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LOCATION:HG F 26.5
DTSTART;TZID=Europe/Stockholm:20240603T123000
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UID:submissions.pasc-conference.org_PASC24_sess142_msa170@linklings.com
SUMMARY:Towards an Open Ecosystem for FAIR (Findable, Accessible, Interope
 rable, Reusable) Drug Response Prediction Models and Data
DESCRIPTION:Minisymposium\n\nEric Stahlberg (Frederick National Laboratory
  for Cancer Research)\n\nFueled by pervasive supercomputing and growing av
 ailability of response data have led to a dramatic increase in the availab
 ility of predictive drug response models. Over the past several years, the
  collaboration between the US Department of Energy and the US National Can
 cer Institute have resulted in multiple advances towards an Open and FAIR 
 ecosystem for creating, evaluating and sharing drug response models. The p
 resentation will provide an overview of several of these projects providin
 g publicly available resources including IMPROVE (Innovative Methods and d
 ata for Predictive Oncology Validation and Evaluation), ATOM (Accelerating
  Therapeutics for Opportunities in Medicine) and MODAC (the NCI Predictive
  Oncology Model and Data Clearinghouse). Future directions and priorities 
 will also be shared in terms of ethical AI and guidance for transparency t
 o build trust and reuse of trained models.\n\nDomain: Life Sciences, Compu
 tational Methods and Applied Mathematics\n\nSession Chair: Thomas Brettin 
 (Argonne National Laboratory, University of Chicago)
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