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From models to medicine: The promise and challenges of computational biomechanics

Hosted by Chemical Engineering and Biotechnology

Wednesday 11 November 2026, 13:30

Venue time (London)

Lecture Theatre 2, Department of Chemical Engineering and Biotechnology, West Cambridge Site

Wednesday 11 November 2026, 13:30Venue time (London)
Lecture Theatre 2, Department of Chemical Engineering and Biotechnology, West Cambridge Site
Price on the ticket pageTickets sold by talks.cam.ac.uk
Bookvia talks.cam.ac.uk
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Event details

Tickets sold by talks.cam.ac.uk

Price on the ticket page

Add to calendar · Downloads an .ics file · Times are in Europe/London · Google Calendar

Speaker: Professor Ryo Torii - Department of Mechanical Engineering, University College London
Series: Chemical Engineering and Biotechnology

Computational biomechanics, particularly computational fluid dynamics, has begun to find its way into clinical practice, notably in cardiovascular disease risk assessment. However, despite growing interest from the clinical community, its practical application remains limited to a relatively small number of areas, such as CT-derived fractional flow reserve computations, raising important questions about what is needed to achieve wider clinical adoption. In this talk, challenges of translating computational biomechanics into clinical science and practice will be discussed, drawing on our recent research in coronary artery disease, heart failure and hospital airflow optimisation. These examples will illustrate both the engineering challenges of delivering fast, reliable and physiologically realistic patient-specific simulations, including the emerging roles of digital twins and artificial intelligence, and the equally important challenges beyond engineering. The latter range from effective collaboration with multidisciplinary hospital teams to translating research innovations into real-world through a start-up company. Ultimately, the talk will consider a broader question: how can we, engineers, bring computational models to support clinical practice more with real world impacts?

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