Minimizing biological risk for novel inhibitory drug targets: One knockout is all you need

We argue that biological risk for novel inhibitory drug targets can be minimized, almost eliminated, by a computational analysis of the healthcare records and DNA sequences in resources like UK Biobank or All-of-Us. The key insight is that an inhibitory drug is functionally equivalent to a loss-of-function (LOF) variant in the targeted gene. It is a special case of what has been called an "experiment of nature". To demonstrate, we considered all available clinical trials (58 in total) and inhibitory drugs (15 in total) for 5 cardiovascular drug targets: PCSK9, APOC3, ANGPTL3, LPA, and ASGR1. The results were shocking. Every biomarker assessed in these clinical trials was successfully predicted, i.e. directionality and proportionality of effect, but not the magnitude since that varies with dosage. This concept has not been widely adopted because geneticists believe that homozygous LOFs, which are exceedingly rare, would be needed to observe a significant phenotypic effect from most genetic knockouts. Our study shows that, to the contrary, given a sufficiently large biobank, counting both carriers and non-carriers, heterozygous LOFs alone can inform drug development.