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§ Private Profile · Valencia, Comunidad Valenciana, Spain
Quibim is a technology company.
Quibim develops advanced software tools that extract quantitative information from medical images, enhancing clinical decision-making and patient outcomes. The company's core offering applies artificial intelligence techniques to various imaging modalities, including MRI, CT, and PET, to derive novel data and generate actionable predictions. This technical approach transforms raw medical scans into precise insights, serving both healthcare providers and the life sciences industry.
Founded in 2012 by Luis Marti Bonmati and Ángel Alberich-Bayarri, Quibim emerged from extensive research in imaging biomarkers. The founders recognized the untapped potential within medical imaging data, aiming to convert qualitative visual assessments into robust, quantitative metrics. Their initial work laid the groundwork for a platform designed to standardize and interpret complex medical imagery, a critical need in personalized medicine.
The company primarily serves hospitals through its Software-as-a-Service platform and collaborates with life sciences organizations via value-based partnerships. Quibim's vision is to transform healthcare by providing AI-guided precision solutions, continually advancing its product line with new predictive imaging biomarker panels. This forward-looking strategy aims to deliver more accurate diagnoses and personalized treatment pathways.
Quibim has raised $59.0M across 2 funding rounds.
Quibim has raised $59.0M in total across 2 funding rounds.
Quibim has raised $59.0M across 2 funding rounds. Most recently, it raised $50.0M Series A in January 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Jan 1, 2025 | $50M Series A | Asabys Partners, Buenavista Equity Partners | Adara Ventures, Amadeus Capital Partners, Future Shape, Kfund, Lockheed Martin Ventures, Scalebridge Capital, Jonathan Milner, Sahin Boydas | Announced |
| Jul 1, 2020 | $9M Seed | Adara Ventures, Amadeus APEX Technology Fund | Amadeus Capital Partners, BITKRAFT Ventures, Future Shape, Kfund, Scalebridge Capital, Jonathan Milner | Announced |
Quibim has raised $59.0M in total across 2 funding rounds.
Quibim's investors include Asabys Partners, Buenavista Equity Partners, Adara Ventures, Amadeus Capital Partners, Future Shape, KFund, Lockheed Martin Ventures, Scalebridge Capital, Jonathan Milner, Sahin Boydas, BITKRAFT Ventures.
Quibim is a Valencia, Spain-based biotechnology company specializing in AI-driven quantitative imaging biomarkers for precision medicine. It builds a cloud-based, tissue-agnostic platform that extracts radiomics and deep features from medical images (MRI, CT, PET), harmonizes data across devices, and integrates with electronic health records (EHR) and multi-omics data to enable actionable predictions for disease detection and treatment.[1][2][3] Key products include QP-Insights® for research and data management, QP-Prostate® for prostate MRI analysis with PI-RADS compliance, QP-Brain® for early neurological disease quantification (Alzheimer’s, multiple sclerosis), and QP-Liver® for liver disease assessment, serving over 150 hospitals, 70+ sites, and biopharma firms like Merck Serono, Novartis, and Janssen.[1][2][5][6] The company solves radiologist workload issues—exacerbated by rising demand—and variability in imaging data by automating analysis, reducing misdiagnosis, and accelerating clinical trials through biomarker discovery and patient stratification, with strong growth including 5X revenue in 2022 and a $50M funding round in early 2025.[2][3]
Quibim was founded in 2012 by Ángel Alberich-Bayarri, a biomedical engineer whose early research at La Fe Health Research Institute in Valencia focused on using imaging to measure biological changes, addressing challenges like image variability across scanners that required constant algorithm tuning.[2][3] Spun out from the institute, the company initially developed radiomics tools before shifting to AI integration between 2015-2020 to automate workflows and create predictive models, marking its entry into commercial operations in 2020.[2][5] Early milestones included the Lanzadera accelerator (2015-2016), European Commission grants for its Quibim Precision platform, and certifications like ISO 13485, ISO 27001, CE class IIb, FDA 510(k), UKCA for products like QP-Prostate, QP-Brain, and QP-Liver.[1][5][6] Pivotal traction came from building the world’s largest de-identified imaging biobank (10M+ images, 50K+ cancer patients) and partnerships with biopharma, evolving from research spinout to global player with offices in Spain, New York, Cambridge, and Madrid/Barcelona.[1][2][5]
Quibim stands out in medical imaging AI through these key strengths:
Quibim rides the AI-precision medicine wave, where exploding imaging data volumes (fueled by full-body scans and multi-omics) meet radiologist shortages—9/10 report workload spikes per McKinsey—demanding automation for early detection over symptom-based diagnosis.[2][3] Timing aligns with regulatory momentum (FDA/EU clearances) and biopharma’s push for efficient trials amid high failure rates, positioning Quibim to lead "imaging-based personalized medicine" via biomarkers and digital twins that predict drug response and enable whole-body screening.[3][6] Market tailwinds include AI's maturation for healthcare (post-COVID imaging needs) and $50M funding to scale globally, influencing the ecosystem by standardizing radiomics, accelerating drug development for partners like Novartis, and shifting diagnostics proactive—potentially reducing misdiagnosis and costs across 150+ sites.[2][3][6]
Quibim is primed to dominate AI medical imaging with expansions into whole-body digital twins and full-body analysis, leveraging its biobank for novel biomarkers in oncology, neurology, and beyond. Trends like generative AI for imaging synthesis and real-world evidence from EHR will amplify growth, especially as biopharma prioritizes responder identification amid trial costs. Expect deeper pharma integrations, new clearances (e.g., more organs), and potential unicorn trajectory post-$50M raise, solidifying its role in transforming imaging from descriptive to predictive—echoing its origin in taming data chaos for precision patient outcomes.[3][6]