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Desupervised & RG Discovery Receive Eurostars Grant

Desupervised and RG Discovery have partnered to develop AI-powered drug discovery tools, supported by a Eurostars R&D grant.

Dr. Michael Green
Dr. Michael Green

February 22, 2022

Copenhagen, Denmark and Lund, Sweden. Two companies have partnered to develop AI-powered drug discovery solutions with support from a Eurostars R&D grant.

In this collaboration, Desupervised and RG Discovery are creating robust AI-based tools to help organisations reduce cost and time in small-molecule drug research and development.

Desupervised will contribute its proprietary AI platform featuring Bayesian deep learning models that quantify uncertainty on every prediction, improving molecular structure predictions. These models require less training data and allow incorporation of domain expertise, streamlining the discovery process. The resulting tool, called AId (artificial intelligence-based tool for Drug Discovery), aims to be accessible even to smaller organisations.

RG Discovery brings integrated drug discovery services, having advanced several small-molecule drug candidates toward clinical trials in CNS and oncology.

From the partners

Johan Evenäs, RG Discovery CEO, stated: “This collaboration aligns with our strategy to become a leading, sustainable European drug discovery company,” noting the partnership will enhance their service offerings through AI technology.

Michael Green, Desupervised CEO, commented: “We leverage RG Discovery’s deep knowledge about drug discovery to build a new democratised drug discovery tool.”

About the companies

RG Discovery AB is a Scandinavian provider of integrated drug discovery contract research supporting life-science companies.

Desupervised ApS is a Nordic AI and ML research company specialising in industry-specific Bayesian models, built on our open-source probabilistic programming language Borch.

Dr. Michael Green
Dr. Michael Green

CEO, Founder

Founder and CEO of Desupervised, where we co-develop uncertainty-aware AI solutions with companies. Theoretical physicist with 25 years building neural networks and a vocal advocate for Bayesian methods and uncertainty quantification.

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