Spanish healthtech company Quibim (QUantitative Imaging Biomarkers In Medicine) has raised $50 million in Series A funding to accelerate its U.S. expansion and advance its AI-powered medical imaging technology. The Valencia-based company, which specializes in developing AI models for analyzing MRI, CT, and PET scans, plans to strengthen its partnerships with U.S. hospitals and pharmaceutical companies.
Key Points:
- The funding round was co-led by Spanish firms Asabys and Buenavista Equity Partners
- Quibim has over 170 global installations, including at Mass General Brigham and Stanford
- The company reported 168% quarter-over-quarter growth in patient image analysis
Founded in 2015, Quibim develops foundational AI models that analyze MRI, CT, and PET scans to extract actionable insights for disease detection and treatment planning. The company’s flagship products, including QP-Prostate (for prostate cancer detection), QP-Brain (for neurological diseases), and QP-Liver (for liver disease diagnosis), are already FDA-cleared or under regulatory review in the U.S.
The fresh capital will accelerate Quibim’s expansion beyond Europe, where it has secured key regulatory approvals and formed strategic partnerships with global pharmaceutical giants like Merck KGaA and Novartis. The company’s AI models are integrated into Philips MRI scanners, further embedding its technology into mainstream clinical workflows.
Quibim’s long-term vision includes building AI-powered digital twins of the human body—dynamic models that predict disease progression, optimize drug development, and improve patient outcomes. With over 100 million medical images processed, Quibim’s data-driven approach is positioning it as a leader in precision medicine.
“Our global expansion into the U.S. is a critical milestone,” said CEO Ángel Alberich-Bayarri. “We aim to revolutionize diagnostics and improve patient outcomes by harnessing the power of AI-driven imaging.”
With the U.S. healthcare system increasingly adopting AI in diagnostics, Quibim’s expansion could pave the way for more efficient, data-driven patient care, benefiting both hospitals and pharmaceutical companies looking to enhance clinical trials.