Digital Twins in Health: A Cross-Cutting Framework for Translational Research

Axe 1 du réseau HR2S

Abstract:

Solutions powered by artificial intelligence enable the analysis and simulation of large-scale data across multiple scales, from the cellular level to the organ and even the functional level. Following an initial development phase focused on data analysis and processing, the integration of fundamental principles of automatic control and signal processing allows for the integration of tools for identifying and simulating models based on measurements associated with uncertainties and mathematical models. This symposium will explore various digital twin models, including empirical, learned, and parametric models. The specific aspects of clinical research prior to the development of digital twins are also expected to be addressed, particularly regarding clinical applications and data production. Furthermore, digital twins also play a key role in industrial development, especially in the pharmaceutical sector, where they enable the simulation and optimization of manufacturing processes. Their growth is accompanied by increasing educational applications, notably through immersive environments integrated into training programs. They are thus contributing to the transformation of industrial and educational practices in pharmacy, demonstrating a major interest in healthcare from research to industrialization. Complementing these digital approaches, the issue of digital twins is intrinsically linked to that of the acquisition, use, and sharing of healthcare databases, with the questions raised at the French and European levels by the GDPR. However, this framework was not specifically designed for digital twins; it only partially covers a tool that addresses numerous legal areas: digital law, personal data protection law, intellectual property law, and healthcare liability law, to name a few. The symposium will address these issues in order to identify the needs in terms of legal proposals in light of the latest advances, as well as the questions of digital and clinical research raised by meeting current and future legal constraints. The complexity of validating and personalizing digital twins in healthcare leads to numerous issues regarding the socio-economic valuation of these tools. In addition, work is also expected on sharing the value of data from European hospitals for model production. Presentations addressing these issues are also anticipated.

Keywords: digital twin, digital health, AI for health, identification, simulation, modeling, metrology, machine learning, law, silver economy, management