Predicting clinically promising therapeutic hypotheses using tensor factorization

Published: Feb 27, 2018
Abstract
Determining which target to pursue is a challenging and error-prone first step in developing a therapeutic treatment for a disease, where missteps are potentially very costly given the long-time frames and high expenses of drug development. We identified examples of successes and failures of target-indication pairs in clinical trials across 875 targets and 574 disease indications to build a gold-standard data set of 6,140 known clinical...
Paper Details
Title
Predicting clinically promising therapeutic hypotheses using tensor factorization
Published Date
Feb 27, 2018
Journal
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