10 February 2022 | Thursday | News
Image Source : Public Domain
Machine learning and artificial intelligence are reshaping discovery and optimization of drug candidates. This synergistic new partnership between Excelra’s GOSTAR and X-Chem’s RosalindAI will enable unique and powerful tools to predict small molecules, chemical, biological, and physical properties, accelerating 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. X-Chem’s RosalindAI delivered superior and actionable results than other similar analyses using well-known publicly available datasets. The results confirmed that RosalindAI’s proprietary models are designed specifically to address challenges in chemical datasets, and when trained on the larger, more diverse GOSTAR data, yielded models twice as better than models trained on other datasets.
X-Chem SVP Noor Shaker says: “AI is revolutionizing 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 unique 360⁰ view of over 8 million small molecules. The content in GOSTAR is meticulously curated with a proprietary QMS-ISO certified process. It captures the most up-to-date view of the chemical space with information on chemical structures and their biological properties, including binding, in-vitro, in-vivo, ADME, Tox, and physicochemical properties.
X-Chem’s RosalindAI is a leading AI platform for preclinical drug discovery. It provides a seamless interface to build best-in-class AI models for chemical design and optimization. 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.