SuntheticsML guides pharmaceutical and chemical R&D teams through their data to the next optimal experiments, allowing them to achive their objectives faster.
Peer-reviewed with Merck and Boehringer Ingelheim in Biochemistry and Org. Process Res. Dev.
By the numbers
fewer experiments than traditional DoE
faster than traditional DoE and HTE
prediction accuracy in guided campaigns
SuntheticsML works across the industries where experimental complexity is highest and every failed run is expensive. Whether you're optimizing a pharmaceutical process, scaling a CDMO campaign, or developing a new cosmetic formulation, the platform adapts to your chemistry — not the other way around.
Selected by the NSF in 2026 for a $19.5M program to help build a national AI-driven chemistry labwith Scripps Research and UCLA.
ACS GCI Pharmaceutical Roundtable, received with Merck
SuntheticsML learns from your data and points to the experiments that matter, so your team reaches its objectives in fewer rounds.
Traditional R&D relies on trial and error. Sunthetics replaces that with machine learning that achieves 99% prediction accuracy — starting with as few as 5 experiments, no coding required.
SuntheticsML models the interacting variables and high-dimensional spaces trial and error can't, with results that hold up in peer-reviewed research and scale from one scientist to the enterprise.
