Driving Hit Identification Through Lead Optimisation Using Artificial Intelligence
Accelerate Hit-to-Lead and Lead Optimization Using the Valence Discovery Platform
The Valence platform enables the design of small molecule drug candidates in novel regions of chemical space, followed by rapid optimization against project-specific potency, selectivity, ADMET, and pharmacology criteria. Valence has pioneered the application of few-shot learning in drug design, allowing the company to unlock prediction tasks for which only small amounts of training data are available, overcoming a critical limitation of existing machine learning technologies in drug discovery.
Through this collaboration, our clients will have the option to access Valence’s platform to support their drug discovery efforts, both standalone or by application of their current drug program. When taking advantage of this option, clients can expect increased diversity in chemical matter being investigated in combination with more rapid optimization against complex, project-specific design criteria, ultimately reducing timelines and improving success rates for drug discovery projects.
The Valence platform offers a step-change improvement over existing de novo design technologies. It has the ability to generate high quality chemical matter that’s readily synthesizable, in novel regions of chemical space, from datasets not otherwise accessible to machine learning methods.
When pursuing AI-enabled drug discovery with us, clients can expect shorter timelines and the highest quality drug candidate molecule. Our experienced scientists and partners collaborate with clients to optimize all phases, including early hit identification, hit-to-lead, lead optimization, patent strategy, and preparation for IND filing.