Drug discovery using iPS cells and in silico model

Human induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs) can recapitulate the properties of human cardiomyocyte and exhibit disease phenotypes in vitro, attributable to their healthy- or patient-specific genetic backgrounds. Therefore, hiPSC-CMs are a crucial tool for developing therapeutic agents for cardiovascular diseases, and regenerative medicine using hiPSC-CMs is expected to be an alternative therapy to heart transplantation. Moreover, the development of organoid models has been advanced to replicate the complex structure of heart tissue in vitro, thereby effectively facilitating drug discovery. On the other hand, current methods for advancing drug discovery using hiPSC-CMs face limitations, including the difficulty of quantifying characteristics such as cell structure and predicting the risk and efficacy of candidate drug in clinical practice. In the field of regenerative medicine, challenges include quality control and the verification of safety of transplanted cells in human. In silico model, including artificial intelligence (AI) and simulation, have been developed in the field of drug discovery using hiPSC-CMs. These advancements encompass phenotype scoring via AI and risk prediction through simulations. This review outlines the current status and challenges of drug discovery using hiPSC-CMs and in silico model, based on the published reports.

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Publication Details

Journal
Folia Pharmacologica Japonica
Published
2024-12-31
DOI
https://doi.org/10.1254/fpj.24046
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
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article

Drug discovery using iPS cells and in silico model

Yoshinori Yoshida, Yuya Fujiwara
Folia Pharmacologica Japonica
3D Printing in Biomedical Research
article

Drug discovery using iPS cells and in silico model

Yoshinori Yoshida, Yuya Fujiwara
article en

Abstract

Human induced pluripotent stem cells derived cardiomyocytes (hiPSC-CMs) can recapitulate the properties of human cardiomyocyte and exhibit disease phenotypes in vitro, attributable to their healthy- or patient-specific genetic backgrounds. Therefore, hiPSC-CMs are a crucial tool for developing therapeutic agents for cardiovascular diseases, and regenerative medicine using hiPSC-CMs is expected to be an alternative therapy to heart transplantation. Moreover, the development of organoid models has been advanced to replicate the complex structure of heart tissue in vitro, thereby effectively facilitating drug discovery. On the other hand, current methods for advancing drug discovery using hiPSC-CMs face limitations, including the difficulty of quantifying characteristics such as cell structure and predicting the risk and efficacy of candidate drug in clinical practice. In the field of regenerative medicine, challenges include quality control and the verification of safety of transplanted cells in human. In silico model, including artificial intelligence (AI) and simulation, have been developed in the field of drug discovery using hiPSC-CMs. These advancements encompass phenotype scoring via AI and risk prediction through simulations. This review outlines the current status and challenges of drug discovery using hiPSC-CMs and in silico model, based on the published reports.

Folia Pharmacologica JaponicaVol. 160(1)
Kyoto University (JP)
Openalex Percentile: Top 77%
3D Printing in Biomedical Research
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