AI Good News: helping cancer teams find relevant clinical trials. Published 26 October 2026 Japanese retrospective study Clinician-reviewed screening No treatment benefit proven Could AI help cancer teams find patients who might otherwise miss the chance to be considered for a clinical trial? A collaboration involving Paradigm Health, Fujitsu and Japan's National Cancer Center Hospital East offers an encouraging example of that idea being investigated. The reported work uses a large language model to help review clinical information and identify records that deserve further attention. It is about supporting a difficult screening task - not allowing a computer to decide someone's treatment. Why matching patients to trials is difficult. Clinical trials have detailed eligibility rules. Relevant information can be spread across medical notes, test results and a patient's treatment history. Finding a possible match may require identifying something that has not yet been tested, as well as recognising information already in the record. An AI system that can help organise that material could give clinicians a more focused starting point. The important word is "help": a shortlist still needs clinical review, up-to-date information and discussion with the patient. What the evaluation reported. In its release dated 25 October, Paradigm Health describes a retrospective evaluation at a single Japanese cancer hospital. One analysis covered 3,027 records and identified 35 patients who needed RET testing. That is a prompt for further investigation, not confirmation that all 35 had the relevant alteration or would qualify for a trial. A separate analysis involved 540 EGFR-related patients. The system shortlisted 57, of whom oncologists prioritised 51 for further consideration. Those are different analyses with different denominators. They should not be combined into a single success rate, nor should the 51 prioritised patients be described as 51 people enrolled in a trial. Screening, not enrolment The reported figures concern historical record review, testing needs and clinician prioritisation. They do not establish trial participation, a new treatment decision, longer survival or an improvement in quality of life. Why this is still encouraging. Finding relevant information is a genuine part of medical work. A useful research opportunity can be missed if a record is difficult to search or a possible testing need is overlooked. The positive result here is that AI-assisted review produced a set of cases that clinicians could examine and prioritise. That is a narrower claim than "AI finds the right cancer treatment", but it is also a more practical one. It focuses on supporting the people already responsible for making careful decisions. What needs to happen next? This account is based on a participating company's release. A full independently assessed study and confirmation of the associated conference details were not available for verification for this article. Prospective evaluation would be needed to understand how the approach performs in routine practice: whether it misses suitable patients, how much checking it requires, whether it saves time and whether more people ultimately gain appropriate access to trials. Results from one hospital also cannot be assumed to transfer directly to another healthcare system. This is Japanese research, not evidence of an NHS rollout. The promising direction is clear nonetheless: use AI to reduce information-searching burdens, keep clinicians in charge and judge success by what happens for patients - not by the size of a shortlist. Primary company report: Paradigm Health, Fujitsu and National Cancer Center Hospital East: LLM-based clinical trial matching | - 25 October 2026. Reported retrospective results; not an independently verified clinical-outcomes study. Less hype. More real-world AI progress. Want practical AI updates without the overwhelm? Follow the UK AI Good News series, or get in touch to talk through where useful technology might fit in your business.

Ochsner Health and Paradigm Health expand access to clinical trials across the Gulf South. Aug 12, 2026, 08:00 ET The AI-native solution increased screening capacity for Ochsner patients by 41% NEW ORLEANS and COLUMBUS, Ohio, Aug. 12, 2026 /PRNewswire/ - Ochsner Health, the Gulf South's leading nonprofit academic healthcare system, and Paradigm Health, an AI-native clinical trial company, today announced the results of a system-wide partnership designed to expand access to clinical trials among Ochsner's patient population. Paradigm Health's AI-driven recruitment platform reviews and identifies potential trial patients across 47 Ochsner hospitals and 370 health centers, expanding Ochsner patients' access to trials by 41%. Clinical trials can offer patients important treatment options and renewed hope. With multiple trial sites throughout Louisiana, Ochsner had a strong foundation to expand participation across its network and connect more patients to research opportunities closer to home. To support that growth, Paradigm Health introduced an efficient way to assess patient eligibility across a large population by assisting research staff in the review process. Ochsner implemented Paradigm Health's AI-powered patient recruitment platform, which integrates within electronic health records and other clinical data sources to continuously evaluate a patient's medical record against clinical trial eligibility criteria. By using AI to efficiently and accurately evaluate a patient's eligibility, Ochsner can continuously reassess a broad group of patients as they progress through their care journey and incorporate trial recruitment into routine patient visits, making it easier for patients to learn about trials and consider enrollment as part of their hands-on care with clinicians. Deployment of this LLM-based platform has yielded meaningful results for both Ochsner's patients and clinical research staff: * 41% increase in screening capacity: By extending the reach of Ochsner's clinical research team, the platform expanded the number of patients clinically considered for trial participation, helping ensure eligible patients were not overlooked. * 3.6x increase in patients identified for future trial eligibility: By continuously reviewing patient data, the platform identified patients who were not yet eligible for a clinical trial but could become eligible as they progress through their care journey. This enabled research teams to reassess eligibility in near real time without additional administrative burden. * 75% reduction in manual effort: AI-powered patient identification and continuous eligibility screening reduced the substantial manual effort required by clinical research coordinators to identify and review potentially eligible patients. The LLM-native eligibility assessment allowed clinical staff to review eligibility of the most likely candidates only and spend more time directly engaging and supporting patients with trial enrollment. "This partnership has helped us implement a more comprehensive, integrated perspective of our patients' eligibility for trials that extends past individual clinics or specific healthcare encounters," said Nneka Ifejika, MD, chief scientific officer at Ochsner Health. "By pinpointing eligible patients sooner in their treatment path and tracking changing eligibility status, we are making our clinical trial infrastructure more efficient and expanding the reach of Ochsner's research team to consider and enroll more patients in need of trials as a care option." "Our partnership with Paradigm Health marks a fundamental shift in how we approach clinical research," said Wendy Chriss, PhD, director of clinical research at Ochsner Health. "By automating the incredibly complex, manual screening process, we are making clinical trials an inclusive, realistic care option for more patients across the Gulf South. This isn't just an operational victory; it is a major step forward in our region." "The traditional clinical trial model leaves out the vast majority of Americans who receive care in community settings, and we have built AI-enabled infrastructure to address this challenge," said Kent Thoelke, founder and CEO of Paradigm Health. "Through our work with Ochsner, we are proving that when we embed intelligent infrastructure directly into a provider's existing workflow, we can scale trial access rapidly, alleviate coordinator burnout, and ultimately accelerate the delivery of life-saving treatments to market." About Ochsner Health The Gulf South's premier nonprofit academic healthcare system, Ochsner Health, provides specialized medical services via a network of 47 hospitals and over 370 clinics and urgent care facilities. Nationally recognized for its commitment to clinical excellence and digital innovation, Ochsner served 1.6 million individuals from across the globe in 2025, supported by a dedicated team of 40,000 employees and 5,000 physicians. For additional details on Ochsner's mission to improve community health, visit www.ochsner.org. About Paradigm Health Paradigm Health has engineered an AI-powered platform to make clinical trials more accessible and efficient, so that patients, researchers, and study sponsors can maximize the impact of clinical research. Incubated by ARCH Venture Partners and backed by leading healthcare and life sciences investors, Paradigm Health aims to break down barriers across the trial ecosystem through one seamless infrastructure implemented at healthcare provider organizations, bringing potentially life-saving therapies to patients faster. For more information about how Paradigm Health is expanding clinical trial access in rural America, visit www.paradigmhealth.ai or read the comprehensive case study at https://www.paradigmhealth.ai/ochsner-case-study. In April 2026, Paradigm Health announced a landmark research collaboration with the FDA focused on advancing a new model to accelerate clinical trial execution and regulatory review. The model uses Paradigm Health's technology-enabled Study Conduct platform to allow real-time review by the FDA, by automating data collection and analysis, and streamlining the reporting of key safety and efficacy signals to trial sponsors and the FDA. SOURCE Paradigm Health, Inc.