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Reverse Translation: The Art of Cyclical Learning
Author(s) -
Kasichayanula Sreeneeranj,
Venkatakrishnan Karthik
Publication year - 2018
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.952
Subject(s) - transformative learning , exploit , transparency (behavior) , data science , citizen journalism , clinical trial , computer science , medicine , psychology , world wide web , pedagogy , computer security , pathology
We live in an era of precision therapeutics, value‐based healthcare, patient‐participatory research, and enhanced clinical trial transparency, with explosive increases in our ability to access and analyze multiscale biological and clinical data from diverse ecosystems. To discover and develop truly transformative medicines with a patient‐centric sense of urgency, we will need to exploit data that lie far beyond the confines of laboratory‐based experimental models and controlled clinical trials, dynamically maximizing the value of information in real‐world data from clinical practice settings and even social media. This demands commitment to a culture that embraces Reverse Translation as a critical component of the practice of Translational Medicine in the discovery, development, regulation, and utilization of therapeutics.