Traditionally, drug discovery has largely been based on observational effects of chemicals on biological functions. The development of a drug being the refinement to a compound with most efficacy for least side effects. These compounds, or candidate drugs, may have arisen from biochemical understanding of processes, investigation of known phenomena such as toxicology, traditional treatments or other associations or even from serendipitous observations such as penicillin.
The potential for genomics to radically change this into a targeted high yield process is well known. The potential has been discussed in the medical research literature for over 20 years.
Over these years, incredible successes have been seen particularly in cancer with multiple targeted agents either replacing or being used alongside chemotherapy. These drugs have been particularly successful in some cancers including leukemia, lung, colorectal and others. Similarly, other disorders including hypercholesterolemia, cystic fibrosis and others are increasingly amenable to these genetically derived targeted treatments.
Drug trials are very expensive and have a high failure rate. One major pharma, for example, has reported closure of 57% of phase 2a trials and 88% of phase 3b trials as a result of lack of efficacy. The latter, a consequence of human disease not following experimental models or mimicking animal findings.
Efficiency improves significantly if genetic findings are applied. A study concluded that drugs were six to seven times more likely to be approved if the drug’s target had Mendelian genetic support . Further, the application of genetics to well understood common disorders was estimated to lead to twice as many progressing from Phase I to approval in repeat studies.
The study of disease within discrete populations that are relatively isolated, or that have a high rate of consanguinity offers a shortcut to the identification of these actionable genes, as has been seen in various populations across the world.
Further, in 2019 it was estimated that with the traditional pharma pre-clinical approach only one in every 200 protein-disease pairings were causal. Clearly this made a very significant contribution to the reported drug development failure rate of 96%. In contrast, substituting genomic data for preclinical studies as the major information source for drug target identification was estimated to reverse the probability of late-stage failure with the potential to produce radical improvement in drug development success rates.
In conclusion then, scientists are generating new knowledge with genomics to radically transform both the drug discovery as well as development processes.