By John J. Whyte, M.D., U.S. Food and Drug Administration
“Variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions which we know as disease.” - Sir William Osler (1849 – 1919)
Since the late nineteenth century, it has been well-known that individuals can vary widely in their responses to the same medication. Yet, accurately predicting and addressing the effects of that variability during drug development has continued to bedevil researchers, drug sponsors, and regulators.1 With the perception that too few women and minorities are enrolled in clinical trials,2 how has the U.S. Food and Drug Administration (FDA) responded to the increasing interest in patient demographic diversity? How do sex, race, and age impact the way different groups of people respond to taking the same medication? And what do pharmaceutical executives need to know about the demographic diversity of clinical trial participants in their applications to the FDA?
Over the past two decades, the FDA has taken steps to encourage greater representation of certain subgroups in trials submitted for regulatory review, and has issued several guidances for industry regarding specific populations, including pediatric, elderly, and female patients.3,4 Congress took note of this problem, and in the 2012 FDA Safety and Innovation Act (FDASIA 907) required FDA to report on the diversity of participants in clinical trials and on the extent to which safety and effectiveness data are based on demographic factors such as sex, age, and race. Section 907 also directed the agency to produce an action plan based on this review. Released in 2014, the FDA’s Action Plan to Enhance the Collection and Availability of Subgroup Data contained 27 recommendations that fell into three broad categories: 1) improve the completeness and quality of the demographic subgroup data contained within medical product applications, 2) identify barriers to enrolling members of demographic subgroups into clinical trials and utilize strategies to address those barriers, and 3) make demographic subgroup data more readily available to the public.
Drug Trial Snapshots: A Transparency Effort
Recognizing the lack of a consistently updated and readily available source for clinical trial demographics, the FDA’s Center for Drug Evaluation and Research (CDER) piloted a new transparency initiative in 2014 called the Drug Trial Snapshots. Snapshots were created to show who participated in the pivotal clinical trials used to approve a drug and stratifies the data by sex, race, and age subgroups. The snapshots also provide statements on whether there were any observed differences in safety and efficacy by demographic subgroups at the time of approval. Drug Trial Snapshots is now an established program of CDER, and FDA releases a snapshot for every new molecular entity (NME) approved (since January 2015) within 30 days of the approval date.5 Since the launch of Drug Trial Snapshots, about half a million people have visited the website. On February 13, 2017, the FDA released a report that summarizes the first two years of the Drug Trials Snapshot program, broken down by calendar years 2016 and 2015.6
Variability in Response to Drugs
Given that Drug Trial Snapshots is primarily a transparency effort to promote discussion on participation in clinical trials and variability in drug response, it is not surprising that the agency has heard from numerous stakeholders regarding the data. Some women’s health advocacy groups have suggested that the number of women need to be proportional to their representation in the population, meaning at least 50 percent of clinical trial participants need to be women. Others have argued that the proportion of Black/African Americans in a drug trial should be similar to the relative prevalence of the disease in Black/African Americans compared to other races.
While the case for prevalence or proportional representation seems to stem from a social justice perspective, from a scientific perspective, sufficient statistical power is necessary to perform relevant subgroup analysis. Variability in responses to drugs can be caused by a large number of factors, including sex, age, diet, concomitant medications, genetic traits, and many others. Drug Trial Snapshots provides some of the available data needed to evaluate these questions and performs the subgroup analyses when possible, per Congressional mandate. Other relevant factors, such as pharmacokinetics in various population groups, body mass, lipid distribution, and hepatic and renal function are also evaluated during FDA’s review to assess their contribution to variability in response. Demographics are not the only factor, but they still remain a common heuristic for grouping individuals until science adopts a richer method of understanding of how we may differ at large.
What Should Pharmaceutical Executives Know?
Collecting demographic data on sex, race, and age is critical to identifying population-specific signals. Any investigational new drug application (INDA) is required to present annual reports on the participation in clinical trials by age group, gender, and race (21 CFR 312.3321).7 As part of their marketing applications, drug sponsors are required to present both safety and effectiveness data by sex, age, racial, and any other subgroups of the population of patients treated, when appropriate (21 CFR 314.5019).8 Although there are currently no statutory or regulatory requirements for sponsors to include specific sex, race, or age subgroups as participants in clinical trials, regulations do require presentation and inclusion of analyses of demographic data in marketing applications.9
Drugs should be tested in the population they intent to treat. With the publication of a drug trial snapshot for each newly approved drug, the FDA aims to provide additional data on who participated in the studies used to evaluate the drug’s safety or efficacy profiles by demographic subgroups.
If there is a reason to believe any particular subgroup may respond differently to a drug, the studies should account for and plan, a priori, how to design a clinical trial to capture such differences. Incorporating more intensive evaluation of the multiple variables early in development, along with the current mechanistic model of the disease, may help to provide answers to questions concerning differential responses of subgroups. With a growing understanding of our individual biologic variability to drug response, these iterative “learn-confirm” cycles can help us better understand how and when biologic variability happens.10
Pharmaceutical executives should recognize that collecting and analyzing demographic data on sex, race, and age may be critical to identifying population-specific signals and a required part of their marketing applications. The Drug Trial Snapshots program provides the basic demographic details of clinical trials and what differences, if any, were found in the demographic subgroups analyzed. By providing the data to begin the conversation on what is the right number of diverse participants to include, where appropriate, the FDA is engaging with the scientific community to better understand what health variables are important to capture and may prove to personalize therapies for us beyond our basic demographics. Additional discussion is needed on ways to improve our understanding of when and why biologic variability in drug response occurs, when it should be measured, and how best to design clinical trials to capture it.
About The Author:
John J. Whyte, M.D., M.P.H., is director of professional affairs and stakeholder engagement at the FDA’s Center for Drug Evaluation and Research (CDER).