HotSpot Therapeutics plans to deploy data from Excelra's flagship product GOSTAR toward select protein targets to augment its allosteric inhibitor candidate pipeline.

The partnership aims to enhance HotSpot's drug discovery and development efforts by incorporating GOSTAR's high-quality, annotated datasets into HotSpot's machine learning (ML) and artificial intelligence (AI) models. With the integration of GOSTAR data, HotSpot will continue to advance the discovery and development of small molecule therapy candidates directed toward allosteric targets that have been difficult to drug or undruggable with traditional small molecule approaches.

GOSTAR provides a unique 360⁰ view of over 8 million small molecules and 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, toxicology, and physicochemical properties. The content in GOSTAR is meticulously curated with a proprietary QMS-ISO-certified process.

"Partnering with HotSpot Therapeutics allows for an exciting application of hit mining, as it combines AI/ML models and structure-based algorithms to accelerate both hit identification and chemical diversification in the field of allostery," said Norman Azoulay, Director of Scientific Products, Excelra.

"HotSpot's Smart Allostery^TM drug discovery platform has delivered a pipeline of small molecule inhibitor candidates directed toward difficult to drug or yet to be drugged targets in cancer and autoimmune disease," said Geraldine Harriman, Ph.D., Co-Founder and Chief Scientific Officer of HotSpot Therapeutics. "Our partnership with Excelra has the potential to expand a portion of HotSpot's AI-enabled capabilities, allowing for the further advancement of our pipeline of targets with identified natural hotspots, as well as the design of novel allosteric modulators."