As trial portfolios become increasingly complex, with multiple active cohorts, biomarker-defined subgroups, and frequent recruitment updates, ensuring that every patient is consistently assessed against all relevant trial options has become an operational challenge. At institutions such as CUN, where more than 200 clinical trials are active, maintaining systematic review across the full portfolio is a priority. This collaboration introduces an AI-powered eligibility support system designed to enhance that process within existing clinical workflows.
The system leverages large language models (LLMs) to analyze structured clinical variables, including diagnosis, staging, molecular profile and prior therapies, alongside unstructured medical documentation in multiple languages. Patient information is then systematically cross-checked against protocol-defined eligibility criteria and real-time cohort status across CUN's active trial portfolio.
As a result, during routine clinical review, clinicians can access a structured list of potentially eligible trials directly within the patient record. This enables consistent, portfolio-level screening across tumour boards, pre-consultation review, and standard outpatient workflows, reducing reliance on manual cross-checking and minimizing the risk of overlooking specific trial arms or biomarker-defined cohorts.
To ensure close alignment with clinical practice, deployment follows a phased model. CUN clinicians initially evaluated the AI matching capabilities within a secure, GDPR-compliant web-based environment, using real clinical scenarios to assess performance and refine implementation.
Building on this evaluation phase, the solution has now been integrated via secure API into CUN's electronic health record (EHR) and clinical trial management systems, enabling eligibility assessment to operate directly within the hospital's governed infrastructure and existing clinical workflows.
In parallel, the collaboration will enhance referral coordination between CUN and external institutions. A CUN-branded website, powered by myTomorrows' technology, will provide referring physicians with visibility into CUN's active trials and real-time cohort status. Through this secure, GDPR-compliant environment, physicians will also be able to AI-pre-screen patients against CUN's portfolio and submit referrals with current eligibility criteria and cohort availability. By enabling eligibility review prior to submission, the model supports clearer communication, reduces administrative back-and-forth, and ensure referrals to reach CUN aligned with current trial requirements.
As myTomorrows' first partner site in Spain, CUN will provide continuous clinical and operational feedback to further refine the model, joining a growing group of leading research institutions collaborating with myTomorrows to shape the continued development of AI-enabled optimization of clinical trial operations.
"This partnership reflects the kind of collaboration we're looking to scale globally," said Michel van Harten, MD, CEO of myTomorrows. "CUN's established record in clinical research and technology adoption, combined with its expertise as a reference centre, makes it a trusted partner as we continue building more systematic and scalable solutions for clinical trial operations. We look forward to working closely with CUN, drawing on real-world clinical experience to further strengthen these models, and to expanding with partners who share CUN's commitment to more efficiently connect patients with innovative, developing treatments."
"This collaboration enables us to integrate systems capable of automatically analyzing clinical information and matching it with the inclusion and exclusion criteria of active trials," said Dr. Eduardo Castañón, clinical coordinator of clinical trials for Oncology at CUN. "It also reinforces CUN's commitment to adopting technologies that support decision making in an increasingly complex environment."
About myTomorrows
myTomorrows is a global healthtech company dedicated to breaking down barriers for patients seeking treatment options. To make this a reality, the company has built a unique and powerful proprietary technology that conducts a comprehensive and accurate search of clinical trials, and where appropriate, Expanded Access Programs (EAPs) This functionality efficiently connects patients, physicians, trial sites and BioPharma to simplify and accelerate access to drugs in development. Headquartered in Amsterdam with an office in New York City, myTomorrows has helped more than 17,700 patients and 3,000 physicians across 440+ sites in over 135 countries. mytomorrows.com
myTomorrows Media Contact:
Kate Schoenstadt
Headline Media
kate@headline.media
+972-54-7776684
About Clínica Universidad de Navarra
With nearly 4,000 full-time professionals across its campuses in Pamplona and Madrid, Clínica Universidad de Navarra is an academic hospital and a national leader in personalized medicine. Recognized for its research and teaching, the prestige of its medical staff, and its long-standing expertise in diagnosing and treating highly complex conditions, Clínica Universidad de Navarra is a high-resolution hospital, known for rapid diagnosis thanks to its multidisciplinary approach and the adoption of the latest technology, offering care across 46 medical and surgical specialties.
The Clinic is ranked among the world's top 120 hospitals in the World's Best Hospitals ranking, and among the world's top 50 cancer hospitals in the World's Best Specialized Hospitals ranking. For the eleventh consecutive year, it has also been named the private hospital with the best reputation in Spain, according to the Merco Salud ranking.
Clínica Universidad de Navarra Media Contact:
Miguel García San Emeterio
Media Relations Director
mgsanemeterio@unav.es
+34 699 70 96 34
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