We started in 2019 with origins in field-leading AI + biophysics research out of Stanford's Pande lab and a published collaboration with a top-five pharma company. We quickly assembled a team of seasoned biotech leaders and expert drug hunters to tightly integrate with our AI platform. Since then, we've dramatically accelerated innovation in ML + molecular simulation technologies for drug discovery.
Key innovations include Dynamic PotentialNet and other novel neural network models that examine drug-target complexes as flexible, spatial graphs — enabling superior prediction of potency, selectivity, and ADMET properties of drug candidates. These field-leading molecular property predictors alongside GEMS, our proprietary molecular generation engine, allow scientists to search immense swaths of chemical space and offer significant advantages in addressing novel, previously undruggable targets.
With a $52 million Series A round in December 2020, we built our own lab space and added to our fast-growing team across ML research, software engineering, chemistry, and biology. We are rapidly progressing our internal drug pipeline, as well as select external partnerships, to create transformative therapies for patients.