iBio acquires multiple assets of AI drug discovery partner RubrYc

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iBio is jockeying for position as a leading player in AI-powered drug discovery while also expanding its immuno-oncology pipeline after closing on the acquisition of multiple assets from its partner, RubrYc Therapeutics.

The plant-based drug developer and contract development and manufacturing organization (CDMO) said the deal shores up its ambition to bring immunotherapies to the clinic, faster.

The acquired assets include a patented system that uses artificial intelligencey (AI) to design 3D models of epitopes - which are the part of an antigen that is recognized by the immune system - to facilitate the creation of better antibody drug candidates (ADCs).

The other assets are two previously licensed candidates and three new immune-oncology therapeutic candidates, plus a partnership-ready PD-1 agonist for serious autoimmune diseases, such as systemic lupus erythematosus and multiple sclerosis.

The agreement includes a $1m upfront payment with RubrYc’s investors also eligible to receive up to $5m in development milestones over the next five years.

iBio RubrYc’s computational biology experts will also join the iBio team, working in its new drug discovery center, which is slated to open in San Diego in the coming weeks.

“Instead of relying on traditional ‘trial-and-error’ drug screening methods, we believe adding an AI-powered discovery capability to the front end of our process will enable us to bring better molecules into the clinic faster and more cost-effectively,” said Martin Brenner, iBio’s chief scientific officer. “This was clearly demonstrated with iBio’s pipeline Target 6, a mutated form of a protein expressed in a number of tumors."

RubrYc’s Discovery Engine enabled the rapid identification of antibodies that selectively bind the mutated protein, without binding the wild-type version, which is more commonly expressed in healthy tissues. "Due to the unique characteristics of the RubrYc Discovery Engine, we were able to expeditiously advance the program from the early discovery to the late discovery stage.”