Genescient’s unique approach to drug development – involving genomics, experimental evolution, and AI data analysis — provides three interlocking advantages over competing approaches.
First, competing firms search for potential drug targets using traditional locus-by-locus mutagenesis or RNAi, which both cost dramatically more than Genescient’s approach, on a per-locus basis (2 or 3 orders of magnitude more, according to heuristic estimates).
Second, Genescient has a unique capability to explore drug targets in flies effectively, because its proprietary database includes cross-linkages between fly and human genomics that provide a path around the pitfall of finding potential targets that may help flies but not people.
Third, Genescient’s hypotheses are guided by AI-powered genomic analysis of experimental evolution rather than by human intuition. This is a huge advantage given that most chronic diseases are controlled by complex networks rather than single-gene mechanisms. Even the best human researchers have a very limited ability to intuit the behavior of such networks, as indicated by the failure of promising therapeutic candidates even in late stage clinical development.
So, rather than a “trial and error” process of trying out various substances on the flies and then seeing whether they also work in humans, Genescient’s experimental-evolution approach allows a more systematic process, in which the set of candidate substances to be tested for therapeutic value is carefully chosen based on statistical and AI analysis of fly genetics and its orthologies to human genetics, prior to wet-lab testing.
As a result of these advantages, Genescient’s approach is capable of discovering powerful drugs that traditional approaches would miss, and is also much less susceptible to false positive results that suggest drugs that won’t work or that have too many adverse side-effects.