An AI–Molecular Modeling Platform for Streamlining Small-Molecule Drug Discovery

To bring a small-molecule drug to market takes 10–15 years and costs roughly \$1B. Of that, around 32% of the costs are spent on pre-clinical R&D. Here, around 5,000-10,000 compounds will be made and tested over a course of approximately 5 years to arrive at a clinical candidate, which will only have about a 14% chance of achieving market approval. In contrast, we discuss how Denovicon’s unique hybrid computational platform (with its AI, machine learning, physics-based approaches, and generative therapeutic design) has, in just a short time, led to the design of next-generation inhibitors for Poly [ADP-ribose] polymerase 1 (PARP1) as exemplified by the sub-nanomolar compound. 2022 BIOVIA Conference ​​​​​​​

@PG ​​​​​​​@AG ​​​​​​​@TL ​​​​​​​