Medra is building an end-to-end platform that pairs autonomous laboratory robotics (its “Physical AI”) with an AI reasoning engine (its “Scientific AI”) to run, interpret, and iteratively improve life-science experiments without human intervention. By closing the loop between prediction and execution, the system generates reusable data, refines protocols through natural-language commands, and creates a self-improving cycle intended to shorten drug-discovery timelines and raise success rates. The company argues that current pharma R&D remains fragmented between brittle lab automation and disconnected machine-learning models, resulting in 10–15-year, $2 billion development cycles. Medra’s unified approach lets scientists run far more experiments, iterate faster, and feed every result back into the model for continuous learning. The platform is positioned as a new category—“Physical AI Scientists”—within biopharma R&D. Headquartered in San Francisco, Medra is led by founder and CEO Michelle Lee, Ph.D. The company has just secured a significant Series A round to scale its technology and expand commercial partnerships.

Total raised

$52M

Funding rounds

1

Latest round

Series A

Latest activity

Dec 2025