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Ignota Labs has been selected as one of 10 winners of the AI for Science Datasets RFP, developing transformative datasets that could underpin the next generation of AI-enabled scientific discovery.
Our proposal: a dataset to increase the understanding of the root causes of drug toxicity and how to mitigate them.
In collaboration with Arctoris, we are mapping the invisible boundaries in chemistry where a tiny tweak to the structure of a drug molecule can cause significant changes in behaviour, often resulting in unintended side effects.
We are building a first of its kind resource to define exactly where and why these changes in behaviour happen, for a selected set of kinases - important cancer targets which pose significant selectivity challenges. The goal is to enable AI drug design to accurately predict how small chemical modifications will impact polypharmacology and toxicity, turning a major clinical risk into a manageable design variable.
Thank you to Renaissance Philanthropy and Department for Science, Innovation and Technology and their Blue Ribbon Committee, including representatives from UK Biobank, Google DeepMind, Convergent Research, and Wellcome Trust.
