Early characterization of drug targets associated with disease can greatly reduce clinical failures attributed to lack of safety or efficacy. As single-cell RNA sequencing (scRNA-seq) of human tissues becomes increasingly common for disease profiling, the insights obtained from this data could influence target selection strategies. Whilst the use of scRNA-seq to understand target biology is well established, the impact of single-cell data in increasing the probability of candidate therapeutic targets to successfully advance from research to clinic has not been fully characterized. Inspired by previous work on an association between genetic evidence and clinical success, we used retrospective analysis of known drug target genes to identify potential predictors of target clinical success from scRNA-seq data. Particularly, we investigated whether successful drug targets are associated with cell type specific expression in a disease-relevant tissue (cell type specificity) or cell type specific over-expression in disease patients compared to healthy controls (disease cell specificity). Analysing scRNA-seq data across 30 diseases and 13 tissues, we found that both classes of scRNA-seq support significantly increase the odds of clinical success for gene-disease pairs. We estimate that combined they could approximately triple the chances of a target reaching phase III. Importantly, scRNA-seq analysis identifies a larger and complementary target space to that of direct genetic evidence. In particular, scRNA-seq support is more likely to prioritize therapeutically tractable classes of genes such as membrane-bound proteins. Our study suggests that scRNA-seq-derived information on cell type- and disease-specific expression can be leveraged to identify tractable and disease-relevant targets, with increased probability of success in the clinic.

Single-cell RNA sequencing of human tissue supports successful drug targets.