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<p>Digital twins (DTs) in precision medicine are increasingly viable, propelled by extensive data collection and advancements in artificial intelligence (AI), alongside traditional biomedical methodologies. We argue that including mechanistic simulations that produce behavior based on explicitly defined biological hypotheses and multiscale mechanisms is beneficial. It enables the exploration of diverse therapeutic strategies and supports dynamic clinical decision-making through insights from network science, quantitative biology, and digital medicine.</p>

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Challenges and opportunities for digital twins in precision medicine from a complex systems perspective

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月17日

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  • Manlio De Domenico,
  • Luca Allegri,
  • Guido Caldarelli,
  • Valeria d’Andrea,
  • Barbara Di Camillo,
  • Luis M. Rocha,
  • Jordan Rozum,
  • Riccardo Sbarbati,
  • Francesco Zambelli

摘要

Digital twins (DTs) in precision medicine are increasingly viable, propelled by extensive data collection and advancements in artificial intelligence (AI), alongside traditional biomedical methodologies. We argue that including mechanistic simulations that produce behavior based on explicitly defined biological hypotheses and multiscale mechanisms is beneficial. It enables the exploration of diverse therapeutic strategies and supports dynamic clinical decision-making through insights from network science, quantitative biology, and digital medicine.