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Nucleai Raises $14M in Funding Round Led by Merck KGaA's M Ventures

NEW YORK – Spatial omics informatics company Nucleai said Wednesday that it has closed a $14 million investment led by M Ventures, the corporate venture capital arm of Germany's Merck KGaA, and supported by existing investors.

The company said it will use the funds to further apply its AI algorithms in the prospective enrollment of patients in clinical trials.

The new funding follows a $33 million Series B round in 2022 and brings the company's total investments to date to $60 million.

Nucleai uses AI and machine learning to analyze pathology images and spatial data to support work in areas like drug development, biomarker discovery, and therapeutic targeting. In the context of clinical trials, it aims to use its platform to help optimize selection of trial participants.

The company previously entered a partnership with contract research organization Propath UK to develop a 30-protein panel for immuno-oncology research.

"M Ventures' investment boosts our ability to scale and deploy our spatial AI technology for patient enrollment in clinical trials and supports our work in the rapidly emerging areas of immunotherapies, antibody-drug conjugates, and bi-specifics," Nucleai Cofounder and CEO Avi Veidman said in a statement. "Our vision is that every next-generation therapeutic is accompanied with an AI-enabled companion diagnostic, ensuring that each patient's treatment pathway is informed and efficacious. This funding positions us to scale spatial AI, not just to intercept but anticipate the complex behavior of diseases."

"Nucleai’s technology stands out by being the first spatial AI tool used by pathologists for clinical trial patient selection that is directly connected to a drug development program, setting them apart from other companies," Noga Yerushalmi, investment director at M Ventures, said in a statement. "Nucleai’s biology-driven mindset and their multimodal approach, which combines traditional pathology data with spatial biology data, allows for more accurate predictions of treatment responses, aligning perfectly with our commitment to optimize speed of new therapies to reach patients."