Computational Medicine & Digital Twins Improving Medical Care
Novel medical technologies are being introduced at unprecedented rates, demanding scientific evidence of their safety and efficacy at an unprecedented pace to ensure patient safety and benefit. With success in both in-vitro/in-vivo studies, products are tested on clinical trials assessing use in humans. Predicting low-frequency side effects has been difficult because such side effects may not become apparent until many patients adopt the treatment. When medical devices fail at later stages, financial losses can be catastrophic. Testing on many people is costly, lengthy, and sometimes implausible (e.g. paediatric patients, rare diseases, and underrepresented or hard-to-reach ethnic groups).
Computational Medicine underpins In-silico trials (IST), i.e., computer-based trials of medical products performed on populations of digital twins (aka virtual patients). Computer models/simulations are used to conceive, develop, and assess devices with the intended clinical outcome explicitly optimised from the outset (a-priori) instead of tested on humans (a-posteriori). This will include testing for potential risks to patients (side effects) and exhaustively exploring medical device failure modes before being tested in human clinical trials. In-silico evidence is still consolidating but is poised to transform how health and life sciences R&D and regulations are conducted. UK can take a leadership position in in-silico trials, which would cement its position as a global leader in health and life sciences, help drive the UK economy and provide UK citizens with early access to innovative health products.
To see all forthcoming (and past) free lectures in Knowledge Miles: The 695th Lord Mayor’s Lecture series, please visit: https://www.knowledgemiles.net/