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

2025/01/17 by Manlio De Domenico, Luca Allegri, Guido Caldarelli +6 · 1 voice · 4 citations
Biochemistry, Genetics and Molecular Biology · Engineering · #Bioinformatics and Genomic Networks #Biomedical and Engineering Education #Genetics, Bioinformatics, and Biomedical Research

paper · pdf · doi:10.1038/s41746-024-01402-3

openalex publication_date 2025/01/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

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.

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