OpenEvidence Partners With Cancer Center to Expand Precision Oncology Support

OpenEvidence is expanding its oncology capabilities through a partnership with what it described as a nationally leading cancer center. The collaboration will integrate a precision oncology knowledge base directly into the company’s workflows, providing clinicians with access to expert-curated interpretations of cancer genomic alterations alongside patient-specific context and peer-reviewed evidence.

The company previewed the partnership and said the identity of the cancer center will be announced next week. According to OpenEvidence, the collaboration brings precision oncology decision support to clinicians across the United States and expands the company’s efforts in cancer care.

Precision Oncology Knowledge Base Added to Existing Oncology Resources

The new partnership builds on OpenEvidence’s existing oncology integrations. The company has a licensing agreement with the National Comprehensive Cancer Network (NCCN) that incorporates evidence-based oncology guidelines into its platform. It also integrates ASCO guidelines, figures, and flowcharts into its oncology model.

OpenEvidence said the precision oncology knowledge base from the cancer center will be incorporated directly into its specialized oncology sub-agent. According to founder Daniel Nadler, Ph.D., the oncology sub-agent has already digitized NCCN treatment algorithms.

Nadler also said the company has partnered with several nationally leading cancer centers and that additional partnerships will be announced in the coming weeks.

Company Continues Development of Specialist AI Models

The partnership is also connected to OpenEvidence’s broader effort to develop what it calls “medical superintelligence” using agentic artificial intelligence. The company’s approach involves creating specialized AI agents focused on specific clinical disciplines.

OpenEvidence has identified oncology as the first area for these specialist models. Nadler previously described the concept as digitally recreating groups of experts and specialists by combining multiple subspecialty expert models into a single system.

“In the near future, we will be rolling out the next OpenEvidence specialist agents, in genetics, cardiology and neurology,” Nadler said.

New Medical AI Models Introduced

OpenEvidence also announced a new family of medical AI models, including OpenEvidence Darwin, which is currently available in research preview.

According to the company, Darwin achieved a perfect score on MedQA, which it described as a fully independent medical AI benchmark. OpenEvidence also reported benchmark results of 72.8% on MedXpertQA, 82.7% on HealthBench Professional and 87.2% on NOHARM. Darwin is available through an application process and is currently being used by institutional partners, including the National Organization for Rare Disorders (NORD), research collaborators and accredited AI researchers at academic institutions.

The company also introduced three production models named Osler, Sackett and Snow. OpenEvidence said Osler is its fastest model and provides answers in about five seconds. Sackett is described as a deeper search model for questions that depend on the weight of evidence, while Snow is its deepest production model and conducts a full investigation of medical literature before generating a report.

According to OpenEvidence, Osler, Sackett and Snow are being rolled out to all verified users free of charge. As of September, the company reported 1.12 million licensed and verified U.S. clinicians using the platform. Nadler also said August was tracking to more than 40 million NPI-verified queries from U.S. clinicians during the previous 30 days.

OpenEvidence is expanding its role in oncology by partnering with cancer-focused organizations and integrating more specialized precision oncology knowledge into its clinical decision-support platform. The move reflects growing interest in using artificial intelligence to help physicians navigate rapidly changing cancer research and increasingly personalized treatment decisions.

The OpenEvidence oncology strategy includes access to expert-curated genomic interpretations, patient-specific context and peer-reviewed evidence. These capabilities are designed to help clinicians evaluate cancer-related information more efficiently at the point of care.

OpenEvidence and Precision Oncology

Precision oncology relies heavily on understanding a patient’s tumor biology, genomic alterations and potential treatment options. As the amount of molecular and clinical research continues to grow, physicians need efficient ways to find relevant and reliable evidence.