Quibim Raises $50M Series A to Transform Medical Imaging with AI-Driven Biomarkers

Quibim, a healthtech pioneer in AI-powered imaging biomarkers, has announced the completion of its $50 million Series A financing round, marking a significant milestone in its mission to revolutionize precision medicine through advanced imaging technologies.

The company's growth trajectory has been remarkable, with patient analyses through its products surging 168% quarter-on-quarter, driven by multiple regulatory approvals and strategic global partnerships. Quibim's technology is currently deployed across more than 170 leading institutions worldwide, including prestigious healthcare centers such as Mass General Brigham and Stanford.

At the core of Quibim's innovation is a comprehensive suite of AI-powered imaging solutions, including the regulatory-cleared QP-Prostate for enhanced cancer diagnosis, QP-Brain for neurological disease detection, and QP-Liver for automated diagnosis of diffuse liver diseases. The company's QP-Insights platform manages one of the world's largest imaging datasets, processing over 100 million medical images and serving as a crucial resource for biopharmaceutical companies and research consortiums.

Quibim has established strategic partnerships with industry leaders to advance its technology. Notable collaborations include Philips for AI model integration into MR scanners, Merck KGaA for developing predictive imaging biomarker models in cancer immunotherapy, and Novartis for driving imaging innovation in drug development.

The Series A funding, led by Asabys, Buenavista Equity Partners, UI Investissements, and GoHub Ventures, with participation from established investors including Amadeus Capital Partners and Tony Fadell's Build Collective, will fuel Quibim's expansion into the U.S. market. This expansion focuses on establishing hospital collaborations, enhancing clinical trials, and accelerating drug development through AI-powered imaging solutions.

Looking ahead, Quibim is pursuing an ambitious vision of creating human digital twins - dynamic models that could revolutionize patient stratification and drug development success rates. The company's current efforts concentrate on developing organ and lesion-level digital twins, with plans to extend these capabilities to whole-body analysis as imaging data volumes continue to grow.

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