Transforming clinical trial enrollment: Leveraging technology and innovation to reach patients where they are

The significant under-enrollment of eligible patients in clinical trials is a persistent challenge that has far-reaching implications for advancing oncologic care and ensuring equitable access to cutting-edge therapies (Hamel et al., 2016, Kumar et al., 2022). Despite extensive research identifying barriers to trial participation, such as structural inequities and logistic barriers, progress in improving trial enrollment remains slow. As oncology enters a new era of technological innovation, there is immense potential for electronic health records (EHR), artificial intelligence (AI), and decentralized clinical trials (DCTs) to revolutionize overall clinical trial screening and conduct. Harnessing these tools requires deliberate action: robust integration into clinical workflows, interdisciplinary collaboration, and patient-centered designs. Concrete strategies that leverage these innovations to address barriers are needed to ensure all patients—particularly those from historically underserved and geographically isolated populations—can access and participate in clinical trials.

In this month’s issue of Gynecologic Oncology Reports, Klein et al describe a quality improvement initiative to enhance clinical trial enrollment in a diverse gynecologic oncology practice in Louisiana (Klein et al., 2024). By implementing a standardized manual screening process at multiple points of care and fostering interdisciplinary collaboration, the team identified gaps in trial availability and tailored their research portfolio to better match patient needs. Despite challenges like complex eligibility criteria and resource constraints during the COVID-19 pandemic, the initiative demonstrated the feasibility of an efficient, equitable screening process to improve trial access for underserved populations. Similarly, Lara et al detailed the outcomes of a pre-screening pilot and fast-track initiative aimed at identifying and facilitating eligible patients for clinical trials with a goal of improving gynecologic cancer clinical trial enrollment among minority racial and ethnic groups. They demonstrated that leveraging a multi-disciplinary team, including financial navigators and clinical trial coordinators, is both feasible and effective in enhancing screening, particularly for eligible Black patients (Lara et al., 2024).

While these types of manual screening processes have proven effective in improving clinical trial enrollment, sustainable and scalable solutions will undoubtedly require more innovative, technology-driven approaches. With the increasing complexity of trial eligibility criteria and mounting pressures on clinical teams’ time, leveraging tools like EHRs, AI, and DCTs is likely going to be essential to streamline potential participant identification and enrollment. Lessons learned in successful manual clinical trial screening paired with emerging technologies has the potential to exponentially advance clinical trial design and accrual and more efficiently bring cutting-edge cancer care directly to the bedside.

EHRs hold vast amounts of patient data, yet their potential for clinical trial screening is underutilized. Currently, clinical research teams most often must manually sift through records to identify eligible patients, a labor-intensive process. By developing automated trial-matching algorithms and embedding clinical trial eligibility criteria directly into patient care templates, EHR systems have the potential to streamline this task, identifying eligible patients in real time based on predefined criteria such as diagnoses, staging, molecular biomarkers, and comorbidities. Additionally, EHRs have the potential to deliver clinical trial information directly to eligible patients via their EHR portals. Integration of the EHR with regularly updated trial databases would ensure clinicians have at-the-elbow awareness of available trials. Furthermore, EHRs could enable longitudinal tracking of patient eligibility, addressing the issue of established patients being overlooked as new trials open or as clinical circumstances evolve.

The integration of AI into the EHR has the potential to revolutionize clinical trial enrollment and design by analyzing vast amounts of patient data to identify individuals who may benefit from trials, even if they do not meet conventional eligibility criteria. AI-driven tools, such as machine learning and natural language processing, can analyze structured and unstructured data, such as clinical notes or pathology reports, to improve the accuracy and speed of patient screening. Additionally, by analyzing social determinants of health alongside clinical factors, AI models can identify patients facing structural barriers—such as limited transportation, financial constraints, or communication challenges—and enable healthcare teams to provide targeted support, ensuring these patients are not excluded from research opportunities. In this manner, AI can help address disparities in trial enrollment.

Finally, DCTs represent a promising solution to barriers posed by traditional trial models that require patients to travel to specific research centers. With increased utilization of the EHR and AI, DCTs can more easily leverage technology, such as telemedicine, remote monitoring devices, and local lab partnerships, to bring trials directly to patients. Remote consenting, as is leveraged in some DCTs, provides an opportunity to streamline enrollment for participants who may face logistical or geographic barriers. This model not only reduces such burdens but also improves access for historically underrepresented populations, such as racial minorities and those in rural areas (Mokshagundam, 2024). By incorporating flexible protocols, like blood draws and imaging at local centers, DCTs ensure patients can participate without disrupting their daily lives, improving both enrollment and retention.

While EHR-based technology can enhance research opportunities for patients already within a healthcare system, reaching potential clinical trial or study participants outside a healthcare institution’s EHR requires innovative outreach strategies that extend beyond traditional recruitment methods. Social media platforms, targeted online ads, and community-based outreach campaigns can effectively connect with underserved populations, including those whose insurance coverage prevents access to certain cancer centers despite living within their catchment area. These tools can allow researchers to reach individuals directly, raising awareness of clinical trials and offering pathways for engagement. Furthermore, self-consenting, as was successfully implemented in the MAGENTA randomized clinical trial for remote genetic testing (Swisher et al., 2023), highlights the feasibility of empowering participants to enroll independently. Additionally, study interventions such as in cancer prehabilitation programs (Mokshagundam, 2024) and self-collection of biospecimens (Swisher et al., 2023) can often be conducted entirely from home, minimizing the need for participant travel. By combining remote technologies with accessible communication strategies, clinical trials can improve inclusivity and ensure broader representation of diverse populations.

While technology is a powerful tool for improving trial enrollment, its success depends on human collaboration. Multidisciplinary teams and interdisciplinary teamwork are essential for implementing these innovations effectively. Improving clinical trial enrollment requires a multifaceted approach that combines technological innovation with human-centered strategies. The integration of EHRs, AI-driven analytics, DCT models, and direct-to-participant recruitment strategies all have the potential to transform clinical trials, making them more accessible and equitable. However, these technologies must be implemented thoughtfully, with continuous evaluation to ensure they address existing barriers and do not unintentionally exacerbate disparities. National organizations and stakeholders in gynecologic oncology research must invest in infrastructure, training, and collaborative frameworks to operationalize these tools. By doing so, we can ensure that clinical trials fulfill their promise of bringing cutting-edge therapies to all patients, regardless of who they are or where they live.