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Collaboration aims to Integrate AI drug discovery

A collaboration between two laboratory software companies aims to integrate synthesis prediction with functionality to design and optimise small molecule discovery.

Optibrium, a developer of software and AI for small molecule discovery, and PostEra, a biotechnology company developing machine learning (ML) technology for preclinical discovery, announced a collaboration to integrate Optibrium’s StarDrop platform with PostEra’s Manifold software.

StarDrop’s suite of drug discovery software enables compound design, optimisation, and data analysis. The integration of Manifold’s retrosynthesis ML capabilities allows users to identify the best scalable synthetic routes.

Aaron Morris, Chief Executive Officer, PostEra, commented: “This collaboration with Optibrium is an exciting opportunity to provide drug discovery scientists with the best possible tools to overcome key challenges in preclinical workflows. By integrating our innovative software products, we hope to make a meaningful impact for patients worldwide.”

Founded in 2019, PostEra’s approach has already attracted high-calibre collaborations, with institutes such as Pfizer and the National Institutes of Health teaming with PostEra on discovery projects. With this integration, PostEra joins Optibrium’s growing list of technology collaborators, including Collaborative Drug Discovery and Certara.

Matthew Segall, Chief Executive Officer, Optibrium, said: “We are delighted to collaborate with PostEra, whose team demonstrates an impressive focus on scientific rigour that strongly aligns with our core values. The combination of StarDrop with Manifold’s retrosynthesis capabilities showcases Optibrium’s ongoing commitment to providing our users with the latest and most innovative technology, delivering a comprehensive AI drug discovery solution that will help scientists further their R&D projects.”

Manifold, a subset of PostEra’s broader medicinal chemistry platform, is a powerful retrosynthesis software that uses ML algorithms to select the best scalable routes for compound synthesis from accessible building blocks, complemented by an intuitive user interface. To streamline project timelines, starting materials that are readily available to purchase can be identified through dynamic connections to contract research organisations. Together, StarDrop and Manifold aim to deliver data flow across the design, optimisation, analysis, and synthesis planning, enabling users to quickly identify and produce high-quality, synthetically accessible compounds in the discovery and development of new therapeutics.


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