BioTech
DiCE scores $80M to roll oral IL-17 psoriasis med into the clinic


DiCE Molecules is setting its sights on the clinic. With $80 million raised from a laundry list of investors led by RA Capital Management, the company will push its lead program, an interleukin-17 (IL-17) antagonist, into a clinical trial in psoriasis and build out its preclinical programs.
“This financing will enable us to accelerate our lead IL-17 program through important milestones while advancing our other assets, including a pair of integrin inhibitors, and also to expand our pipeline using the same combination of technology and structural insights,” said DiCE CEO Kevin Judice, Ph.D., in a statement. “We believe the immunology space is underserved by current small molecule approaches and we are excited about the opportunity to advance next-generation therapeutics for this patient population.”
RELATED: Sanofi is rolling the DiCE on a small molecule R&D platform
DiCE’s pipeline is based on its DNA-encoded library (DEL) technology, which generates small molecules that target protein-protein interactions, which have long been difficult to drug.
Its lead program targets IL-17, a family of inflammation-promoting cytokines that play a role in psoriasis, psoriatic arthritis and other autoimmune diseases. Several drugs targeting IL-17A are already on the market, including Novartis’ Cosentyx, Eli Lilly’s Taltz and Bausch Health’s Siliq. But all three are monoclonal antibodies given by injection, and DiCE hopes to one-up them with an oral small molecule. UCB is working on an antibody that targets IL-17A and IL-17F, but it, too, is injected.
The series C funding, drawn from the likes of Alexandria Venture Investments, Sanofi Ventures and Osage University Partners, will also advance and expand DiCE’s preclinical work.
RELATED: Koller’s insitro snaps up Haystack to build up machine learning tech
Besides its in-house pipeline of immunology programs, DiCE is working with Sanofi on an immuno-oncology candidate. It has also teamed up with insitro to combine machine learning with its DEL capabilities.
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