The article "Digital Patient Twins for Personalized Therapeutics and Pharmaceutical Manufacturing" by Fischer, Volpert, Antonino, and Ahrens explores the potential and limitations of digital patient twins (DPTs) in healthcare and pharmaceutical manufacturing. DPTs are virtual models of patients that integrate various health data, including real-time feedback from wearables, to enable personalized therapeutics and improve health monitoring. The authors highlight the growing impact of data science and artificial intelligence on health data ecosystems, which could lead to more precise and efficient healthcare solutions. However, the utility and feasibility of DPTs in routine medical processes are still limited, and reliable simulations for predicting individual drug responses are lacking. Additionally, individualized pharmaceutical manufacturing faces challenges such as low automation, scalability, and high costs, along with regulatory hurdles. The article discusses the regulatory aspects and the need for more digitalization in the pharmaceutical industry. It also emphasizes the importance of data control, security, and sovereignty in the context of DPTs. Overall, the authors argue that DPTs have the potential to revolutionize healthcare by improving diagnosis, treatment, and patient care, but they need to overcome several technical and regulatory challenges to fully realize their potential.The article "Digital Patient Twins for Personalized Therapeutics and Pharmaceutical Manufacturing" by Fischer, Volpert, Antonino, and Ahrens explores the potential and limitations of digital patient twins (DPTs) in healthcare and pharmaceutical manufacturing. DPTs are virtual models of patients that integrate various health data, including real-time feedback from wearables, to enable personalized therapeutics and improve health monitoring. The authors highlight the growing impact of data science and artificial intelligence on health data ecosystems, which could lead to more precise and efficient healthcare solutions. However, the utility and feasibility of DPTs in routine medical processes are still limited, and reliable simulations for predicting individual drug responses are lacking. Additionally, individualized pharmaceutical manufacturing faces challenges such as low automation, scalability, and high costs, along with regulatory hurdles. The article discusses the regulatory aspects and the need for more digitalization in the pharmaceutical industry. It also emphasizes the importance of data control, security, and sovereignty in the context of DPTs. Overall, the authors argue that DPTs have the potential to revolutionize healthcare by improving diagnosis, treatment, and patient care, but they need to overcome several technical and regulatory challenges to fully realize their potential.