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The FDA Grand Rounds is an educational presentation that is webcast monthly to highlight cutting-edge research underway across the Agency and its impact on protecting and advancing public health. Each session features an FDA scientist presenting on a key public health challenge and how FDA is applying science to its regulatory activities. The 45-minute educational presentation is followed by questions from the audience. You can also view the presentation under Past Grand Rounds following the live webcast. #FDAGrandRounds.

Some Perspectives on Data Science and Coronaviruses

June 9, 2022
9:00 AM - 10:00 AM ET
Webcast

About the Speaker

Seshadri S. Vasan, DPhil (Oxon)
COVID-19 Science Leader, CSIRO, Australia
Honorary Professor, University of York, UK

Dr. Seshadri S. Vasan, is a COVID-19 Science Leader for Australia’s science agency CSIRO, and one of the successful applicants for the FDA’s Medical Countermeasures Initiative (MCMi) regulatory science extramural funding. He is based at the secure ‘Australian Centre for Disease Preparedness’ facility in Geelong and was previously at the equivalent British high-containment facility in Porton Down. Prior to that he worked on arboviral diseases as the Head of Public Health for Oxford University’s spin-out Oxitec. He is an Honorary Professor of Health Sciences at the University of York in England, and obtained his doctorate from Trinity College, Oxford, as a Rhodes scholar.

About the Presentation

This lecture will present some perspectives, illustrated with recent COVID-19 experience and examples, on how in silico modelling and data science techniques could strengthen nonclinical (in vitro and animal) models for existing and emerging coronaviral diseases. Four peer-reviewed case studies will be reviewed briefly:

  1. Could alignment-free approaches complement traditional phylogenetic analysis of coronavirus variants?
  2. Why big data on viral genome sequences are less useful without metadata?
  3. Could we predict if certain hosts are likely susceptible to infection by an emerging coronavirus variant?
  4. Can AlphaFold2 artificial intelligence predictions of protein structure aid our understanding of viral antigens?

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