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George Church-backed JURA Bio launches with $16M to bring AI to cell therapy

By her own admission, Elizabeth Wood is far from a typical biotech CEO.
Fittingly, she’s building an unconventional startup in JURA Bio, which announced…

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This article was originally published by Endpoints

By her own admission, Elizabeth Wood is far from a typical biotech CEO.

Fittingly, she’s building an unconventional startup in JURA Bio, which announced on Thursday a $16.1 million seed round to bring machine learning into developing cell therapies. Wood co-founded JURA back in 2017 alongside Julie Norville, an MIT bioengineering PhD who is JURA’s chief technology officer.

The Harvard biologist George Church is also a founder, telling Endpoints News he expects JURA to play a role in an “amazing revolution” that applies machine learning to complex libraries of drug candidates. He says JURA is one of six biotechs he has founded around that theme. Others include Shape Therapeutics for RNA editing, Dyno Therapeutics on optimizing AAV vectors, Nabla Bio for designing antibodies, and Manifold Bio for protein therapeutics.

George Church

“I’m fairly convinced that gene and cell therapy are going to be among the best therapies, period,” Church said. “They’re just smarter than any other therapy, they’re easier to program, and we’re getting better and better at it.”

Despite Church’s enthusiasm, JURA’s leaders initially struggled to break into biotech funding circles. They pitched a sweeping vision of wanting to build a suite of ML-powered methods applied to drug discovery. The impact, Wood said, would be to truly customize a cell therapy to a patient’s particular cancer or autoimmune disease. Big-name investors weren’t interested.

“I’m a bad fundraiser,” Wood told Endpoints. “We’re new to this field. We don’t have this easy story to tell. I have a strong vision of how we want to build, and the VCs are right to say my timelines and theirs don’t match up, especially at that time.”

Instead, Wood and Norville, both first-time founders in biotech, carved their own path.

Wood applied for Y Combinator, considering joining the startup incubator in 2019. While she doesn’t remember the particular terms, she remembers the feeling of looking over Y Combinator’s term sheet.

“I got the term sheet, and I was a little bit shocked,” she said. “They were asking for a lot more of the company than I was expecting.”

Early on, they attempted to fit the typical biotech mold by building JURA as a single-asset company, focusing on a multiple sclerosis cell therapy program. Big Pharma wasn’t interested, but Wood said that ultimately worked out for the best.

“That sort of freed me from the burden of realism,” Wood said. “It was crazy in what I wanted to build, and I was not willing to give up an inch of ground.”

Instead, JURA turned a vendor into an investor: Aldevron, a North Dakota-based manufacturer that Danaher bought in 2021 for $9.6 billion.

When Wood told Aldevron co-founders Michael Chambers and John Ballantyne about the Y Combinator offer, they offered to fund her startup themselves. Chambers and Ballantyne led JURA’s $16 million seed round, along with FC Capital and biotech investor Josh Elkington.

Michael Chambers

JURA’s first partnership, also announced Thursday, is with Syena, a subsidiary of the biotech startup Replay, to develop T cell receptor-based therapies.

JURA will use that cash to build its platform, specifically in mapping out the adaptive immune system. JURA is initially focusing on T cell receptors, or TCRs, analyzing how they bind with different human leukocyte antigens, or HLAs. The goal is to have a predictive map of how T cell receptors and HLAs bind, driven by generating over 100 billion T cell receptors.

JURA’s own pipeline remains under wraps, with the startup still in the early stages of drug development.

Much like currently available CAR-T therapy, autologous TCR therapy uses a patient’s own T cells as the medicine. In particular, TCRs could unlock access to a new range of cancer targets, specifically intracellular proteins.

“If you can harness it, it has extraordinary potential,” Wood said.



cell therapy



machine learning

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