Designed for Performance, Part 1: Recruitment Is a Design Outcome, Not an Operational Failure

For more than a decade, patient recruitment and retention have been persistent hurdles in clinical research and are consistently cited as the biggest operational challenges with running clinical trials.¹ A recent industry survey shows that enrollment delays outpace budget constraints and start-up delays. In 2012, reports indicated that nearly 80% of clinical trials failed to meet their enrollment timelines, and 50% of research sites either enrolled only a single patient or under-enrolled relative to expectations.^2,3 Retention has not fared much better. Across all clinical trials, an average of 30% of randomized participants do not complete the study, and 85% of studies fail to retain sufficient participants.⁴

And yet, operational effort has never been higher. Clinical operations and patient recruitment teams work relentlessly to rescue delayed enrollment. Digital outreach has scaled. Recruitment vendors have multiplied, promising powerful artificial intelligence-driven solutions. Decentralized models have expanded. Sites are working at capacity and report bandwidth constraints. Sponsors are investing heavily in mitigation strategies.

But delays persist. Over a decade later, in 2023, 85% of trials were delayed, with nearly a quarter experiencing major delays exceeding 40% of their original timelines.⁵ If we are trying harder than ever — arguably achieving operational excellence — why are results not fundamentally improving?

Because recruitment and retention are treated as operational execution challenges. Enrollment struggles because we are attempting to operationally compensate for what are fundamentally design decisions. Many of the most influential drivers of recruitment performance are embedded long before enrollment begins. Enrollment outcomes are not rescued operationally; they are engineered structurally. We have optimized execution without redesigning the system that determines execution success.

Performance is locked in before first patient in: the protocol effect

By the time first patient in occurs, most determinants of recruitment success are already fixed:

• Eligibility criteria are finalized.
• Visit schedules are defined.
• Procedures and assessments are locked in.
• End point strategy is set.

Operational teams inherit these constraints; they do not create them. Recruitment success is less about downstream effort and more about upstream structure.

The escalation of complexity and burden constrains enrollment success

Meanwhile, the number of sites and patients required for Phase III trials has nearly doubled over the past decade.⁶ Development pipelines have narrowed to focus increasingly on oncology, personalized medicine and rare diseases, leaving sponsors competing for both sites and eligible patients. Clinical operations teams are expected to manage accelerated development timelines, driven in part by increasing trial complexity and shorter periods of market exclusivity for new drugs.

At the same time, protocol complexity further exacerbates these constraints. Over the last decade, both the number of eligibility criteria and the total number of procedures performed in clinical trials have increased significantly, with procedures rising more than 60%. A participant in a Phase III trial may undergo nearly 300 procedures, up to 40% of which support exploratory or non-core end points. Participants can also expect to spend more than two hours in clinic for approximately half of their visits.

As procedures increase, enrollment durations lengthen and studies experience lower enrollment and completion rates.⁷ As end points multiply, site workload expands. As eligibility criteria intensify, screen failure rates rise.

While some pressures — such as shrinking exclusivity windows — are external, many are deliberate design choices. Clinical operations and recruitment professionals are optimizing within boundaries that were never designed with recruitment feasibility as a primary objective.

What we are experiencing is not an operational shortfall — it is a burden-by-design system behaving exactly as specified.

Evidence that design drives performance

Data increasingly reinforce that performance is not random but engineered:

• Protocols with lower participant burden have shorter study cycle times.
• Protocols with lower participant burden have lower dropout rates.
• Phase II and III trials incorporating decentralized elements have demonstrated higher screen-to-randomization rates and more participants per site than trials without such elements.
• Investigators who report positive experiences with a sponsor enroll twice as many patients as those reporting neutral or negative experiences.

The common denominator is intentional design. Recruitment performance is the measurable output of design decisions.

A recruitment-by-design operating model

To make meaningful progress, recruitment and retention planning must move systematically upstream into protocol development. A recruitment-by-design operating model must be embedded within protocol governance from the earliest stages of development. It should include:

• Early patient and site insights: Systematically embed patient and site staff perspectives into protocol design and co-develop recruitment strategy.
• Burden benchmarking and KPIs: Standardize the measurement of participant burden across the industry; quantify burden during protocol development and tie it to performance KPIs.
• Eligibility discipline: Require a quantified burden score and recruitment feasibility review, scrutinizing restrictive eligibility criteria to meaningfully shorten recruitment timelines.
• Intentional site experience strategy: Because enrollment performance correlates with Investigator experience, activate a deliberate site engagement strategy.
• Continuous recruitment risk monitoring: Conduct recruitment risk assessment and mitigation in parallel with protocol drafting.

Elevating enrollment feasibility into the design governance process is not merely an operational improvement — it represents a structural shift in how we design research and define accountability in clinical development.

The next decade of performance gains in clinical research will not come from additional recruitment vendors, more digital advertising or more mitigation plans. They will come from designing trials that patients can realistically join and sites can realistically execute. Until enrollment feasibility becomes a design requirement rather than a mitigation activity, performance will remain predictable.

Recruitment is not failing. It is performing exactly as designed.

Rebecca Johnson, PhD, is a clinical research recruitment and inclusion executive and strategist. In her most recent role, Johnson led the clinical trial recruitment and diversity, equity, and inclusion functions at SPARC. Prior to that, she held several leadership positions within IQVIA’s patient recruitment team, including advising pharmaceutical sponsor teams with their efforts to achieve more diverse trial populations. Johnson has a master’s in public health and a doctorate in health sciences. Her doctoral dissertation research focused on increasing access to clinical trials for historically underrepresented populations.

References

1. Studna, A. (2025, October). Applied Clinical Trials’ 2025 state of the industry survey. Applied Clinical Trials, 34(4). https://www.appliedclinicaltrialsonline.com/view/applied-clinical-trials-2025-state-industry-survey
2. Institute of Medicine (IOM). (2012). Public engagement and clinical trials: New models and disruptive technologies: Workshop summary. Washington, DC: The National Academies Press.
3. Clinical Trials Arena. (2012). Clinical trial delays: America’s patient recruitment dilemma. Clinical Trials Arena. https://www.clinicaltrialsarena.com/features/featureclinical-trial-patient-recruitment/
4. Pilastro, M., Fernando, J., Ivanov, B., Alexandre, K., Vaidis, M., Burgher, S., & Gunther, C. (2022, May). Transforming the clinical trial patient experience. Accenture. https://www.accenture.com/content/dam/accenture/final/a-com-migration/r3-3/pdf/pdf-158/accenture-clinical-trial-offering.pdf
5. Flanigan, J. & Evers, J. (n.d.). How customer-first clinical trials cut complexity and delays. Bain & Company. https://www.bain.com/insights/how-customer-first-clinical-trials-cut-complexity-and-delays/#
6. Smith, Z. (2025, Sept). Current industry trends, and new and emerging opportunities for optimization [Conference session]. Evolution Summit, Carlsbad, CA.
7. Getz, K., Botto, E., Arques, A., Galuchie, L., Sanmiguel, N., Sheetz, N., &Smith, Z. (2026). Insights informing strategies for optimizing the collection of clinical trial data. Therapeutic Innovation & Regulatory Science, 60(2) 563-574. https://doi.org/10.1007/s43441-025-00899-4