Trial Library and AON Partner to Enhance Cancer Clinical Trial Access with AI-Enabled Matching Technology
核心洞察
Trial Library (搜索) has partnered with American Oncology Network (搜索) (AON (搜索)) to implement AI-enabled clinical trial matching and patient navigation across 10 locations in three states, expanding access to oncology trials.
The collaboration has already accelerated trial enrollment by identifying dozens of eligible patients for solid tumor (搜索) trials within the first quarter since implementation.
By streamlining the trial identification process, the partnership reduces administrative burden on healthcare providers while connecting more cancer (搜索) patients with potentially life-changing innovative therapies.
Trial Library (搜索), a leader in AI-enabled clinical trial matching and patient navigation for oncology, has formed a strategic partnership with American Oncology Network (搜索) (AON (搜索)) to enhance patient identification and recruitment for cancer (搜索) clinical trials. The collaboration, announced on March 12, 2025, aims to expand access to innovative cancer therapies through clinical trials for patients across community oncology settings.
The partnership integrates Trial Library (搜索)'s technology into three AON (搜索)-affiliated practices spanning 10 locations across Missouri, Ohio, and North Carolina. This implementation enables oncologists to more efficiently identify eligible patients and connect them with appropriate clinical trial opportunities.
Addressing Barriers to Clinical Trial Participation
"Clinical trials are essential to advancing cancer (搜索) treatment, yet many patients face barriers to participation," said Katie Goodman, RN, vice president of clinical research at American Oncology Network (搜索). "Partnering with Trial Library (搜索) streamlines the trial identification process, reducing the burden on providers, and ensuring more patients have access to innovative therapies that could change their lives."
Despite the critical importance of clinical trials in advancing cancer (搜索) treatments, patient recruitment remains a significant challenge in oncology research. Barriers to participation include lack of awareness, geographic limitations, and complex eligibility criteria that make matching patients to appropriate trials difficult for busy clinicians.
Early Success in Patient Identification
The implementation of Trial Library (搜索)'s patient identification platform has already shown promising results. In the first quarter since launch, the system has identified tens of eligible patients for solid tumor (搜索) trials across AON (搜索) locations, including trials for breast and lung cancer (搜索) patients.
This early success demonstrates the potential of AI-enabled matching to address the persistent challenge of under-enrollment in oncology clinical trials. By automating the complex process of screening patients against trial eligibility criteria, the technology allows clinical staff to focus more on patient care and less on administrative tasks.
Transforming Community Oncology Research
The collaboration represents a significant step forward in how community oncology practices engage with clinical research. Traditionally, clinical trials have been concentrated at academic medical centers, limiting access for patients treated in community settings where approximately 80% of cancer (搜索) care is delivered in the United States.
Trial Library (搜索)'s technology is embedded within Oncology Hematology Associates (Missouri), Zangmeister Cancer Center (搜索) (Ohio), and Messino Cancer Centers (搜索) (North Carolina). This integration allows for seamless identification of potential trial candidates within existing clinical workflows.
Technology-Enabled Patient Navigation
Beyond just identifying eligible patients, the partnership also leverages Trial Library (搜索)'s patient navigation capabilities. This component helps guide patients through the often complex process of clinical trial participation, addressing questions and concerns that might otherwise prevent enrollment.
The navigation platform serves as a bridge between identification and enrollment, ensuring that more of the identified patients actually participate in trials for which they are eligible. This comprehensive approach addresses multiple points in the patient journey where traditional trial recruitment often fails.
Expanding Equitable Access to Innovative Therapies
AON (搜索), founded in 2018, has rapidly expanded to include more than 290 providers across 21 states. The organization has made expanding access to quality care a cornerstone of its mission, with a particular focus on addressing disparities in cancer (搜索) care.
This partnership with Trial Library (搜索) aligns with AON (搜索)'s commitment to health equity, as it helps ensure that innovative therapies being tested in clinical trials are accessible to a broader and more diverse patient population. Historically, clinical trial participants have not adequately represented the diversity of cancer (搜索) patients, limiting the generalizability of research findings.
Future Implications for Oncology Research
If successful, this model of AI-enabled trial matching and patient navigation could be expanded across AON (搜索)'s entire network, potentially transforming access to clinical trials for patients in community oncology settings nationwide.
The collaboration between Trial Library (搜索) and AON (搜索) represents a significant step toward addressing the persistent challenge of clinical trial recruitment in oncology, with potential benefits for both current patients seeking access to cutting-edge treatments and future patients who will benefit from the medical advances these trials help develop.