Abstract Drug candidates are often evaluated for their activities against unexpected targets (off-targets), to either prospectively flag potential hazards or to provide mechanistic insights for a given phenotype. The in vitro to in vivo translatability is critical when selecting which “phenotypically consequential” off-targets to screen. To this end, human genetics and indication-based pharmacology offer unraveled insights. Enhanced natural language processing tools were applied to harness the power of large data obtained from 7 genetics and 2 pharmacology databases. Mapping biological roles to organ systems, we curated targets implicated in 22 organ systems of safety concerns, resulting in a safetyome composed of over ∼11,000 proteins. This is a significant expansion from our previously proposed screen, whose scope included phenotypes affecting 5 organ systems. Prioritization of the large panel using expression pattern and gene conservation across species resulted in a core panel of 500 targets. Mapping biological roles obtained from the databases to specific terms allowed us to systematically generate over 3,000 phenotype-based (specialized) panels, which can be used as gene or protein sets for issue resolution. All three components: The full safetyome, the core panel of 500 targets, and the over 3,000+ specialized panels, were systematically and orthogonally tested using independent data source, i.e., gene expression data from the Comparative Toxicogenomics Database. All panels, together with a user-friendly App, are published to aid effective safety assessment and issue resolution with strong “translational” focus.
Liu et al. (Thu,) studied this question.