SuperAPI AI Directory

Recursion Pharmaceuticals

Recursion Pharmaceuticals is an AI drug discovery company founded more than a decade ago. Its core idea is to capture cell images and train artificial intelligence to understand disease-related cellular perturbations, in order to reduce the approximately 90% failure rate of traditional drug discovery. The company has developed a drug discovery and development platform called Recursion OS, which combines automated laboratories for wet-lab and dry-lab experiments with machine learning models to form a continuous learning system. According to its introduction, the platform can run up to 2 million experiments per week and build a proprietary dataset of more than 50 PB, covering biology, generative de novo chemistry, and translational clinical tools, thereby systematically reducing drug discovery risk. The platform has produced a pipeline of potential first-in-class and best-in-class therapeutics for diseases with high unmet need, including aggressive cancers and rare diseases, and has demonstrated improvements in speed, efficiency, and cost from hit identification to IND-enabling studies. Recursion has also established partnerships with pharmaceutical companies, computational companies, and data partners to advance new drug discovery.

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Recursion Pharmaceuticals is a company focused on AI drug discovery. Its official website introduction states that the company was founded more than ten years ago, based on the idea of capturing cell images and using these images to train artificial intelligence to understand the vast unknown biological space—the cellular perturbations that drive disease—thereby using AI drug discovery to reduce the approximately 90% high failure rate of traditional drug discovery.

[Purpose] Recursion's core goal is to use data and AI to bring better drugs to patients faster. Its Recursion OS drug discovery and development platform is designed to discover and develop potential first-in-class and best-in-class therapies, with a focus on diseases with high unmet need, including aggressive cancers and rare diseases. The company states that compared with the average of traditional pharmaceutical companies, it has achieved significant improvements in speed, efficiency, and cost from hit identification to IND-enabling studies.

[Main capabilities] According to official website information, Recursion has built an AI-native data factory composed of automated laboratories, forming an end-to-end drug discovery and development engine. This engine is driven by a bilingual team of scientists and technologists, and the "lab-in-the-loop" formed by wet-lab and dry-lab experiments creates a continuous learning system of physical automation and machine learning models. The company states that it runs up to 2 million experiments per week and builds a proprietary dataset of more than 50 PB, closely connecting biology, generative de novo chemistry, and translational clinical tools to systematically reduce drug discovery risk. In addition, the platform also uses patient data to advance AI drug discovery.

[How to use] The official website provides a "Contact us today!" entry for those interested in cooperation or learning more to get in touch. For users who wish to learn more, the official website invites visitors to "Dive into Recursion's innovative approach to decoding biology" and "Join our mission." Regarding specific platform access methods, APIs, subscriptions, or usage steps, the information does not currently provide them.

[Applicable scenarios] Recursion's technology is applicable to the field of drug discovery and development, especially for diseases with high unmet need, such as aggressive cancers and rare diseases. Its strategic partnerships include collaborations with industry-leading pharmaceutical companies, technology partnerships with computational giants, and next-generation data partnerships that enhance its capabilities and pharmaceutical generative AI. The information states that these partnerships help accelerate new drug discovery and expand access toPatient impact.

[Limitations] The available information does not provide details regarding pricing, charging models, degree of platform openness, specific functional limitations, regulatory status, or guarantees of clinical outcomes. The official website mentions that REC-3565 (a selective MALT1 inhibitor) has been dosed in the first patient in a Phase 1 clinical study for relapsed or refractory B-cell lymphoma, but does not provide complete clinical data or approval status for the drug. All specific capabilities, effects, and collaboration details are subject to the official website's statements; other information has not yet been provided.