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Developer of ‘Physical AI Scientists’ Raises $52M

Medra’s Physical AI autonomously runs experiments end-to-end, interfacing with standard laboratory tools and instruments.

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By: Charlie Sternberg

Associate Editor, Contract Pharma

Medra, a company developing a platform for Physical AI Scientists, has announced a $52 million Series A financing led by Human Capital, with participation from existing investors Lux Capital, Neo, and NFDG, alongside new investors Catalio Capital Management, Menlo Ventures, 776, Fusion Fund, and others.

“Pharma runs millions of experiments, but most of that data can’t be reused or fed back into AI. We’re closing that loop by tying predictions to outcomes in a continuous, self-improving cycle,” said Michelle Lee, Ph.D., CEO & Founder, Medra. “To accelerate drug development, we need to link predictions directly to automated execution and feed the results back into the model. This continuous loop enables drug discovery companies to run far more experiments, iterate faster, and advance therapies with a higher probability of success.”

According to Medra, current AI lab alternatives tend to fall at one end of the spectrum, offering either traditional industrial automation without meaningful machine learning or AI-driven software without any robotic execution. Medra, on the other hand, unifies robotics, AI, and data generation into a continuous system.

Medra’s Physical AI autonomously runs experiments end-to-end, interfacing with standard laboratory tools and instruments and allowing scientists to adapt workflows through natural-language instructions. Its companion system, Medra’s Scientific AI, interprets results and co-pilots protocol improvements to enhance experimental outcomes and create a continuous learning engine.

“Medra is creating an entirely new category in biopharma R&D, one where we believe science can continuously learn and scale to create groundbreaking therapeutics with a higher chance of clinical success,” said Armaan Ali, Co-founder, CEO & Managing Partner, Human Capital.

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