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<p>Rare diseases affect over 300 million people worldwide and pose unique research challenges. In silico approaches, such as mechanistic models, machine learning, and simulations, offer scalable tools for disease characterisation, drug discovery, and virtual trials. This review categorises these methods by context of use, critically appraises their strengths and limitations, and identifies barriers to translation, highlighting key opportunities and ongoing challenges in advancing computational strategies for rare disease research.</p>

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Advancing the frontier of rare disease modeling: a critical appraisal of in silico technologies

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月17日

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  • Francesca Pistollato,
  • Fabia Furtmann,
  • Lindsay J. Marshall,
  • Surat Parvatam,
  • Jan Turner,
  • Flora Tshinanu Musuamba,
  • Giulia Russo,
  • Francesco Pappalardo

摘要

Rare diseases affect over 300 million people worldwide and pose unique research challenges. In silico approaches, such as mechanistic models, machine learning, and simulations, offer scalable tools for disease characterisation, drug discovery, and virtual trials. This review categorises these methods by context of use, critically appraises their strengths and limitations, and identifies barriers to translation, highlighting key opportunities and ongoing challenges in advancing computational strategies for rare disease research.