Extended Data Fig. 3: Sensitivity to changes in genetic data and drug pipeline over the past decade and to the ‘genetic insight’ filter.

“2013” here indicates the data freezes from Nelson et al.⁵ (that study’s supplementary dataset 2 for genetics and supplementary dataset 3 for drug pipeline); “2023” indicates the data freezes in the present study. All datasets were processed using the current MeSH similarity matrix, and because “genetic insight” changes over time (more traits have been studied genetically now than in 2013), all panels are unfiltered for genetic insight (hence numbers in panel D differ from those in Fig. 1a). Every panel shows the proportion of combined (both historical and active) target-indication pairs with genetic support, or P(G), by development phase. A) 2013 drug pipeline and 2013 genetics. B) 2013 drug pipeline and 2023 genetics. C) 2023 drug pipeline and 2013 genetics. D) 2023 drug pipeline and 2023 genetics. E) 2023 drug pipeline with only OTG GWAS hits through 2013 and no other sources of genetic evidence. F) 2023 drug pipeline with only OTG GWAS hits for all years, no other sources of genetic evidence. We note that the increase in P(G) over the past decade⁵ is almost entirely attributable to new genetic evidence (e.g. contrast B vs. A, D vs. C, F vs. E) rather than changes in the drug pipeline (e.g. compare A vs. C, B vs. D). In contrast, the increase in RS is due mostly to changes in the drug pipeline (compare C, D, E, F vs. A, B), in line with theoretical expectations outlined by Hingorani et al.¹⁶ and consistent with the findings of King et al.¹⁵ We note that both the contrasts in this figure, and the fact that genetic support is so often retrospective (Extended Data Fig. 2g) suggest that P(G) will continue to rise in coming years. For 2013 drug pipeline, N = 8,624 T-I pairs (1,605 preclinical, 1,772 phase I, 2,779 phase II, 636 phase III, and 1,832 launched); for 2023 drug pipeline, N = 29,464 T-I pairs (N = 12,653 preclinical, 4,946 phase I, 8,268 phase II, 1,781 phase III, and 1,816 launched). Details including numerator and denominator for P(G) and full continency tables for RS are provided in Tables S19 - S20. In A-F, the center is exact proportion and error bars are Wilson binomial 95% confidence intervals. Because all panels here are unfiltered for genetic insight, we also show the difference in RS across G) sources of genetic evidence and H) therapy areas when this filter is removed. In general, removing this filter decreases RS by 0.17; this varies only slightly between sources and areas. The largest impact is seen in Infection, where removing the filter drops the RS from 2.73 to 2.03. The relatively minor impact of removing the genetic insight filter is consistent with the findings of King et al.¹⁵, who varied the minimum number of genetic associations required for an indication to be included, and found that risk ratio for progression (i.e. RS) was slightly diminished when the threshold was reduced. See Fig. S5 for the same analyses restricted to drugs with a single known target.

Source Data