Takeaways by Saasverse AI
- Medra | Series A | $52 Million | Physical AI Scientist Platform for Drug Discovery.
- Led by Human Capital with participation from Lux Capital, Neo, NFDG, Catalio Capital Management, Menlo Ventures, 776, Fusion Fund, and others.
- Platform integrates robotics and AI for autonomous lab workflows; deployed at Genentech and other biopharma partners, targeting drug discovery acceleration.
Medra, a groundbreaking startup pioneering the integration of robotics and AI into drug discovery workflows, has raised $52 million in Series A funding. Human Capital led the round, with participation from existing investors Lux Capital, Neo, and NFDG, as well as new backers Catalio Capital Management, Menlo Ventures, 776, and Fusion Fund. This financing brings Medra’s total funding to $63 million, including pre-seed and seed rounds, and positions the company as a leader in the emerging field of physical AI for scientific research.
Founded in 2022 by Stanford Robotics PhD graduate Dr. Michelle Lee, Medra is on a mission to revolutionize the pharmaceutical industry through its Continuous Science Platform, the world’s first physical AI scientist. This platform combines advanced robotics, AI-driven software, and natural language interfaces to automate complex laboratory workflows, allowing for unprecedented speed, precision, and adaptability in scientific experiments. Medra’s approach closes the loop between predictive modeling and experimental execution, creating a self-improving system that accelerates drug discovery and development.
At the heart of Medra’s innovation is the seamless integration of physical AI and scientific AI. The physical AI component uses sensor-equipped robotic arms to autonomously perform intricate laboratory tasks such as pipetting, mixing, and cell manipulation. These robots are controlled by Medra’s proprietary software, which allows scientists to issue natural language instructions and collaboratively brainstorm experimental designs. Every detail of an experiment, from pipette angles to reagent mixing speeds, is meticulously recorded and fed into the Continuous Science Platform. This data then informs the platform’s AI, which refines experimental protocols and proposes adjustments for subsequent iterations.
The scientific AI side of the platform is equally transformative. By leveraging multimodal reasoning across unstructured data, visual inputs, and experimental results, Medra’s AI can optimize protocols, design new experiments, and facilitate closed-loop learning. This capability enables the platform to continuously refine its own performance, adapt to new scientific challenges, and generate actionable insights at a scale unattainable by traditional lab setups.
Medra’s platform is designed to support a wide range of applications, from gene editing and protein engineering to immunology and antibody development. Its modular architecture allows researchers to easily integrate new instruments and adapt workflows to different scientific domains. For example, the system can autonomously prepare NGS libraries, execute CRISPR-Cas9 gene editing protocols, and perform cell viability assays—all while capturing rich metadata and video documentation to enhance reproducibility and auditability.
Medra has already deployed its system at five customer sites across the U.S., including Genentech, a subsidiary of Roche, and Addition Therapeutics, focusing on early-stage drug discovery. Genentech is leveraging Medra’s platform to explore novel therapeutic candidates, while Addition Therapeutics uses it for gene editing research. By partnering exclusively with paying biopharma clients and avoiding unpaid pilot projects, Medra is positioning itself as a premium provider of end-to-end scientific automation.
Dr. Michelle Lee, Medra’s CEO and founder, highlighted the platform’s potential to transform drug discovery timelines: “Pharmaceutical companies run millions of experiments annually, yet much of the data remains underutilized. By linking predictions directly to automated execution and feeding results back into models, we’ve created a system that accelerates experimentation and improves success rates. This feedback loop enables drug discovery companies to iterate faster and bring therapies to patients more efficiently.”
The $52 million Series A funding will enable Medra to scale its operations, expand its customer base, and build a state-of-the-art laboratory in the Bay Area. This facility will house approximately 100 robots, capable of running experiments autonomously around the clock and generating continuous data to improve Medra’s models. The company has also announced plans to host private tours of its San Francisco facility in January 2026, offering potential partners a firsthand look at its transformative technology.
“ Medra is addressing a critical bottleneck in the pharmaceutical industry: the inefficiency and fragmentation of preclinical workflows. By unifying robotic execution with AI-driven optimization, the company’s Continuous Science Platform offers a fundamentally new approach to scientific research. This closed-loop system not only accelerates the pace of experimentation but also enhances the quality and reproducibility of results, making it a game-changer for early-stage drug discovery. Medra’s focus on physical AI sets it apart from competitors who rely solely on either automation or machine learning, positioning the company as a true innovator in the life sciences. ” Saasverse Analyst comments
Saasverse Insights
Medra’s rise reflects a broader trend in the AI and SaaS ecosystems: the integration of robotics and AI to create intelligent, self-improving systems. This convergence is particularly impactful in domains like drug discovery, where the stakes are high, and traditional methods are both time-intensive and resource-consuming. By enabling continuous, autonomous experimentation, Medra is not only advancing the state of pharmaceutical research but also laying the groundwork for similar breakthroughs in adjacent fields such as synthetic biology and materials science.
As the demand for AI-driven laboratory automation grows, Medra’s ability to scale its platform and forge strategic partnerships will be key to maintaining its competitive edge. The company’s emphasis on modularity, natural language interfaces, and real-time adaptability ensures that its technology will remain relevant as scientific needs evolve. With its innovative approach and strong financial backing, Medra is poised to redefine the relationship between AI, robotics, and scientific discovery, driving a new era of precision and efficiency in research.