VeriSIM Life’s AtlasGEN Novel Drug Designer Bridges the Translational Gap, Bringing Life-Saving Treatments to Patients Faster

Drug discovery, research and development has reached a boiling point of inefficiency; in the US, the FDA approves about 50 new drugs per year while 300 million patients suffering from unmet diseases have no direct treatment. This is not acceptable. To bring life-saving treatments to patients faster, we must radically change the traditional drug design process which endures massive R&D failure in pursuit of an approved new therapy. Big pharma in particular is getting worse at translating new drugs to the market: while the number of registered new drug candidates has increased 72%, the relative proportion of approved drugs from big pharma has fallen from 76% to 25%. 

Designing a new drug molecule to fight diseases is extremely difficult; even when a disease’s pathway is clearly understood and a target identified, finding a drug compound that is both selective and potent requires significant scientific trial and error experimentation, even with the help of computers. This is the main reason for the large translational gap, which is also known as the “valley of death,” referring to the routine failure of the bench-to-bedside process and the lack of successful drug candidates that make it all the way through discovery and research to clinical use in patients.

Some in the industry tout generative AI as the solution to this crisis, but many of them are missing the point: without integrating cutting-edge technologies like artificial intelligence with accurate and relevant biological knowledge systems and data, AI-based drug discovery methods are doomed to the same propensity for failure as the current processes. AI can help drug developers find drug candidates faster, but they will not have biological relevance derived from actual human and animal physiology. Instead, drug developers need an approach that applies biological validation to the drug design process, which produces drug candidates that are inherently superior in translatability. 

VeriSIM Life recently announced the availability of AtlasGEN™ Novel Drug Designer, which is the first and only platform that combines generative chemical discovery with biological validation to compress drug candidate selection and reduce costly experimental research dramatically. AtlasGEN is different because it constrains the generative AI with biological data, ensuring relevant and accurate results. Instead of returning 1000 potential molecular hits, most of which are not good, AtlasGEN reduces wasted time, energy and money by returning only the results that are viable. 

AtlasGEN is the natural extension of the BIOiSIM^® platform–VeriSIM Life’s predictive translational science decision engine which uses hybrid AI to simulate the biology of humans and other species and assess the therapeutic potential of therapies, be they small molecule, large molecule or other modalities. The accuracy of BIOiSIM has been validated in multiple studies, and by clients worldwide.