Towards Human Digital Twin in Healthcare Technical, Legal, and Ethical Implications

Background: The clinical deployment of the Human Digital Twin (HDT) could bring huge benefits for patients, doctors, insurance, and other stakeholders of the healthcare system. Due to the complex and novel nature of the technologies involved in deploying an HDT, assessing the social and ethical implications of HDT along with the technical implementation is critical in order to properly evaluate the current and future state of deployment. Although these aspects have been examined in isolation, a combinatory approach is deemed vital in evaluating the transfer of HDT from theoretical and experimental research to real-world applications.
Objective: This work aims to provide a holistic overview of the technical, legal, and ethical aspects of HDT development and deployment.
Methods: Expert interviews were found to be an effective method to assess the current and future state of HDT development, as professionals in the field of medical informatics research, quality management, medical innovation, and personalized medicine have actively delved into relevant cases and aspects of this technology. The results generated through the interviews are analyzed by employing open, deductive, and axial coding techniques.
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Results: Reflection upon the categorized results provides valuable insights into the examined implications of HDT technology. The interconnectiveness of the different areas becomes evident, as legal and ethical considerations are directly linked to the technical implementation of HDT. Furthermore, the use of advanced machine learning techniques, such as deep learning, may improve technical performance but it also creates significant regulatory barriers and ethical dangers due to the inherent lack of explainability.
Conclusion: Although the high importance of restrictions to prevent the abuse of HDT technology is established, the current regulatory framework in the EU and in particular in Germany is deemed overly restrictive, to a degree that it puts companies, research teams, and startups at a significant competitive disadvantage compared to their counterparts in the USA and in Asia. These insights contribute to a better understanding of HDT and its implementation while paving the way for more effective research approaches toward realistic, responsible, and effective real-world applications.