Increase your Chance of Diverse Clinical Trial Enrollment with IRT

Ensuring a diverse enrollment in clinical trials is one of the key missions our industry must take. There is evidence that not all racial groups are equally represented in clinical trials. One study led by Dr. Jonathan Loree and Dr. Kanwal Raghav analyzed 230 oncology clinical trials that took place between 2008 and 2018, that resulted in FDA-approved cancer drugs. If you have not read this study, I encourage you to do so. The results speak for themselves: “Whites, Asians, blacks, and Hispanics represented 76.3%, 18.3%, 3.1% and 6.1% of trial participants, respectively, and the proportion for each race enrolled over time changed nominally (blacks, 3.6% vs 2.9% and Hispanics, 5.3% vs 6.7%) from July 2008 to June 2013 vs July 2013 to June 2018. Compared with their proportion of US cancer incidence, blacks (22% of expected) and Hispanics (44% of expected) were underrepresented compared with whites (98% of expected) and Asians (438% of expected).”

There are multiple actions sponsors can take to improve clinical trial patient diversity, but once those measures are in place, how can they control and monitor their progress toward meeting enrollment goals?

This is an area where IRT can help. For many clinical trials, IRT is the first point of patient entry into the trial. The first IRT transaction usually captures essential patient demographics and generates the patient number, which will be the patient identifier for the duration of the trial. IRT is also the system that controls enrollment in the right treatment arm, the right cohort, or the right trial phase. It is relatively easy for an IRT system to collect data points that can help determine if a patient fits in a certain targeted category, such as a certain age range for example. The same functionality can be applied to ensure the compilation of patients enrolled in a trial matches the demographic that best represents disease incidence rates.

This concept can only work if the IRT collects each patient’s racial/ethnic group as a parameter at the time of screening or enrollment/randomization. This requirement can be tricky, as some sponsors may choose not to collect this data point. However, I believe we need to put this in perspective with what a lack of diversity means: without the right level of diversity, we are not exploring if subgroups of patients respond differently to treatment and we are releasing new medicines based on results that do not correctly represent the future patient population.

Enrollment cap vs stratification