Arch builds bridge to new class of medicines, leading $50M investment in the AI-enabled Vilya

Arch Venture Partners is bankrolling a biotech that could render high-throughput screening obsolete. The biotech, Vilya, starts life with a $50 million, Arch-led series A round and technology to design a new class of medicines.

Vilya grew out of work led by David Baker, Ph.D., at the Institute of Protein Design to use computational design to expand the chemical space. Armed with the technology, the Seattle-based biotech plans to design novel artificial molecules with customized biologic-like properties that can hit difficult-to-drug therapeutic targets in a broad set of indications.

According to Vilya, the molecular structures will range in size between small molecules and antibodies and have desirable druglike properties such as the ability to cross biological membranes and disrupt protein-protein interactions.

“Over the last few decades, drug developers have struggled to find natural molecules for most drug targets. Vilya’s ability to precisely design membrane permeable molecules with high structural accuracy opens the door to a new class of medicines that combine the advantages of traditional small molecule drugs and larger protein-based therapeutics,” Baker said in a statement.

Baker shared details of some of the research behind Vilya’s technology in a paper published in Cell. The paper describes the use of computational design, coupled with experimental characterization, to create membrane-permeable and orally bioavailable macrocyclic peptides.

Naturally occurring macrocycles, such as cyclosporine A and griselimycin, have pointed to the potential for the molecules to access targets that are inaccessible to small molecules and proteins. The ability of macrocycles to both disrupt protein-protein interactions and cross biological membranes gives them potential advantages over established modalities, but it has proven hard to develop new peptides. 

Baker and his collaborators addressed part of the challenge in the Cell paper with a design-build-test that entailed creating peptides containing different structural features, determining their crystal and solution structures, and evaluating their permeability. Vilya wants to build on the work, using machine learning to expand the chemical space and change how drugs are discovered.  

“Our ability to create and screen a new class of target-directed, structured molecules in silico, could transform drug discovery and development, potentially rendering high throughput screening obsolete,” Steven Gillis, Ph.D., Arch managing director and Vilya executive chair, said in a statement.