Traditional drug development forces chemists to juggle a dozen disparate properties to gauge a compound's potential. Beacon-2 consolidates these variables into a single metric, allowing teams to identify high-quality candidates with greater precision. The underlying ADMET models have already proven their accuracy by outperforming over 750 competitors in three consecutive OpenADMET blind challenges.

In a practical test of its agentic design capabilities, Inductive tasked its AI chemist, Indy, with optimizing a SARS-CoV-2 compound. Over five autonomous cycles, the system improved the predicted human dose by 17-fold, a margin capable of shifting a drug program from failure to clinical viability. According to CEO Josh Haimson, computing dose directly from structure fundamentally alters the decision-making process for research teams.

Beacon-2 is now accessible to partners through the company's Compass platform, where it is currently integrated into active drug discovery programs. Inductive, which combines chemical intelligence models with physical lab robotics, currently supports over 100 discovery initiatives across the biopharma sector.