Advancing the frontier of rare disease modeling: a critical appraisal of in silico technologies.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 41249457.
- Also identified by DOI 10.1038/s41746-025-02068-1 and PMC identifier 12623476.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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.