INSIST in silico project: The future of randomised controlled trials

NeuroNews published an interview with two of the INSIST project’s leaders: Charles Majoie (professor of neuroradiology at the Amsterdam University Medical Center Amsterdam) and Alfons Hoekstra (professor of computational science and engineering, director of the Informatics Institute at Amsterdam University and one of VPHi’s directors)

“Performing a randomised control trial (RCT) is a huge burden and also very expensive, for researchers as well as patients. Despite good designs, they often fail. So, with INSIST, we aim to generate a platform to perform the trials in silico through computational modelling and simulation technologies. We now have computer simulations, which are standard technology in many industries like automotive, aeronautics or engineering, but they are really underestimated for the health care setting. INSIST is based largely on existing databases like the MR CLEAN trial and MR CLEAN registry. We have generated a virtual population model, which is an effective covariant distribution model, incorporating all relevant patient parameters that may account for the differences between those individuals. We also generated models to simulate thrombosis and thrombolysis, thrombectomy, and models simulating tissue fate during and following ischaemic stroke. We have also generated a platform for in silico trials.” says Charles Majoie explaining the aim of the project.

Hoekstra added, “We are talking about mathematical models. What we do is try to mimic parts of physiology in the computer and then we are able to do that. We can also model the path of physiology in a computer, in this case a stroke, and we can also model treatment. We have a movie showing a thrombectomy treatment, but this is not an animation. This is completely computed from the basic laws of physics and from the basic laws of physiology and biology. And that is one big thing to realise. And so when we speak about models, this is what we mean.”

Read the full article here


Date: 25/02/2021 | Tag: | News: 1173 of 1633
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