Challenges and opportunities for digital twins in precision medicine from a complex systems perspective
Manlio De Domenico, Luca Allegri, Guido Caldarelli, Valeria d’Andrea, Barbara Di Camillo, Luís M. Rocha, Jordan C. Rozum, Riccardo Sbarbati, Francesco Zambelli
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.
Topics & Concepts
Perspective (graphical)Precision medicineData scienceComputer scienceMedicineArtificial intelligencePathologyBiomedical and Engineering EducationBioinformatics and Genomic NetworksGenetics, Bioinformatics, and Biomedical Research