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Clinical trials often struggle with slow recruitment, poor patient and site experiences, and a lack of diversity; challenges that continue to delay timelines and limit the quality and relevance of results. While these issues are often treated as separate problems, they are closely connected and frequently stem from decisions made early in trial design and delivery.
In our three-part series, featured in Applied Clinical Trials, we discussed how applying behavioral science and service design can help address these challenges more effectively. From improving patient recruitment and retention, to reducing friction in patient and site experiences, to designing trials that better reflect real-world populations, the articles highlight how understanding human behavior can uncover root causes and inform more practical, scalable solutions.
Below is a short synopsis of each piece along with a link to the full articles on Applied Clinical Trials.
Article 1: Patient Recruitment in Clinical Trials
Recruiting patients for clinical trials is one of the most costly and challenging aspects of drug development, often because of decisions made early in trial design and study startup. A major issue is the lack of input from clinicians who will conduct the trials or from patients who will take part in them, leading to protocols that may be scientifically sound but don’t align with real-world healthcare. Early application of behavioral science, UX research, and service design can identify barriers such as unrealistic administrative burdens, invasive procedures, inconvenient appointments, and insufficient support.
Additionally, during study startup, selecting the right sites is crucial, yet feasibility assessments often miss key practical realities, such as clinic accessibility and staff capacity. Observing real workflows and co-designing processes with site staff can help improve efficiency and reduce frustration. Again, a behavioral science approach can reveal patient motivators and barriers, enabling strategies to build trust, simplify processes, and alleviate practical burdens, addressing recruitment challenges at their source.
In this article, you will learn:
- Why patient recruitment has become one of the biggest bottlenecks in drug development
- How challenges during recruitment often originate earlier in trial design and study startup
- What pharma companies can do to identify and address these issues earlier
- How behavioral science and service design can improve recruitment speed, diversity, and outcomes
Read the full article on Applied Clinical Trials
Article 2: Patient and HCP Experience in Clinical Trials
Clinical trials often struggle because they become overly complex, resulting in a poor experience for both patients and sites. Challenges such as confusing information, unreliable technology, and inefficient processes can accumulate and affect site engagement and patient willingness to continue. Standard operational metrics like screening and enrollment rates act only as surface-level indicators, revealing problems only after they have already developed and failing to explain the underlying experiences driving them.
Addressing these challenges begins with better measurement. Collecting data on patient understanding, satisfaction, convenience, and technical failures, combined with qualitative feedback, helps reveal both what is going wrong and why. Sharing these insights across teams ensures that issues are addressed rather than repeated in future trials.
Behavioral science provides evidence-based methods to improve how patients and sites interact with trial materials, tools, and processes, while service design helps optimize workflows and reduce predictable points of failure. Together, they enable practical, low-risk improvements that can be piloted and scaled.
In this article, you will learn:
- Why overly complex clinical trials create poor experiences for patients and sites
- The limitations of current methods for measuring patient feedback
- How friction from technology and processes impacts recruitment, retention, and trial success
- How behavioral science, research, and service design can reduce burden and improve outcomes
Read the full article on Applied Clinical Trials
Article 3: Diversity in Clinical Trials
A recent study found that only 6% of pivotal phase III trials reflect the racial and ethnic makeup of the U.S. population. The implications are serious: differences in safety, effectiveness, and risk across populations may go undetected, limiting confidence in how well treatments work for everyone.
Barriers to participation are both structural and behavioral. Trust remains a major challenge, particularly among underserved communities with historical reasons for mistrust in medical research. Building trust requires long-term investment and visible representation among investigators and care teams. Accessibility is another key factor. Trials are often conducted at large medical centers far from underserved populations, creating logistical barriers. Expanding trials into community settings or enabling remote participation can significantly improve access.
Behavioral science helps uncover how people think, feel, and make decisions about participation, including perceptions of risk, mistrust, and practical constraints. Rather than relying on assumptions or surface-level changes, effective strategies involve co-designing solutions with communities, testing interventions, and tailoring approaches to specific populations. As a result, clinical trials can better reflect and serve the populations they aim to treat.
In this article, you will learn:
- Why diversity in clinical trials is critical for generating valid and generalizable evidence
- The current gaps in representation and their implications for drug safety and effectiveness
- Why regulatory efforts alone are not enough to solve the problem
- How behavioral science and service design can help address the root causes of underrepresentation.
Read the full article on Applied Clinical Trials
To read more about how behavioral science approaches can help pharma overcome common challenges read our two-part series on the value of behavior mapping here.
