Tech startup Converge Bio secures $25M funding from top investors and industry leaders

AI-Powered Drug Discovery: Converge Bio Leading the Way

Artificial intelligence is revolutionizing the field of drug discovery, with pharmaceutical and biotech companies increasingly turning to AI to streamline research processes and improve success rates amidst rising costs. Over 200 startups are now vying to integrate AI into research workflows, attracting significant interest from investors. One such company making waves in the AI-driven drug discovery space is Converge Bio, which recently secured a new round of funding as competition in the industry heats up.

Based in Boston and Tel Aviv, Converge Bio specializes in leveraging generative AI trained on molecular data to help pharma and biotech companies accelerate drug development. The company recently closed a $25 million oversubscribed Series A funding round, led by Bessemer Venture Partners, with participation from TLV Partners, Saras Capital, Vintage Investment Partners, and executives from Meta, OpenAI, and Wiz.

Converge’s approach involves training generative models on DNA, RNA, and protein sequences and integrating them into the drug development workflows of its clients to expedite the process. CEO and co-founder Dov Gertz explained in an interview that the platform spans various stages of the drug development lifecycle, from target identification to manufacturing, clinical trials, and beyond, offering support for experiments at each stage.

The company has already introduced three AI systems tailored to different aspects of drug development: antibody design, protein yield optimization, and biomarker/target discovery. These systems are designed to work seamlessly within the workflows of pharmaceutical and biotech companies, eliminating the need for clients to piece together different models themselves.

Since its inception, Converge has completed over 40 programs with more than a dozen pharmaceutical and biotech partners, expanding its operations across the U.S., Canada, Europe, and Israel, with plans to enter the Asian market. The team has grown significantly, now comprising 34 employees, up from just nine in November 2024.

The surge of interest in AI-driven drug discovery is evident, with notable collaborations and advancements in the field. Eli Lilly’s partnership with Nvidia to build a powerful supercomputer for drug discovery and the Nobel Prize-winning AlphaFold project by Google DeepMind developers are just a few examples of the industry’s momentum.

Reflecting on the industry’s growth, Gertz highlighted the shift towards data-driven molecular design and the diminishing skepticism surrounding AI’s role in drug discovery. Converge’s innovative approach, combining generative and predictive models to enhance outcomes for partners, has been well-received, paving the way for broader adoption across the life sciences sector.

While acknowledging the potential of large language models (LLMs) in drug discovery, Gertz emphasized the importance of training models on biological data to truly understand complex molecular interactions. Converge’s strategy involves utilizing a variety of AI architectures, including LLMs, diffusion models, and traditional machine learning, tailored to specific use cases.

Looking ahead, Gertz envisions Converge Bio as the go-to generative AI lab for life science organizations, complementing traditional wet labs with computational tools for hypothesis generation and molecule design. The company’s mission is to drive innovation and efficiency in drug discovery, ultimately delivering better outcomes for the industry as a whole.

This article has been updated to include information on the number of customers served by Converge Bio.