Trust, of course, is essential to any clinical trial’s success. Without it, patients will not enroll. Yet, mistrust caused by historical injustices is very real within some communities. Sponsors must be prepared to acknowledge history, have candid and sensitive conversations, and apologize when necessary to dispel any myths and overcome skepticism.
Additionally, educating communities on the measures in place today, such as Institutional Review Boards (IRBs) and Informed Consent, which are designed to safeguard patient safety and ensure informed participation, can further bolster trust and confidence in the clinical trial process.
2. Define diversity. Race and ethnicity are arguably the two most recognized forms of diversity. However, sponsors may need to think about other diversity factors such as age, (dis)abilities, sex, gender identity, pregnancy, and individuals breastfeeding. Study teams should carefully determine which diversity factors are relevant to their study and then use that insight to write the clinical development plan and protocol that supports inclusive behavior for these groups.
3. Write more inclusive protocols. It’s common practice to utilize I/E criteria from previous protocols for the same product or indication. However, sponsors should discourage this shortcut in favor of continually scrutinizing previously used criteria against reasons and rates for screen failures for diverse populations. AI tools could potentially make the process faster by showing who would be excluded by different versions of the protocol.
One critical aspect of inclusivity often overlooked is the gendering of protocols. Historically, clinical trial protocols have been framed in binary terms, which can inadvertently exclude Sexual Gender Minorities (SGM). By de-gendering protocols, sponsors can ensure that all individuals, regardless of their gender identity, feel acknowledged and included in the trial process.
In addition to writing more inclusive protocols, a review of real-world data may show which trial designs are most effective at reducing barriers for desired populations. Could transportation challenges be alleviated through decentralized or hybrid models, for example?
