Start: Wednesday, 24 May 2017 @ 09:00

End: Wednesday, 24 May 2017 @ 00:00

Venue: Hasselt University room C20 building D

City: Diepenbeek

Country: Belgium

Postcode: Campus

Description:

Current pharmaceutical research and development generates vast amounts of data. These big data come from high content screens, magnetic resonance imaging, omics and diagnostic patient monitoring devices. Together with this increasing magnitude of databases there is an associated increase in the time required to execute data processing. With the increasing complexity of methodology and new scientific insights, the existing computational algorithms and infrastructure are unlikely to cope with the challenges soon. Complex statistical models will push the limits of the current algorithms and implementations. To be able to face the challenges of the near future increased performance both at the algorithmic and software/hardware levels are deemed crucial.
Case studies on drug development will be given. One important project that is part of a collaboration of academic and industrial partners is conducting research on the computational requirements for disease modeling of Type II Diabetes as part of the ExaScience project (www.exascience.com). Appropriate use of computing infrastructure and high performance computing software makes it possible to use these new technologies in a time-constrained setting. This is a requirement when the disease models are used to make decisions within hours during the interim analyses of clinical trials with adaptive experimental designs. Besides this project other real-life cases presented include genomics, microbiome and brain imaging.
Speaker: Luc Bijnens PhD, Janssen Pharmaceutical Companies of Johnson and Johnson, 30 Turnhoutseweg,

Big data and High Performance Computing in Life Sciences https://tess.elixir-europe.org/events/big-data-and-high-performance-computing-in-life-sciences Current pharmaceutical research and development generates vast amounts of data. These big data come from high content screens, magnetic resonance imaging, omics and diagnostic patient monitoring devices. Together with this increasing magnitude of databases there is an associated increase in the time required to execute data processing. With the increasing complexity of methodology and new scientific insights, the existing computational algorithms and infrastructure are unlikely to cope with the challenges soon. Complex statistical models will push the limits of the current algorithms and implementations. To be able to face the challenges of the near future increased performance both at the algorithmic and software/hardware levels are deemed crucial. Case studies on drug development will be given. One important project that is part of a collaboration of academic and industrial partners is conducting research on the computational requirements for disease modeling of Type II Diabetes as part of the ExaScience project (www.exascience.com). Appropriate use of computing infrastructure and high performance computing software makes it possible to use these new technologies in a time-constrained setting. This is a requirement when the disease models are used to make decisions within hours during the interim analyses of clinical trials with adaptive experimental designs. Besides this project other real-life cases presented include genomics, microbiome and brain imaging. Speaker: Luc Bijnens PhD, Janssen Pharmaceutical Companies of Johnson and Johnson, 30 Turnhoutseweg, 2017-05-24 09:00:00 UTC 2017-05-24 00:00:00 UTC Hasselt University room C20 building D, Diepenbeek, Belgium Hasselt University room C20 building D Diepenbeek Belgium Campus [] [] [] [] [] []