In Silico Trials Open Innovation community on Crowdhelix

Background

The In Silico Trials Helix is a joint initiative of the Virtual Physiological Human Institute (VPHi) and Avicenna Alliance. It was launched in early 2022 and is co-chaired by Prof Alex Frangi, University of Leeds and KU Leuven (VPHi Member and co-chair of the Avicenna Alliance UK Task Force) and Prof Liesbet Geris, University of Liège and KU Leuven (Executive Director of VPHi).

Scope

Virtual or “in silico” trials are clinical trials performed in virtual populations via computer simulation. Computational modelling and simulation are widely encountered across industry sectors underpinned by engineering and science (e.g. automotive and aerospace) but used only to a more limited degree in pharma and medtech innovation and regulations.

Technological developments in patient-specific computational simulations have enabled in silico trials to predict the safety and efficacy of medical devices and novel drugs as part of the research and development life cycle. In silico trials have the potential to revolutionise clinical testing by reducing both the time and costs associated with developing new medical devices and drugs, as well as reducing human and animal harm and testing. Recently, there is also a stronger focus on regulatory science for in silico medicine, developing guidelines and standards for credibility assessment in the regulatory approval process.

The Virtual Physiological Human Institute (www.vph-institute.org), bringing together academics and healthcare professionals, has encouraged and coordinated the development of virtual humans for more than a decade. The Avicenna Alliance (www.avicenna-alliance.com) is bringing together researchers from academia (represented by VPHi) and industry, and other stakeholders ranging from regulatory authorities to policymakers. The In Silico Trials Helix aims to work closely with these two entities as well as UK KTN (www.insilicouk.org) to further amplify visibility and international collaboration among all in silico stakeholders.

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