In Silico Profiling of Clinical Phenotypes for Human Targets Using Adverse Event Data
AbstractWe present a novel approach for the molecular transformation and analysis of patient clinical phenotypes. Building on the fact that drugs perturb the function of targets/genes, we integrated data from 8.2 million clinical reports detailing drug-induced side effects with the molecular world of drug-target information. Using this dataset, we extracted 1.8 million associations of clinical phenotypes to 770 human drug-targets. This collection is perhaps the largest phenotypic profiling reference of human targets to-date, and unique in that it enables rapid development of testable molecular hypotheses directly from human-specific information. We also present validation results demonstrating analytical utilities of the approach, including drug safety prediction, and the design of novel combination therapies. Challenging the long-standing notion that molecular perturbation studies cannot be performed in humans, our data allows researchers to capitalize on the vast tomes of clinical information available throughout the healthcare system. View Full-Text
- Supplementary File 1:
ZIP-Document (ZIP, 67682 KB)
Share & Cite This Article
Soldatos, T.G.; Taglang, G.; Jackson, D.B. In Silico Profiling of Clinical Phenotypes for Human Targets Using Adverse Event Data. High-Throughput 2018, 7, 37.
Soldatos TG, Taglang G, Jackson DB. In Silico Profiling of Clinical Phenotypes for Human Targets Using Adverse Event Data. High-Throughput. 2018; 7(4):37.Chicago/Turabian Style
Soldatos, Theodoros G.; Taglang, Guillaume; Jackson, David B. 2018. "In Silico Profiling of Clinical Phenotypes for Human Targets Using Adverse Event Data." High-Throughput 7, no. 4: 37.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.