Medra AI Raises $52M Series A to Scale Autonomous “Physical AI Scientist” Platform for Drug Discovery
Medra AI, a San Francisco‑based startup building what it calls the first Physical AI Scientist platform that unifies artificial intelligence with robotics to autonomously run scientific experiments, has raised $52 million in a Series A funding round to scale its autonomous laboratory technology and accelerate its vision for transforming drug discovery and life‑science research.
The Series A investment was led by Human Capital and saw participation from a broad group of existing and new investors, including Lux Capital, Neo, NFDG, Catalio Capital Management, Menlo Ventures, 776, and Fusion Fund, among others. This financing brings Medra’s total capital raised to approximately $63 million, reflecting strong support from venture firms aligned with frontier AI, robotics, and biotech innovation.
Founded by CEO Michelle Lee, Medra is developing an integrated platform that combines Physical AI—general‑purpose robotics capable of executing laboratory experiments—with Scientific AI, an artificial intelligence system that reasons about experimental results and iteratively improves protocols. The company’s technology seeks to close the loop between prediction, experimentation, and optimization, enabling continuous learning from experimental outcomes and accelerating the pace at which scientific knowledge can be generated and applied.
Medra’s platform distinguishes itself by enabling autonomous execution of laboratory work using the same instruments scientists already rely on, while also interpreting results and adapting experimental methods in real time. This approach aims to address longstanding inefficiencies in pharmaceutical R&D, where traditional lab automation remains fragmented and requires significant human intervention. By creating a continuous feedback loop tying AI predictions directly to experiment execution, Medra intends to dramatically increase throughput, reduce manual bottlenecks, and enable discovery at scales that are difficult or impossible with conventional workflows.
In practical terms, Medra’s systems can interpret instructions in natural language, perform experiments end‑to‑end with robotic precision, and feed data back into machine learning models to refine future predictions and experimental approaches. According to the company, this continuous scientific loop enhances reproducibility and speeds the iteration cycles that are a hallmark of drug discovery and early‑stage biopharmaceutical research.
In addition to the funding news, Medra has announced a strategic collaboration with Genentech, a biotechnology leader. Under this partnership, Medra’s Physical AI and Scientific AI technologies will be integrated with Genentech’s laboratory information management systems and machine learning infrastructure, creating a closed‑loop workflow that supports prediction, execution, and iterative improvement of experiments. The partnership underscores industry interest in autonomous science as a way to accelerate therapeutic innovation.
The company’s technology has already seen deployment with select partners. Medra reports that its autonomous systems are in operation across multiple sites in the United States, including collaborations with both Genentech and other research organizations such as Addition Therapeutics, where its integrated platform supports experimental workflows from gene editing to biochemical assays. These early deployments highlight the platform’s real‑world applicability and potential to scale beyond proof‑of‑concept into operational laboratory settings.
Medra’s founders and investors see the platform as a foundational shift in how scientific research is conducted. By combining physical robotic execution with reasoning AI, the company aims to help scientists generate data at unprecedented scale and accelerate discovery timelines that traditionally span many years and substantial cost. With the new funding, Medra plans to build out its autonomous lab infrastructure, grow its technical teams, and expand partnerships with pharmaceutical companies and research institutions.
The $52 million Series A comes as AI continues to reshape multiple sectors of biotechnology, with autonomous science platforms emerging as a new frontier for investment. Medra’s integrated AI‑robotics approach could unlock efficiencies in early drug discovery, increase reproducibility, and help bring new treatments to patients more quickly by leveraging automation and continuous learning in laboratory environments.
By advancing its platform and broadening its collaborations, Medra is positioning itself at the intersection of AI, robotics, and life‑science research, where autonomous experimentation may redefine traditional scientific workflows and accelerate the pace of innovation across the biopharmaceutical landscape.
