Artificial Intelligence, BioPharma

Diagonal Therapeutics’ New Slant Attracts $128M to Reactivate Antibody Drug R&D

Diagonal Therapeutics develops agonist antibodies to treat rare cardiovascular conditions. Using artificial intelligence, the startup’s technology sorts through billions of antibody/receptor combinations to identify the ones that reactivate signaling pathways lost to disease.

In a drug discovery career spanning more than two decades, Alex Lugovskoy has seen a lot of antibodies come and go. The vast majority of them work by inhibiting a cellular function. Lugovskoy, now the CEO of startup Diagonal Therapeutics, said he long hoped someone would come up with a way to develop antibodies that activate their targets. With each passing year, no one did. So he took up the challenge himself.

Diagonal uses computational and experimental techniques to understand what happens when an antibody binds to a receptor and which binding combinations will yield the desired effect. After developing its platform for the past two years, the startup this past week pulled back the curtain on its approach. Diagonal also revealed $128 million in financing to support a pipeline that includes a lead program for a rare bleeding disorder that has no FDA-approved therapies.

Cambridge, Massachusetts-based Diagonal is not reinventing the wheel when it comes to antibodies. The company’s drugs leverage the biopharmaceutical industry’s more than 40 years of experience designing and manufacturing antibodies, Lugovskoy said. But he added that one key difference is that while Mother Nature can point the way to inhibit a target, it’s less clear how to engage a receptor to create a desired signaling effect. Each Diagonal antibody binds to two targets, bringing them together in a particular way. The many ways for an antibody to bind to various sites on receptors amounts to billions of potential combinations.

“Filtering through all these combinations was not possible without our tech, that’s what we bring to the table,” Lugovskoy said.

Alex Lugovskoy

Alex Lugovskoy, photo by Diagonal Therapeutics

Early in his career, Lugovskoy worked in drug discovery at Biogen. His experience also includes senior roles at Merrimack Pharmaceuticals, Morphic Therapeutic, and Dragonfly Therapeutics. After leaving Dragonfly in 2021, Lugovskoy said his thoughts returned to the question of why antibody research was so focused on inhibitors rather than agonists. But unlike the start of his career, more powerful technologies are now available that can be applied to agonist antibody R&D. He took the idea to Michael Gladstone, a partner at Atlas Venture. In 2022, they co-founded Diagonal, whose name is a portmanteau of the words “digital,” “agonist,” “antibody,” and “ligand.” The startup received seed financing from Atlas, Lightspeed Venture Partners, and Velosity Capital.

Diagonal spent its first year testing its technology to see what it could do. The research eventually turned to hereditary hemorrhagic telangiectasia (HHT), a disorder caused by genetic mutations that lead to malformations in blood vessels that can rupture. HHT is often first noticed when patients develop frequent nosebleeds, but the condition also poses risks to the gastrointestinal tract and artery-vein connections in internal organs, particularly the lungs, liver, and brain.

While Diagonal’s drug candidate does not fix the mutations at the root of HHT, it could address the signaling problems that lead to abnormal blood vessels. The mutated genes that cause HHT encode proteins in the TGF-beta signaling pathway. Diagonal designed an antibody that reactivates receptors in this pathway. Lugovskoy said preclinical research showed Diagonal’s drug prevented and reversed the formation of pathological vascular malformations characteristic of HHT.

A second Diagonal program is in development for pulmonary arterial hypertension (PAH), a rare form of high blood pressure affecting the arteries leading from the heart to the lungs. The disease develops as the arteries narrow, making the heart work harder and also causing breathing difficulty. Unlike HHT, there are drugs for PAH. Vasodilators, drugs that widen blood vessels, have been a standard PAH treatment for years. Recently approved Winrevair, a fusion protein from Merck, takes a different approach, trapping proteins associated with driving the proliferation of cells that build up and make blood vessels narrower. Diagonal aims to bring yet another approach to PAH with agonist antibody intended to correct the signaling imbalance that is tipped toward cell proliferation.

Lugovskoy said Diagonal’s technology can yield a working prototype of an agonist antibody in eight months or less, which is about the same time needed to develop an inhibitor antibody. As for safety, Lugovskoy said adverse effects haven’t been an issue so far, which he attributes to what these drugs are doing. Rather than creating a new signaling cascade, Diagonal is trying to restore signaling that should be there but was lost to disease.

The Diagonal technology is indication agnostic and has produced agonist antibodies for four targets. Besides the HHT and PAH programs, the pipeline includes an antibody that activates IL-18 receptor signaling to spark anti-tumor effects. The fourth target remains undisclosed. Going forward, Diagonal’s focus is rare cardiovascular diseases driven by a genetic loss of function, Lugovskoy said. Now that Diagonal has exited stealth mode, the company is looking for biopharma partners interested in applying the technology to therapeutic areas outside of the startup’s core cardiovascular focus.

Diagonal’s Series A financing was co-led by BVF Partners and Atlas. It includes the participation of Lightspeed, RA Capital Management, Frazier Life Sciences, Viking Global Investors, Velosity, and Checkpoint Capital. Most of the new capital will support the HHT program, which is funded all the way through clinical proof of concept, Lugovskoy said. He offered no timelines for that goal. The PAH program won’t get as far without additional funding.

“It gets us to IND,” Lugovskoy said, referring to an investigational new drug application. “But not much farther than that. As of right now, we are making decisions on the basis of emergent data all the time.”

Image: Juan Gartner, Getty Images