A clinical trial’s endpoints are the measurable outcomes used to evaluate the effectiveness of the treatment or intervention under study. They answer the question, “What is this treatment good for?”
Choosing the right endpoints can shape the entire clinical trial. When carefully selected, endpoints do far more than merely set data collection goals. They can provide a means to assess potential benefits and risks of a treatment, optimize study design, and comply with regulatory criteria.
Factors That Affect Endpoint Selection
Factors that affect endpoint selection in clinical trials include:
- The treatment or intervention being studied.
- The intended or hypothesized effect of the treatment or intervention on a condition or symptom.
- Whether treatment effects can be measured directly or require indirect measurements to predict clinical outcomes.
- Incorporation of real-world evidence.
- Available tools or methods for analyzing endpoint data.
- Regulatory requirements related to clinical evidence and data collected during trial.
In many clinical trials, these factors do not neatly align into a single set of endpoint criteria. For instance, regulatory requirements may demand that clinical trials track a certain endpoint, but the trial’s design and parameters may make that endpoint difficult to track — or irrelevant to the treatment or condition under study.
Research by Marco Caccamo, Frank E. Harrell, and Anna R. Hemnes notes additional factors that make endpoint selection challenging. Caccamo et al. focus on endpoints on clinical trials for pulmonary arterial hypertension (PAH), noting that “the changing expectations of patients, clinicians, and regulators in this evolving therapy area” complicate the choice of endpoints and the means used to measure progress toward those endpoints.
For instance, a commonly used primary endpoint in PAH trials — measuring a six-minute walking distance — doesn’t always correlate well with clinical outcomes, the authors write. Composite endpoints appear to track more accurately when patients’ conditions are worsening, but “there is no standard definition of worsening.”
These varying yet interrelated factors all affect the choice of endpoints — revealing both opportunities and challenges.
Challenges and Opportunities in Clinical Trial Endpoint Selection
Choosing clinical trial endpoints is challenging. Choosing effective endpoints, however, opens up opportunities for better data collection and analysis, as well as a deeper understanding of trial efforts and the chance to leverage available data for more effective results.
Top challenges — and opportunity sites — in clinical trial endpoint selection include orphan drugs, regulatory demands, and the need to incorporate digital endpoints.
Clinical Trials for Orphan Drugs
Orphan drug clinical trials pose a number of challenges in endpoint selection, writes Scott N. Freeman, Scientific Innovator and CEO at FF Biotherapeutics. These include:
- Small patient populations, which can impose difficulties in recruitment and retention and make it harder to ensure a statistically significant patient sample.
- Disease heterogeneity, leading to varying presentation and progression that make it harder to select endpoints that accurately portray treatment effects across the entire study group.
- Limited natural history data, which can hinder clinical trial teams’ understanding of disease progression and biomarkers.
These challenges can make it more difficult for clinical trial teams to identify relevant endpoints.
Regulatory Requirements
Regulatory demands provide a framework for shaping clinical trial endpoints. For example, the German Federal Institute for Drugs and Medical Devices states that clinical endpoints must define “which parameter (WHAT), at which time (WHEN), with which method, which device or survey instrument, etc. (HOW) will be recorded,” writes Bettina Martin, Head of Clinical and Safety Affairs at the Johner Institute.
This specificity can help clinical trial teams clarify their study endpoints. Yet regulatory requirements can also challenge clinical trial teams by demanding information that is difficult to track or has become irrelevant — particularly when a condition or its treatment is rapidly changing.
One example emerged during the COVID-19 pandemic. Endpoints that were highly relevant at the start of the pandemic, such as prevention of hospitalization and death from COVID-19, became more difficult to track as vaccination rates increased and patients developed immunity due to previous infections. “There is now a difference between what can be reasonably measured in outpatient COVID-19 clinical trials and what guideline panels require as efficacy endpoints,” write Kristian Thorlund and fellow authors in a 2023 article in Communications Medicine.
Digital Endpoints
Traditional endpoints are typically measured at clinical trial sites. Digital endpoints are clinical outcomes measured outside the clinic, through the use of wearable sensors and similar devices.
Digital endpoints make it possible to collect data in real time. They allow clinical trial teams to incorporate real-world data into clinical trials, gaining a clearer overall picture of a patient’s status and progress.
Despite their potential, most available digital endpoints-related tools aren’t widely used in pharmaceutical clinical trials, says Adam Cohen, a clinical pharmacologist researching digital endpoints at Leiden University. Two major challenges are regulatory restrictions and funding.
“The opportunities for digital endpoints are enormous. Unfortunately, the barriers are almost greater,” says Cohen.
Better Data Capture and Analysis for Endpoint Selection
One way to choose better endpoints in clinical trial design is to understand how similar studies have approached endpoint selection. By learning from existing work, clinical trial teams can select endpoints that make sense in the context of their efforts. They can differentiate more clearly between endpoints intended to answer regulators’ questions, demonstrate efficacy, or lead to further scientific hypotheses and research.
Anju’s TA Scan supports these efforts. TA Scan incorporates high-quality public data from over 450,000 clinical trials, 7.2 million publications, and 730,000 presentations occurring globally. By using TA Scan, clinical trial teams can:
- Make data-driven decisions about clinical trial endpoint selection.
- Integrate endpoint selection with other key clinical trial development tasks, like trial design, diversity strategy, site selection, and KOL identification and management.
- Drive predictability in clinical trial timelines.
- Execute precise, predictive visualizations of clinical trial outcome scenarios, allowing for improved fine-tuning of endpoint selection.
TA Scan works seamlessly with other Anju offerings, helping your clinical trial, data science, and Medical Affairs teams coordinate their efforts for clinical trial and product launch success.
It’s not always easy to choose clinical trial endpoints. Competing demands, complex trials, and regulatory boundaries can complicate the process. With access to Anju’s TA Scan data science tool, clinical trial teams can gain a clearer picture of relevant challenges and shape endpoint selection accordingly.
Images used under license by Shutterstock.com.
Authored by Elke Ydens, Associate Director of Business Solutions, Data Division
Elke Ydens, Associate Director of Business Solutions at Anju’s Data Division, brings over a decade of life sciences experience and a PhD in Biochemistry and Biotechnology from the University of Antwerp. As a Subject Matter Expert in Data Science, she adeptly addresses customer needs, leveraging her background in neuro-immunology and biochemistry. Elke remains dedicated to professional growth, contributing to industry publications, and staying updated on industry trends, while also finding success in extracurricular pursuits, formerly competing in world and European bridge championships, and more recently active in beekeeping and coaching. Connect with Elke on LinkedIn to explore her achievements further.