Digital patient twins (DPTs) are virtual models of patients that integrate data from wearables, genetic information, and medical records to enable personalized therapeutics and pharmaceutical manufacturing. This review discusses the potential of DPTs in improving health monitoring, facilitating personalized medicine, and enhancing pharmaceutical processes. DPTs can simulate individual patient responses to drugs, support precision medicine, and guide the development of individualized therapies. However, challenges remain in terms of data integration, regulatory approval, and scalability. The review highlights the importance of digital twins in bridging health monitoring, personalized medicine, and pharmaceutical manufacturing, while also addressing regulatory and ethical considerations. DPTs have the potential to revolutionize healthcare by enabling more accurate diagnoses, personalized treatments, and improved drug development. Despite their promise, issues such as data security, regulatory compliance, and the need for robust AI algorithms must be addressed to fully realize the benefits of DPTs in healthcare. The integration of DPTs into healthcare systems requires collaboration across multiple domains, including data science, regulatory frameworks, and clinical practice. The review emphasizes the need for further research and development to overcome existing limitations and fully harness the potential of DPTs in transforming healthcare.Digital patient twins (DPTs) are virtual models of patients that integrate data from wearables, genetic information, and medical records to enable personalized therapeutics and pharmaceutical manufacturing. This review discusses the potential of DPTs in improving health monitoring, facilitating personalized medicine, and enhancing pharmaceutical processes. DPTs can simulate individual patient responses to drugs, support precision medicine, and guide the development of individualized therapies. However, challenges remain in terms of data integration, regulatory approval, and scalability. The review highlights the importance of digital twins in bridging health monitoring, personalized medicine, and pharmaceutical manufacturing, while also addressing regulatory and ethical considerations. DPTs have the potential to revolutionize healthcare by enabling more accurate diagnoses, personalized treatments, and improved drug development. Despite their promise, issues such as data security, regulatory compliance, and the need for robust AI algorithms must be addressed to fully realize the benefits of DPTs in healthcare. The integration of DPTs into healthcare systems requires collaboration across multiple domains, including data science, regulatory frameworks, and clinical practice. The review emphasizes the need for further research and development to overcome existing limitations and fully harness the potential of DPTs in transforming healthcare.