Digital Twins in Health Science: Transforming Personalized Medicine and Healthcare Systems

George Church^1*_, Thomas Tessa²

¹Department of Molecular and Cellular Biology, Harvard University, USA

²Stanford Center for Biomedical Informatics Research, Department of Medicine, USA

*Corresponding Author

George Church, Department of Molecular and Cellular Biology, Harvard University, USA. E-mail: George_church@gmail.com

Abstract

Digital twin technology, originally developed in the engineering and manufacturing sectors, has rapidly emerged as a transformative tool in health science. A digital twin in healthcare is a virtual replica of a patient, organ, or physiological system that continuously updates with real-time data to simulate, predict, and optimize health outcomes. By combining biomedical data, wearable technology, machine learning, and simulation models, digital twins can personalize treatment, enhance clinical decision-making, and streamline healthcare delivery. This article explores the concept of digital twins in health science, their applications, benefits, and challenges, and the future potential for precision medicine and public health.