In current drug development, there exist huge gaps in translating activity in the preclinical screening models into desirable clinical outcomes in humans. In this project titled """"""""Rapid reverse translational drug repositioning: novel computational approaches, unique data, and broad implications,"""""""" we propose to develop a novel drug discovery strategy that directly translates observed phenotypic perturbations caused by drugs or diseases in human bodies into novel disease treatments in humans (direct human ->human translation), and retrospectively corroborates novel drug indications using large amounts of patient electronic health record (EHR) data. In this way, we can minimize the translational gap between pre-clinical testing results in animal models and clinical outcomes in humans in current drug development.
In this project titled Rapid reverse translational drug repositioning: novel computational approaches, unique data, and broad implications, we propose to develop a novel drug discovery strategy that directly translates observed phenotypic perturbations caused by drugs or diseases in human bodies into novel disease treatments in humans (direct human ->human translation). In this way, we can minimize the translational gap between pre-clinical testing results in animal models and clinical outcomes in humans, which is a significant problem in current drug development.
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