Presentation (CTI)

OBJECTIVES: Digital twins (DTs) are complex systems involving physical and virtual models which exchange information in real time. DTs are already used widely in the manufacturing, aerospace, and automobile industries. This research aimed to identify the current and potential uses of DTs in the healthcare and pharmaceutical industries.
METHODS: A targeted literature review was conducted to identify current and potential uses of DTs in healthcare. Google and PubMed were searched to identify relevant published and grey literature. Searches used combinations of the term “digital twins” with “healthcare”, “health” and “pharma”. Categories of DT use reported in literature were identified.
RESULTS: Within the last five years, the concept of digital twins has been increasingly explored and the market value is increasing. DTs could be used to model the body or diseases to improve diagnosis and personalize treatment. DTs also have the potential to optimize the organization and efficiency of healthcare systems. Currently, the most prominent area of application is in clinical trials through simulating patient responses to treatment and in supporting patient identification for recruitment, but regulatory guidance is lacking.
CONCLUSIONS: DTs have the potential to revolutionize the pharmaceutical and healthcare industries, resulting in better health outcomes for patients. However, excitement over innovation must be weighed against costs, the complexities of the human body, and inherent data quality issues. How payers will consider the use of DTs in clinical trials during HTA is unclear and creates more questions than solutions.