Company specializing in autonomous robotics and AI for life sciences research, Medra AI, announced the launch of its platform designed to automate laboratory experimentation at the physical level through robotics and reasoning systems. The platform applies AI purpose-built for laboratory environments, aiming to generate larger volumes of data and facilitate scientific breakthroughs.
The system, known as the Continuous Science Platform, operates as a self-improving closed loop composed of two integrated components: Physical AI and Scientific AI. Physical AI performs actions by automating approximately 70% of laboratory instruments already in use, equipped with visual and language understanding to capture detailed data such as image records, motion logs, and precise measurements of laboratory protocols. This includes tracking specific details such as reagent mixing times and pipette angles, creating an unprecedented dataset of experimental processes at scale.
Scientific AI interprets this granular experimental data alongside real-world outcomes, producing recommendations for protocol adjustments that Physical AI then carries out. Through this iterative feedback process, both systems collaborate to refine experimental parameters and move toward optimal methodologies. Together, the components are designed to scale experimental throughput and accelerate the pace of discovery in the life sciences.
Medra AI has established collaborations with several leading biotechnology and pharmaceutical organizations, applying its Continuous Science Platform to accelerate and enhance experimental outcomes. The platform is being used not only to increase the pace of scientific workflows but also to improve the quality and reproducibility of results.
The company has also begun publishing initial case studies with early partners. These include Addition Therapeutics, a gene-editing firm focused on RNA therapeutics where the platform is supporting RNA transfection, and Lila Sciences, a scientific intelligence platform where it is being applied to protein characterization workflows. Additional projects are underway with other partners in areas such as antibody engineering, microbial and fungal characterization, as well as cell and protein purification.
Through these initiatives, Medra AI aims to expand the role of AI-driven laboratories and provide scientists with tools to accelerate discovery and innovation across diverse fields of research.
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