We translate complex human data into insights that drive drug discovery. Valo has unique access to more than 17 million de-identified patient records, some with patient histories spanning 20-30 years and linked biobank samples. Using AI and proprietary knowledge graphs, we identify patient subtypes and map them to biological pathways. We then apply advanced causal inference and statistical genetics techniques to pinpoint targets for therapeutic intervention, and we validate them in human data before beginning experimentation in the lab.

By starting with human biology, we reduce biological risk early, focus our chemistry on validated targets, and aim to increase the likelihood of success downstream.

Like our human causal biology platform, our chemistry platform is designed for success in humans. We model the key attributes a drug needs to achieve the necessary safety and efficacy early in drug discovery, so we can align discovery efforts with the desired clinical profile from the beginning.  

Our tightly-coupled modeling and laboratory capabilities allow us to explore vast chemical spaces and identify novel, diverse lead compounds quickly. Models are rapidly refined after each round of experiments and applied to balance the competing properties needed to advance the most promising lead series into candidates.

By uniting AI and chemistry, with a patient-centric approach, we aim to accelerate discovery, de-risk high failure points, and uncover novel compounds against challenging targets that are often inaccessible with traditional approaches.