No data required. Just define your TPP and Enki does the rest. Enki is an ensemble of generative algorithms trained on decades worth of experimental data with proven results.
Select your on-target(s), off-target(s),
and other properties in minutes.
The Enki™ Platform is the first commercially accessible foundation model for small molecules.
Founded in September 2019, we are a team of experienced AI/machine learning researchers and medicinal and computational chemists applying state of the art generative AI to drug discovery in close collaboration with biopharmaceutical partners to redefine the unit economics of drug discovery and development.
We are a team of experienced AI/machine learning and business specialists applying state of the art generative AI to drug discovery in close collaboration with biopharmaceutical partners to bring new therapeutics to market across disease areas and positively impact lives.
Handol Kim
Mehran Khodabandeh, PhD
Ahmad Issa, PhD
Marshall Drew-Brook
Jason Rolfe, PhD
Ali Saberali, PhD
Peter Guzzo, PhD
Roslynn Drewitt-Lange
Sara Ibrahim Omar, PhD
Nathania Takyi, MSc
Frank Chang
Board Member
Robert N. Young
PhD, SAB Member (Medicinal Chemistry)
Jennifer Hamilton
PhD, Advisor (Strategy/Commercial)
Todd Farrell
Advisor (Strategy)
John Boylan
PhD, SAB Member (Cell Biology/Oncology drug discovery)
Mads Daugaard
PhD, SAB Member (Oncology Biology)
Alexander Tropsha
PhD, SAB Member (Cheminformatics)
Nancy Harrison
Advisor (Strategy/ Commercial)
Artem Cherkasov
PhD, SAB Member (Cheminformatics)
Founded in September 2019, we are a team of experienced AI/machine learning and business specialists applying state of the art generative AI to drug discovery in close collaboration with biopharmaceutical partners to bring new therapeutics to market across disease areas and positively impact lives.
Immuno-Oncology pioneer ImmVue Therapeutics to adopt Enki™Lead Generator to discover first-in-class cancer drugs.
Rakovina announces potential multi-target engagement with Variational AI focused on DNA Damage Repair (DDR)
QSAR models struggle with extrapolation compared to conventional ML tasks like image recognition. Machine learning generalizes effectively when structured to align with its problem domain, suggesting that improving QSAR models…
Please see open job listing below or contact us if you would like to join the team in the area of machine learning, computational medicinal chemistry, and business development.