The patient availability conundrum

Despite tremendous scientific and medical advances, the economics of investing in drug research and development are challenging. The long-term trend suggests increasing R&D costs, lengthy development timelines, and high rates of failure. There are many factors that influence a positive outcome, from individual drug development decisions up to wider regulatory frameworks, all of which are crucial to the health of the pharmaceutical industry. In this article, we posit that patient availability and the ability to enroll volunteers into clinical studies is the most important and rate-limiting of steps. Any actions that address this bottleneck will have a hugely beneficial effect on new treatment progress.

Median enrollment rate has halved since the beginning of 2010

Clinical trials account for both the majority of time and cost of overall drug R&D. Costs quickly mount in late-stage development, where the required number of patients can run into the thousands over a prolonged treatment period. Finding and recruiting these patients is paramount, particularly as eligibility criteria for trials have tightened.

In spite of best efforts, biopharma companies are getting progressively slower at enrolling patients into clinical trials. Our analysis of Trialtrove data reveals that median enrollment performance for mid/late-stage clinical trials has dropped from 0.75 patients per site per month for studies that completed in 2010, down to just 0.31 in 2024. This analysis is specific to Phase II and III industry-sponsored trials and excludes COVID-19 research.

The decline has been consistent and persistent, with a fairly sizable drop in the most recent year ending a plateau seen during COVID-19. Not shown in the chart, enrollment rates were relatively stable prior to 2010.

Source: Citeline, Trialtrove

During this period, the R&D pipeline has grown 145% from under 10k candidates to almost 24k, as of Citeline’s most recent estimate. Furthermore, the number of companies actively involved in drug development has increased by over 200%. This expansion in R&D activities has not precipitated an accompanying increase in patient availability for clinical trials, nor any meaningful improvement in recruitment or retention. The total target accrual in the 2024 cohort of studies was just 16% larger than those from 2010, with around 750k patients now participating in mid- or late-stage studies annually. Compression in enrollment rate is the inevitable net result.

Source: Citeline, Trialtrove and Pharmaprojects

Drop in enrollment rate is consistent across therapy areas and geographies

Pharma portfolios have reshaped considerably since 2010 as novel targets have emerged and new therapies have changed disease landscapes. This means that the balance of clinical development has shifted, and enrollment rates can be highly sensitive to trial design choices. An overall drop in enrollment rate at a global level could therefore be driven by external factors, such as a pivot towards precision medicine, oncology, and rare diseases.
But as the analysis below shows, the observed drop in enrollment rate is seen across the spectrum of therapy areas and in every major geography.

Oncology clinical trials carry the slowest enrollment rates historically, but rare diseases in particular have plummeted since 2010. This perhaps indicates a degree of saturation of rare disease research in certain conditions that now have several appropriate treatment options, and also a pivot towards ultra rare diseases where patient identification is even more challenging. Recruitment rates in immunology clinical trials have also dropped sharply as new standards of care have emerged.

On the geographic level, enrollment rates for clinical trials in each of the three major biopharma continents have also steadily dropped since 2010. The typical Phase II or III study with sites in Asia, while higher than in the US or Europe, has fallen in tandem. Note that due to the global nature of late-stage clinical research, there is a degree of overlap with these samples.

Advice for sponsors to alleviate the patient bottleneck

It is clear that biopharma’s appetite for clinical research has outgrown patient availability. In such cases of demand and supply imbalances, investment must go into improving patient capacity in order to alleviate the strain on R&D budgets and therapeutic innovation. Without this, the economic equation will only worsen.

Individual sponsors can expedite their clinical research through greater investment on a per trial basis, adding more sites and intensifying outreach efforts. This can end up as a zero-sum game, limiting the pool of patients available for other research activities. Rather, in our capacity of supporting the entire clinical research ecosystem, we would distill our overarching view into five main areas of focus and advice.

• Predict success criteria during the planning process. There is a wealth of intelligence on clinical trial performance, whether that sits within an outside data provider or in a sponsor’s own experience. To this, you can add patient demographics, outcomes data, treatment paradigms, and much more. Before long, clinical teams are faced with an abundance of information that can overwhelm tasks such as protocol design and study feasibility. Rather, decision makers can work backwards using predictive algorithms trained on vast, clinically relevant datasets. This will help focus attention on the key features that drive overall trial success and reduce the number of studies that fail to provide conclusive evidence. Thus, every patient’s participation and contribution is maximized.
• Harness timely real-world data. Diagnosis is becoming more complicated than ever, particularly as precision medicine narrows how diseases are categorized, and sponsors are looking for smaller and smaller patient populations. RWD can be used in near real-time to support the identification of patients and potential matching to available clinical trials. With multiple sources of RWD and sophisticated analysis, sponsors can mirror the complexity of a study’s eligibility criteria and cast the net as widely as possible. This will help to direct as many patients as possible into clinical research as a viable treatment strategy.
• Diversify clinical research. Diversity in clinical research is critical, not least because it is good science. But more broadly, a diverse trial means going into demographics that are typically underrepresented, where patient availability is likely to be greater. This also extends to diversity among sites and investigators, going beyond the major academic centers where clinical research is concentrated. There are many more prescribers than there are principal investigators, so converting these HCPs into first time PIs broadens the research base and taps into harder-to-reach communities.
• Focus on patient-centricity. With a finite number of eligible patients, sponsors must ensure that every patient counts. This may mean decisions that make the logistics of running a trial more difficult or expensive, but improve the patient proposition. Decentralization of certain activities can reduce patient burden, while the number of site visits and endpoints must be clinically rational. A degree of patient drop-out is inevitable, but sponsors must ensure that retention for non-clinical reasons is maximized. Ongoing engagement throughout the trial is just as important as during recruitment efforts.
• Create a positive research experience. For a patient, the decision to join a trial is not taken lightly. The process may mean deviating from standard of care, giving up time and energy for procedures and site visits, with associated travel, accommodation costs, and potential loss of income. Thus, sponsors should consider how to respect patient involvement by creating a positive research experience. This may include practical steps such as stipends and reimbursement through to how study information is communicated. Particularly when the trial completes, there is a responsibility to disclose results in an appropriate way with patients and their HCPs. In turn, this creates a feedback loop whereby HCPs will be more likely to engage with and recommend their patients for clinical trials in the future.

Daniel Chancellor

VP, Thought Leadership | Norstella