Genesis Therapeutics, a privately-held company inventing and deploying state-of-the-art artificial intelligence (AI) techniques to augment drug discovery and development, today announced that it has entered into a multi-target collaboration agreement with Genentech, a member of the Roche Group. The collaboration leverages Genesis’ graph machine learning and drug discovery expertise to identify innovative drug candidates for therapeutic targets in multiple disease areas. Genesis will receive an upfront payment and is eligible to receive pre-clinical, clinical and regulatory milestone payments, as well as future royalties on Genentech’s sales of approved drugs resulting from the collaboration.
“This partnership with Genentech enables us to leverage our AI technology platform with Genentech’s unmatched capabilities in molecular innovation and structural biology. We look forward to executing rapidly on this opportunity, which has the potential to change the standard of treatment for patients,” said Evan Feinberg, Ph.D., Genesis co-founder and CEO.
Genesis originated from breakthrough AI research at Stanford University’s Pande Lab, where Dr. Feinberg co-invented PotentialNet, a graph convolutional neural network algorithm that represented a leap forward in molecular property prediction when first published in the peer-reviewed journal, ACS Central Science. Since its founding, Genesis has further accelerated its innovation in AI and developed next generation algorithms, thus pioneering the intersection of protein motion — a key element of drug binding — with neural networks to develop fast and accurate technology for predicting the potency, selectivity, and ADME properties of drug-like molecules.
James Sabry, M.D., Ph.D., Global Head of Roche Pharma Partnering, stated, “AI can help unlock the next generation of innovative therapies for patients in need of additional options. We are excited to work with Genesis’ team to discover medicines currently out of reach using conventional methods.”
About the Genesis’ Molecular AI Platform
Genesis has developed Dynamic PotentialNet and other novel neural network algorithms that examine drug-target complexes as flexible, spatial graphs, with the advantage of superior potency and selectivity prediction uniquely toward novel, previously undruggable targets as well as well-characterized therapeutic targets. Genesis’ AI engineers, led by Co-founder and VP of Engineering, Ben Sklaroff, and informed by its medicinal chemistry team under the direction of Dr. Nicholas Stock, have executed a comprehensive and innovative process for drug discovery and early development. Their robust infrastructure scales the company’s AI platform on the Cloud, enabling them to combine their proprietary Molecular Generation Engine with their field-leading molecular property predictors to search immense swaths of chemical space as they approach drug discovery as a multiparameter optimization problem.
About Genesis Therapeutics
Genesis Therapeutics is a biotechnology company that invents and deploys breakthrough AI techniques to discover and develop drugs both internally as well as in select partnerships. Genesis is unique in its groundbreaking deep learning technology, its synergy of machine learning with biophysical simulation and its pairing of AI with extensive biotech/pharma expertise. With origins in AI research at Stanford by its co-founder and CEO, Evan Feinberg, Ph.D., Genesis has raised seed funding from Andreessen Horowitz, and augmented its technical expertise with accomplished biotech veterans. Complementing its cutting-edge technology, Genesis’ cadre of seasoned drug hunters includes Peppi Prasit, Ph.D., acting chief scientific officer and member of the Board of Directors, and Leonard Bell, M.D. founding chairman of the Board of Directors, who have collectively driven the discovery and development of 11 FDA-approved treatments, including “first and only-in-class” therapeutics and blockbuster drugs. Genesis was founded in 2019 and is headquartered in Burlingame, CA. To learn more, visit genesistherapeutics.ai.