A near-autonomous AI chemist improves a challenging reaction in medicinal chemistry

OpenAI’s work in science is motivated by a simple belief: advanced AI can become a powerful partner for scientists, helping them explore more ideas, connect distant concepts, design better experiments, and accelerate discoveries that benefit humanity. We have already shared early examples of models contributing to novel results in mathematics, including work on the unit distance problem⁠, in theoretical physics, through a new result on gluon amplitudes⁠, and in biology, where GPT‑5 helped lower the cost of cell-free protein synthesis⁠ in an automated lab. We also introduced GPT‑Rosalind⁠, a purpose-built model to support life sciences research and drug discovery workflows. 

This project extends that trajectory into medicinal chemistry, where progress cannot be measured by reasoning alone. A hypothesis has to work in the lab with real molecules, instruments, and experimental noise. Working with Molecule.one⁠(opens in a new window), we connected GPT‑5.4 to Maria—an agentic chemistry AI integrated with a high-throughput laboratory for autonomous research—and gave it an open-ended goal: to improve one of several important reaction classes. The system generated research proposals, designed and ran experiments, analyzed experimental data, and proposed follow-up experiments. Humans remained in the loop by designing steering and grading prompts and selecting proposals to test. They also made limited corrections to experimental plans, assisted with basic laboratory operations, and independently validated the final result.

The most promising proposal, OAI-M1-03, focused on a difficult but useful version of Chan–Lam coupling, a reaction chemists use to form carbon-nitrogen bonds. Starting from the open-ended goal of improving Chan–Lam coupling for process chemistry, GPT‑5.4 independently identified primary sulfonamides as a challenging, high-value substrate class and suggested that mild oxidants, including TEMPO, could improve the reaction. 

TEMPO improves product formation at bench scale