X-Chem and Excelra link up on drug discovery

Published: 14-Feb-2022

The partnership, utilising Excelra’s GOSTAR and X-Chem’s RosalindAI platforms, will improve capabilities to predict small molecules, chemical, biological, and physical properties

Excelra and artificial intelligence specialist X-Chem are partnering to accelerate preclinical drug discovery and aid scientists to find drug candidates for currently hard-to-drug targets.

The partnership, utilising Excelra’s GOSTAR and X-Chem’s RosalindAI platforms, will improve capabilities to predict small molecules, chemical, biological, and physical properties, designed to accelerate the time and resource-intensive stages of drug discovery from hit identification to preclinical candidate selection.

“This is a perfect match between two of the best solutions for some hard challenges in drug discovery,” said Norman Azoulay, Director, Scientific Products. “We’re convinced this partnership will immediately help drug developers fuel their pipelines better.”

GOSTAR’s proprietary data set underwent rigorous analysis and large-scale ML model building to predict drug solubility in a recent joint study. RosalindAI delivered superior and actionable results than other similar analyses using well-known publicly available datasets, X-Chem claims.

X-Chem SVP Noor Shaker said: “AI is revolutionising drug discovery in ways never thought possible before, and RosalindAI is leading the way with AI tools that are accurate, scalable, and robust, enabling a transformation in preclinical drug discovery. Our collaboration with Excelra will enable us to leverage GOSTAR data and enable AI in ways never possible before.”

GOSTAR provides a 360⁰ view of more than 8 million small molecules. The content is curated through a proprietary QMS-ISO certified process. RosalindAI is an AI platform for preclinical drug discovery. It has also been successfully applied to the design of a novel chemotype for challenging targets and for the accurate prediction of chemical activities and properties, X-Chem says.

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