Three years have passed since the publication by Nelson et al. and five years have passed since the data freeze used for analysis occurred [3]. The results may now be validated using drug progression events to which Nelson et al. were completely blinded at the time. Similarly, ongoing efforts in discovering disease-associated variants in increasingly large patient samples have rapidly grown the number of potential gene trait links. For example, a public central repository of genetic association studies (GWAS Catalog [10], https://www.ebi.ac.uk/gwas/) has grown by four-fold [11, 12]. Additionally, the quantity and quality of links between noncoding SNPs and genes has expanded with the development of GTEx [13]. Here we report revised estimates of the impact of genetic evidence on drug target success and extend Nelson’s observations into a model that can be deployed by other companies and academics to predict the likelihood of success of targets of interest to them.
