ZebiAI and TB Alliance Announce Collaboration to Apply ML-Driven Discovery Platform to Tuberculosis Targets

TB Alliance to leverage ZebiAI’s platform to discover novel probe compounds for important tuberculosis targets, with options for drug discovery

ZebiAI, a biotech company focused on improving human health by powering machine learning (ML) to source novel targets and discover new therapeutics, announced a strategic collaboration agreement with TB Alliance, a not-for-profit organization dedicated to the discovery, development and delivery of better, faster-acting and affordable tuberculosis drugs.

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ZebiAI’s platform utilizes vast datasets of high-quality protein-small molecule interaction data and proprietary machine learning (ML) algorithms, applied in partnership with Google Accelerated Science, to discover novel compounds from commercial and virtual libraries. Through the collaboration, TB Alliance will provide funding for ZebiAI to develop small molecule probes against key tuberculosis targets. TB Alliance also has the right to exercise options for further ML-driven discovery work on each target in collaboration with ZebiAI.

The collaboration is part of ZebiAI’s Chemome Initiative, which utilizes its ML-driven discovery platform to further characterize the function of understudied proteins and validate novel therapeutic targets in partnership with the research community.

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Rick Wagner, CEO of ZebiAI, said, “We are thrilled to work with TB Alliance to help drive the development of more effective tuberculosis treatments. The collaboration is an ideal match for our vision of improving human health by utilizing machine learning to quickly source probe compounds against important or understudied targets and then continuing to apply our ML-driven drug discovery engine to optimize those compounds into drugs.”

Nader Fotouhi, Chief Scientific Officer of TB Alliance, said, “TB Alliance is committed to using cutting edge technology and establishing new partnerships to improve treatment for people with TB. Machine learning, applied to small molecule therapeutics, has the potential to become an important component of drug discovery in the future. We are excited to collaborate with ZebiAI to apply this technology to critical tuberculosis targets. With new drug candidates, we can expand our pipeline of novel regimens that can help bring the TB pandemic under control.”

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