linical trials have grown increasingly sophisticated and increasingly difficult for participants and investigative sites to support. Protocol complexity, frequent visits, nonessential procedures, and growing demands for data can create substantial burdens that limit who is able and willing to participate. At the same time, advances in basic science, precision medicine, and artificial intelligence are accelerating therapeutic discovery faster than traditional evidence-generation systems can efficiently evaluate them.

The typical phase 3 clinical trial collects an average of 5.9 million data points, up 11% annually since 2020, even as the proportion of eligible adults participating in clinical trials has remained stubbornly low. Access to clinical trials is therefore not simply a question of enrollment. It is a layered challenge that spans awareness of available studies, healthcare provider support, eligibility, ease of entry, the quality of the trial experience, and the time and financial burden placed on participants. Barriers at any of these points can limit participation, but many are created by decisions made long before a patient is approached.

A 2024 report summarizing Tufts CSDD findings provides supportive context, noting that the burden from questionnaires, lab and blood work, procedure frequency, and site visit requirements has increased and is linked to participant dropout.

The challenge is to redesign evidence generation so that research is easier to access, more representative, and better integrated into patients’ care, without compromising the quality of evidence needed for regulatory decision-making.

Improving enrollment, retention, representativeness, and the overall patient experience requires redesigning how evidence is generated, embedding research into clinical care where appropriate, reducing unnecessary burden, and aligning trial complexity with the specific regulatory and scientific question being addressed. Productive, collaborative patient engagement must be a commitment that runs from protocol and development planning through to sharing findings back with the participants who made the research possible. The evidence suggests that meaningful patient engagement results in tangible benefits, and pragmatic approaches may improve both efficiency and generalizability without compromising evidentiary rigor where the science supports it.

The Full Scope of the Access Challenge

Each layer of the challenge—from awareness of available studies and provider support to eligibility, ease of entry, and the participant experience—involves different stakeholders, and success at one depends on what happens at the others. So does the commitment to return useful results to the communities that made the research possible. Structural barriers across these layers contribute to lower enrollment and retention among underrepresented populations, making early patient engagement important for equitable trial design. As described in “Modernizing Site Quality in Clinical Trials,” early patient and site engagement improves feasibility and reduces operational burden.

What these layers share is their sensitivity to protocol design decisions made long before a single patient is approached. Trial complexity, unnecessary procedures, overly restrictive eligibility criteria, and excessive data collection frequently become barriers to participation, particularly in community settings and historically underrepresented populations. Bringing patient voices into the protocol planning stage, rather than consulting them after a design is substantially developed or, worse, finalized, has measurable consequences for study performance.

Research by the Tufts CSDD and the Clinical Trials Transformation Initiative found that a modest investment of $100,000 in a patient engagement activity during protocol design, such as a patient advisory board review, could yield a financial return more than 500 times that amount. This return is driven by avoided amendments, improved enrollment and retention, improved operational efficiency, better adherence, and earlier product launch. Protocols developed with patient input were also more extensively simplified and had timelines closer to or exceeding plan. These findings align with ICH E6(R3), which emphasizes participant-focused design and proportionate oversight as core principles for modernized clinical trials. That is a compelling argument for prioritizing and resourcing patient engagement from the outset.

Quality by Design and Regulatory Engagement as Enablers for Innovation

Broader participation in clinical trials can offer clear benefits: more generalizable results, stronger enrollment and retention, and more robust product labeling. EMA’s real-world evidence framework similarly stresses the role of real-world data in supporting regulatory decision-making and improving the relevance of evidence across diverse patient populations. Recent FDA guidance, particularly the emphasis on Quality by Design (QbD) embedded in ICH E6(R3), combined with the demonstration projects of FDA CDER’s Center for Clinical Trial Innovation (C3TI), gives the industry a practical mechanism to minimize perceived and actual risks and a path to be able to do this as a repeatable practice.

Two initiatives stand out for advancing study design and increasing patient involvement:

• FDA’s Streamlined Trials Embedded in Clinical Practice (STEP) project targets the integration of research into routine care settings—the most direct path to reducing participant burden and expanding trial participation beyond academic medical centers. Early C3TI-facilitated discussions suggest that cross-functional sponsor-regulator engagement can help clarify expectations around oversight, endpoint collection, and inspection readiness.
• Selective Safety Data Collection (SSDC) addresses the tendency toward overcollection of safety data for mature development assets and marketed medicines that contributes disproportionately to site and patient burden without a corresponding benefit to evidence quality. This approach aligns directly with fit-for-purpose data collection principles reflected in ICH E19 and ICH E6(R3).

What these two opportunities have in common is that they are better suited for medicines that have a reasonable amount of evidence behind them, whether from earlier indications or from large clinical trial databases where significant risk has already been discharged. Pragmatic elements such as expanded eligibility and simplified procedures and endpoints expand the potential for participation and representativeness. The potential to profile the medicine in a real-world setting is valuable to inform clinical care. SSDC, in particular, is a focused approach: it collects only the data needed to assess core safety parameters in medicines that are already well characterized, which streamlines the burden on both patients and investigators.

The ongoing VICTORION-2-PREVENT cardiovascular outcomes trial incorporated a selective safety data collection strategy. This enabled reduced visit frequency more closely aligned with routine clinical practice while maintaining appropriate safety oversight and regulatory engagement.

Sponsors’ concerns about greater heterogeneity compromising a study’s ability to meet its primary endpoint are increasingly addressable through good study design and early regulatory engagement, which turns that heterogeneity into a manageable, expectable risk. FDA, EMA, and PMDA have all signaled the need to modernize evidence generation, with growing emphasis on real-world data, AI, and the infrastructure and data standards required to achieve this at scale, including continued regulatory harmonization across regions. The importance of consistent oversight structures is further illustrated in a recent article on governance variability in clinical trials, which examines how governance differences across regions can slow adoption of innovative, patient-centered evidence-generation models. ICH E19 further reinforces harmonization by defining a selective approach to safety data collection, enabling sponsors to reduce unnecessary burden while maintaining participant safety and evidentiary integrity.

Incentives Drive Real Change

In any serious discussion of trial access, the incentive structure deserves scrutiny. A 2024 analysis found that many trial procedures do not support core endpoints and instead add participant and site burden, highlighting the need for more feasible and patient-centered protocol design. For sponsors, performance metrics centered on speed—protocol approval, first site initiated, first-patient-in—compete directly with the investment of time and resources required to finalize study designs that take full advantage of programs like STEP and SSDC. Feasibility, representativeness, and operational sustainability are still too often secondary considerations rather than core measures of trial quality and development success. For healthcare providers, overly complex studies with high investigator and patient burden are simply not feasible for many community-based practices—settings that often have access to the right patients and capable investigators, but lack the infrastructure, operational support, or prior sponsor relationships needed to participate repeatedly in research.

Better tools alone will not expand access if the incentives governing development do not reward their use.

For access to improve at scale, three shifts are necessary:

• Sponsors should build outcome metrics for enrollment feasibility, representativeness, and study performance into development team accountability frameworks. These belong alongside cycle time as core success criteria, not as supplemental key performance indicators.
• Health systems and providers need investment and support in training and data infrastructure to participate as genuine partners in research, particularly in communities that are capable but currently underserved. The government also has a role in building both the infrastructure and the incentives to modernize evidence generation, and public-private partnerships that establish models while retaining quality and addressing public health priorities can accelerate that work.
• Technology and platform companies should move toward standards-based interoperability and reusable infrastructure models that reduce study-by-study customization, improve data portability, and enable research workflows to operate more seamlessly within healthcare delivery systems.

The PACT consortium, facilitated by Tufts CSDD, drew on data from more than 100 clinical trials and found that trials using virtual and remote solutions exceeded planned enrollment timelines while also improving patient recruitment and diversity. Yet deploying these capabilities at scale requires a platform approach grounded in data interoperability and digital workflow adoption. FDA’s Digital Health Technologies guidance supports remote data acquisition in clinical investigations, while FDA’s interoperability framework reinforces safe, secure, and effective data exchange across systems.

A Call to Action Across the Ecosystem

Access to clinical trials is the front door to a learning health system, but it has to be engineered, not improvised. FDA’s learning health system initiatives reinforce that sustainable evidence generation requires intentional infrastructure investment, continuous feedback loops, and shared accountability across sponsors, regulators, and health systems. Modernizing evidence generation can advance access and rigor together. Many of the tools, technologies, and regulatory frameworks needed to improve patient access already exist. What is needed now is the resolve to apply them consistently and at scale.

Clinical trial access should be an essential design principle from the very beginning of protocol development. If we engineer research around the people and communities it is intended to serve, we can generate better evidence, develop medicines more efficiently, and build a clinical research system in which participation is a realistic opportunity for every eligible patient.