약물 안전성을 위한 심근세포 계산 모델의 가능성

  • role: Corresponding author, First author通信作者, 第一作者
  • Affiliation:

    Beijing National Center for Applied Mathematics, Capital Normal University, Beijing 100048, China

  • Email:lei.wang@cnu.edu.cn
  • Introduction:* Lei Wang lei.wang@cnu.edu.cn
Lei Wang1*,  
  • Affiliation:

    Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK

Blanca Rodriguez2

추상적인

키워드

심근세포 계산 모델;약물 안전성 테스트;심장 전기생리학;인 실리코 임상 시험;인공지능 (AI)

References

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    Tomek J, Bueno-Orovio A, Passini E, Zhou X, Minchole A, Britton O, et al. Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block. Elife. 2019;8:e48890.
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    Passini E, Zhou X, Trovato C, Britton OJ, Bueno-Orovio A, Rodriguez B. The virtual assay software for human in silico drug trials to augment drug cardiac testing. J Comput Sci. 2020;45:101163.
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    Serrano R, Feyen DA, Bruyneel AA, Hnatiuk AP, Vu MM, Amatya PL, et al. A deep learning platform to assess drug proarrhythmia risk. Cell Stem Cell.2023;30(1):86-95.e4.
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    Sahli-Costabal F, Seo K, Ashley E, Kuhl E. Classifying drugs by their arrhythmogenic risk using machine learning. Biophys J.2020;118(5):1165–76.
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    Tang X, Yu Z, Chen J, Cui Y, Shao D, Wang W, et al. CellForge: agentic design of virtual cell models. arXiv: 2508.02276 [Preprint]. 2025
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    Bremner SB, Gaffney KS, Sniadecki NJ, Mack DL. A change of heart:human cardiac tissue engineering as a platform for drug development. Curr Cardiol Rep. 2022;24(5):473–86.

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