2018. 2018. (Computing in Cardiology; Vuosikerta 45).

Tutkimustuotosvertaisarvioitu

Harvard

Paci, M, Passini, E, Klimas, A, Severi, S, Hyttinen, J, Rodriguez, B & Entcheva, E 2018, In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. julkaisussa Computing in Cardiology 2018. Computing in Cardiology, Vuosikerta. 45, Maastricht, Alankomaat, 23/09/18. https://doi.org/10.22489/CinC.2018.086

APA

Paci, M., Passini, E., Klimas, A., Severi, S., Hyttinen, J., Rodriguez, B., & Entcheva, E. (2018). In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. teoksessa Computing in Cardiology 2018 (Computing in Cardiology; Vuosikerta 45). https://doi.org/10.22489/CinC.2018.086

Vancouver

Paci M, Passini E, Klimas A, Severi S, Hyttinen J, Rodriguez B et al. In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. julkaisussa Computing in Cardiology 2018. 2018. (Computing in Cardiology). https://doi.org/10.22489/CinC.2018.086

Author

Paci, Michelangelo ; Passini, Elisa ; Klimas, Aleksandra ; Severi, Stefano ; Hyttinen, Jari ; Rodriguez, Blanca ; Entcheva, Emilia. / In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. Computing in Cardiology 2018. 2018. (Computing in Cardiology).

Bibtex - Lataa

@inproceedings{93bbfe5af0af4aca97228fd4856704ec,
title = "In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes",
abstract = "All-optical high-throughput systems allow simultaneous high resolution action potential (AP) and Ca2+ transient (CaTr) measurements from cardiomyocytes within multicellular context, offering means to speed up in vitro drug tests. Here, we aim to develop experimentallyconstrained in silico models of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and hiPSC-CM populations to predict drug effects in humans, by leveraging functional data obtained by all-optical means. Using multi-objective genetic algorithms (MoGAs), we constructed three control populations of in silico hiPSC-CMs, constrained with experimental data of APs and CaTrs recorded at room temperature and non-paced conditions from three different plates containing hiPSCCM syncytia. We then simulated the effect of increasing doses of Diltiazem (130 models), Cisapride (200 models) and Astemizole (200 models) in the three populations, respectively. Comparing model predictions with the experimental drug administration (not used for the optimization/calibration of the populations) revealed good agreement with experiments: e.g. Diltiazem shortened APs while Astemizole and Cisapride prolonged APs.",
author = "Michelangelo Paci and Elisa Passini and Aleksandra Klimas and Stefano Severi and Jari Hyttinen and Blanca Rodriguez and Emilia Entcheva",
year = "2018",
doi = "10.22489/CinC.2018.086",
language = "English",
series = "Computing in Cardiology",
booktitle = "Computing in Cardiology 2018",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

AU - Paci, Michelangelo

AU - Passini, Elisa

AU - Klimas, Aleksandra

AU - Severi, Stefano

AU - Hyttinen, Jari

AU - Rodriguez, Blanca

AU - Entcheva, Emilia

PY - 2018

Y1 - 2018

N2 - All-optical high-throughput systems allow simultaneous high resolution action potential (AP) and Ca2+ transient (CaTr) measurements from cardiomyocytes within multicellular context, offering means to speed up in vitro drug tests. Here, we aim to develop experimentallyconstrained in silico models of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and hiPSC-CM populations to predict drug effects in humans, by leveraging functional data obtained by all-optical means. Using multi-objective genetic algorithms (MoGAs), we constructed three control populations of in silico hiPSC-CMs, constrained with experimental data of APs and CaTrs recorded at room temperature and non-paced conditions from three different plates containing hiPSCCM syncytia. We then simulated the effect of increasing doses of Diltiazem (130 models), Cisapride (200 models) and Astemizole (200 models) in the three populations, respectively. Comparing model predictions with the experimental drug administration (not used for the optimization/calibration of the populations) revealed good agreement with experiments: e.g. Diltiazem shortened APs while Astemizole and Cisapride prolonged APs.

AB - All-optical high-throughput systems allow simultaneous high resolution action potential (AP) and Ca2+ transient (CaTr) measurements from cardiomyocytes within multicellular context, offering means to speed up in vitro drug tests. Here, we aim to develop experimentallyconstrained in silico models of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and hiPSC-CM populations to predict drug effects in humans, by leveraging functional data obtained by all-optical means. Using multi-objective genetic algorithms (MoGAs), we constructed three control populations of in silico hiPSC-CMs, constrained with experimental data of APs and CaTrs recorded at room temperature and non-paced conditions from three different plates containing hiPSCCM syncytia. We then simulated the effect of increasing doses of Diltiazem (130 models), Cisapride (200 models) and Astemizole (200 models) in the three populations, respectively. Comparing model predictions with the experimental drug administration (not used for the optimization/calibration of the populations) revealed good agreement with experiments: e.g. Diltiazem shortened APs while Astemizole and Cisapride prolonged APs.

U2 - 10.22489/CinC.2018.086

DO - 10.22489/CinC.2018.086

M3 - Conference contribution

T3 - Computing in Cardiology

BT - Computing in Cardiology 2018

ER -