Challenges and opportunities for digital twins in precision medicine from a complex systems perspective on npj digital medicine
ISC director G. Caldarelli coauthored a perspective on npj Digital Medicine.
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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Precision medicine standard approach for digital twins. The framework relies on using large-scale heterogeneous data sources (pre-clinical, clinical, envir- onmental, lifestyle, etc.). This massive database can be used in sophisticated com- putational models (such as deep learning), while relying solely on statistical data analysis to construct a series of digitalized instances–the digital twins–of a patient, which can then be used to test one or more therapeutic strategies for clinical decision-making. Human body design by Freepck and osteocytes from Servier Medical Art (smart.servier.com).