There was much hope that the advent of the Human Genome Project would lead to significant innovations as we began to learn more and more about how genes relate to disease. The ability of translating this knowledge to targeted therapies, however, is challenging. One key issue is how many genetic mutations cause a disease; it is likely easier to create a precision medicine for a disease caused by one genetic mutation than a disease caused by multiple mutations.
In fact, this is what a paper by Hermosilla and Lemus (2018) find. They use data from the open-source Genome-Wide Association Studies (GWAS) Catalog to determine the number of genetic mutations associated with a disease and data from Thomson Reuters Cortellis to determine the number of drugs being developed for a given disease. Using this approach, they find the following:
…biological complexity is an important determinant of the rate of translation [into new, innovative medicines]. This rate is large among diseases with lower measured complexity, decreasing as complexity rises, and indistinguishable from zero among diseases in the extreme of higher complexity. Particularly, in the current “genomic era,” biological complexity stands out as a potentially important conditioning factor for the assessment of innovative productivity in the industry, and the allocation of funding by scientific agencies.
The full paper is available here.