New insights from leadership at A2-Ai reveal where older adults fall out of the enrollment pathway—and what the data tells us to do next.

The Missing Population in Clinical Trials

As the global population grows older, the number of adults who rely on prescription medications continues to rise. Yet individuals in their eighties and beyond remain noticeably absent from many of the clinical trials that guide modern medical decision-making. This disconnect raises serious concern: if the people who use the most medications are underrepresented, the evidence informing their treatment may not fully reflect their needs.

To better understand this gap, the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ Consortium) recently published a Brief Report titled, “Representation of Older Adult Patients in Clinical Trials” in Clinical and Translational Science. Jack Cook, Senior Vice President of Clinical Pharmacology at A2-Ai was a co-author. The investigation takes a detailed look at possible reasons for the underrepresentation and what it means for the future of drug development. The analysis drew on several complementary approaches, including a review of more than 2,700 Phase II and III trials, two industry surveys, and real-world population data.

Age Limits and Inclusion/Exclusion Criteria are Not the Main Barrier to Participation

One of the first insights that emerged is that most clinical trials are not limiting participation through formal age cutoffs. In fact, over 75% of industry-sponsored clinical trials allow participants over eighty to enroll, contradicting the long-standing belief that age restrictions are the primary barrier. The authors also assessed whether exclusion criteria unintentionally screened out older adults. Across a set of pivotal trials, factors such as kidney function thresholds were not more likely to eliminate older participants than younger ones. Even after randomization, older adults did not discontinue participation at higher rates. From an eligibility standpoint, the door is open.

Drop-Off Happens Prior to Enrollment

Where the gap becomes clear is in the comparison between individuals who qualify for a study and those who actually enroll. When the authors examined clinical trial populations alongside real-world disease prevalence, adults over eighty appeared far less often than expected across most therapeutic areas. TriNetX simulations, which applied the clinical trials’ inclusion and exclusion criteria to large, real-world datasets, confirmed that the eligibility pool of older adults is much larger than the number who make it into the randomized study population. Only in conditions dominated by older age groups, such as transcatheter heart valve disease, did enrollment reflect real-world demographics. This points to a loss of older adults before they reach formal screening.

Why Older Adults Decide Not to Participate

To understand this earlier drop-off, the study gathered information on why screened patients chose not to continue. The most frequent reasons were personal preference and physician advice rather than medical ineligibility. Many older individuals declined because they worried about side effects, felt overwhelmed by frequent study visits, or struggled to balance trial demands alongside multiple other medications. Others were discouraged by video-based visits or digital tools, which were intended to be convenient but were often less appealing to this age group. In some cases, functional limitations, transportation challenges, or a desire to avoid additional strain while managing other chronic conditions also played an important role. These subjective and logistical concerns became more common with age, suggesting that daily realities, not eligibility rules, shape participation decisions.

Creating Clinical Trials that Reflect Real Patients

For organizations engaged in clinical research and drug development, including A2-Ai, these findings highlight a meaningful opportunity. Increasing the representation of older adults requires more than adjusting eligibility criteria; it calls for trial designs that reflect the practical realities of aging. Simplifying visit schedules, offering home-based or hybrid options, reducing logistical burden, and maintaining clear communication with treating physicians can make participation more feasible for this population. Just as importantly, recognizing the influence of personal preference and physician guidance is essential. Older adults are more likely to participate when studies feel manageable, relevant, and aligned with their broader health priorities.

As this work by Dr. Cook and IQ Consortium shows, rigorous clinical pharmacology, data-driven insight, and careful study design can help ensure trial populations more closely reflect the individuals who will use these therapies. A2-Ai remains committed to contributing scientific expertise that supports safer, more effective treatments for people of all ages. Better representation leads to better data, and better data enables better therapeutic decisions for everyone.

Read the full article here: https://ascpt.onlinelibrary.wiley.com/doi/10.1111/cts.70407