"The drug-development lifecycle has defined stages - from target identification and discovery to manufacturing, clinical trials, and beyond - and within each, there are experiments we can support,"
"Our platform continues to expand across these stages, helping bring new drugs to market faster."
"Take our antibody design system as an example. It's not just a single model. It's made up of three integrated components. First, a generative model creates novel antibodies. Next, predictive models filter those antibodies based on their molecular properties. Finally, a docking system, which uses physics-based model, simulates the t"
Converge Bio applies generative AI trained on DNA, RNA, and protein sequences to accelerate multiple stages of drug development, from target discovery to manufacturing and clinical trials. The company has launched customer-facing systems for antibody design, protein yield optimization, and biomarker and target discovery. The antibody workflow integrates a generative model to create novel antibodies, predictive models to filter candidates, and a physics-based docking system to simulate interactions. Converge raised an oversubscribed $25 million Series A led by Bessemer Venture Partners, with participation from TLV Partners, Vintage Investment Partners, and unnamed executives from Meta, OpenAI, and Wiz. The platform aims to shorten R&D timelines and increase success rates.
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