Leveraging healthcare intelligence to increase diversity of oncology clinical trials

The Food and Drug Omnibus Reform Act has recently established regulatory requirements for diversity, including sponsors�� responsibility to submit a diversity action plan to the FDA, which provides a rationale for enrollment goals and plans to achieve them. To achieve these diversity requirements, sponsors may benefit from a holistic approach that incorporates evidence-based analysis, patient centricity, and strategic solutions throughout clinical development. Healthcare technology and data availability now offer innovative solutions to mitigate barriers to enrolling representative populations.

To achieve a representative clinical trial population, sponsors should first perform an evidence-based analysis of the disease population and their geographic distribution. Prevalence-to-participation ratios and participation consumption ratios can help identify the study-appropriate target and underrepresented populations. Once diversity goals are defined, sponsors must then develop a detailed action plan with patient centricity strategies to achieve those goals.

One strategy for enrolling more representative populations requires a reexamination of a trial��s eligibility criteria, which may be based on outdated restrictions or disproportionately exclude certain demographic groups. An ASCO survey found 56% of physicians agree that the complexity and number of eligibility criteria are compromising clinical trial recruitment. Sponsors may benefit from adopting AI tools that assess real-world data to identify eligibility criteria that are relevant to real patient populations and identify opportunities to open eligibility criteria to a broader range of patients without impacting safety.

Sponsors may also need to provide site-level support to optimise the engagement of underrepresented communities. For example, experienced and academic centers may need guidance on engaging these communities through community outreach and their extended networks. Training site staff on cultural sensitivity and implicit bias can also help lessen barriers that might impact patient willingness to participate in a trial.

Additionally, site staff who reflect the community demographics can also improve patient trust. In fact, presented at ASCO��s 2022 meeting indicated that black cancer patients are more likely than non-black patients to prefer learning about clinical trials from someone with shared experience, particularly those with shared race or ethnicity. Community oncology sites that participate in clinical trials may help studies reach more diverse patient populations.

Sponsors also may benefit from using AI, when insights from AI supplement and support engagement with groups already working with potential patients �C including community clinics and advocacy organisations. Appropriately trained AI can provide insights into the diversity of investigator staff at sites and their surrounding communities, and into which sites are likely to recruit patients based on their connectivity and proximity to target populations. Leveraging AI in this way has demonstrated significant benefits for 91��ϡ�s clinical studies, improving demographic and geographically aligned site selection, recruitment rates, and start-up timelines.

By taking a multifaceted approach that includes data analysis, community engagement, and broader inclusive trial practices, sponsors can support more representative patient populations in oncology clinical trials. In turn, diverse trials enhance the validity of trial outcomes, and ensure that the benefits of oncology clinical research are more equitably distributed.

To learn more about 91��ϡ�s services and how we can support you in increasing diversity in your oncology clinical trials, please contact us.

This article was first published on Clinical Oncology Daily on 2 June 2024.

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