Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan
In clinical trials, a staggering 80% encounter delays during the startup phase and 37% struggle to meet enrollment targets. Read more Key clinical trial statistics. These figures highlight a critical, yet often underemphasized, aspect of clinical trials—the feasibility process.
The feasibility process is essential for assessing the practicality of a clinical trial’s design, ensuring the study is prepared to tackle the challenges that may arise. Here are some key strategies to optimize the feasibility process and set the clinical trial up for success:
Engaging stakeholders early in the clinical trial process is crucial for understanding and addressing the unique needs and concerns of various groups, such as patients, healthcare providers, and regulatory bodies. For instance, the Clinical and Translational Science Award (CTSA) Trial Innovation Network has demonstrated the benefits of early stakeholder involvement in facilitating multisite trials across different regions.[1]
By establishing open lines of communication during feasibility studies, researchers can better anticipate potential challenges and address regulatory, logistical, and patient-centered issues before they become significant obstacles. This proactive approach not only ensures smoother trial execution but also improves the likelihood of study acceptance and adherence. Ultimately, engaging stakeholders early helps build trust, aligning everyone’s expectations and paving the way for more effective and successful clinical trials.
Among the key factors in assessing feasibility for clinical trials, site selection, patient recruitment, and regulatory compliance are the most vital. For this reason, conducting a comprehensive feasibility assessment should be the first step in the trial process.
Checklists designed specifically for clinical trial feasibility can serve as invaluable tools to systematically gather insights. For instance, the University of California, San Francisco (UCSF) designed a Clinical Trial Feasibility Checklist Form, which helps evaluate key components before proceeding. Similarly, frameworks like the Medical Research Council Framework also offers valuable guidance in assessing the feasibility of complex-interventions including the clinical trials. However, it’s important to note that no single checklist or framework can cater to every trial’s specific needs. The success of these tools largely depends on the user’s commitment to thoroughly following each step.[2]
Navigating the complexities of ethical and regulatory requirements is one of the most significant challenges in clinical trial feasibility. In a multinational clinical stroke trial, the median time from the first submission to a regulatory authority to the initiation of a trial site was 784 days. Longer delays in site initiation were linked to lower patient recruitment rates within the first six months after the trial began.[3]
To prevent such setbacks, it’s essential to start early and engage in thorough discussions with key regulatory bodies. These discussions help clarify the specific regulatory requirements for the trial, ensuring that ethical considerations are integrated from the outset. By embedding regulatory compliance into the feasibility studies from the beginning, trials are more likely to run efficiently, meet ethical standards, and ultimately improve their chances of success.
Among the multiple factors contributing to trial delays, patient recruitment stands out as one of the leading causes. Therefore, effective recruitment and retention strategies are essential to ensure that clinical trials meet their participant goals and yield reliable results.
One valuable approach is partnering with community-based organizations and local advocacy groups, especially when targeting underrepresented populations [4]. Similarly, flexible consent processes also play a key role. Offering simplified or electronic consent forms can make the enrollment process more accessible, encouraging more people to participate and stay involved. In addition, optimizing the study design, such as reducing visit frequency or providing flexible scheduling, can minimize participant burden and improve retention. By proactively identifying and solving these challenges during feasibility studies, clinical trials can create an environment that encourages continued participation.[5]
Patient recruitment, the leading cause of delays in clinical trials, is primarily hindered by inadequate site capabilities [6]. Therefore, choosing the right trial site is crucial in speeding up recruitment and ensuring the trial stays on track to meet its enrollment goals—an essential part of the feasibility process.
When selecting sites, it’s crucial to evaluate more than just physical infrastructure. Key factors include the site’s experience with similar trials, its recruitment capacity, and its ability to engage with the target population. The expertise of site staff, available resources, and historical performance with past trials are essential considerations. Additionally, geographic location plays a role—trials in areas with a higher concentration of the target population often see faster recruitment and better retention rates.
There are some guidelines available to help with site selection. For example, in 2017, Anahí Hurtado-Chong provided clear recommendations for optimizing site selection [6]. By following these guidelines, researchers can ensure they pick the right sites from the start, helping to avoid delays and setting the trial up for success.
In the clinical trial feasibility process, conducting pilot studies or smaller-scale feasibility studies before starting larger trials is considered best practice. These studies help researchers identify potential challenges that could arise during the main trial, offering valuable insights into recruitment strategies, data collection methods, and participant adherence.
A scoping review on HIV-related clinical trials in sub-Saharan Africa found that 70% of trials in the region were informed by pilot or feasibility studies.[7] This trend demonstrates how pilot studies can enhance the efficiency and success of clinical trials by addressing potential issues early on.
There are some innovative approaches that are shaping the future of clinical trial feasibility. For instance, technology—especially mobile and digital health solutions—is unlocking new opportunities to improve feasibility process. Furthermore, leveraging data-driven strategies, like electronic health records and digital platforms for participant engagement, streamlines trial operations, ensuring more efficient workflows and better data integrity.
Moreover, Artificial Intelligence (AI) is also playing a significant role in enhancing the feasibility assessment of clinical trials. With the help of AI tools Clinical Trial Risk Tool, researchers, Contract Research Organization (CRO), and clinical trial sponsors can more accurately predict trial outcomes, refine study designs, and detect potential problems early. This helps teams make smarter decisions about whether a trial is viable, ultimately boosting the chances of success.
A strong feasibility process is essential to the success of any clinical trial. By engaging stakeholders early, conducting thorough assessments, ensuring regulatory compliance, prioritizing recruitment, selecting the right sites, and leveraging pilot studies, researchers can minimize delays and obstacles. Emerging technologies like AI and digital tools further enhance feasibility, making trials more efficient and effective.
Hassell, L., et al., Feasibility of Connecting Regional Research Programs to National Multisite Trials Emanating From the CTSA Trial Innovation Network. Journal of Clinical and Translational Science, 2020. 4(2): p. 75-80.
Gloy, V., et al., Scoping Review and Characteristics of Publicly Available Checklists for Assessing Clinical Trial Feasibility. BMC Medical Research Methodology, 2022. 22(1).
De Jonge, J.C., et al., Regulatory Delays in a Multinational Clinical Stroke Trial. European Stroke Journal, 2021. 6(2): p. 120-127.
Davis, M., et al., Peer Academic Supports for Success: Pilot Randomised Controlled Feasibility Trial. Early Intervention in Psychiatry, 2025. 19(2).
Geerligs, L., et al., The Value of Real-World Testing: A Qualitative Feasibility Study to Explore Staff and Organisational Barriers and Strategies to Support Implementation of a Clinical Pathway for the Management of Anxiety and Depression in Adult Cancer Patients. Pilot and Feasibility Studies, 2020. 6(1).
Hurtado-Chong, A., et al., Improving Site Selection in Clinical Studies: A Standardised, Objective, Multistep Method and First Experience Results. BMJ open, 2017. 7(7): p. e014796.
Nalubega, S., et al., _The Practice of Pilot/Feasibility Studies in Informing the Conduct of HIV Related Clinical Trials in Sub-Saharan Africa: A Scoping Review. Contemporary Clinical Trials Communications, 2022. 29: p. 100959.
Guest post by Youssef Soliman, medical student at Assiut University and biostatistician Designing a high-quality clinical trial protocol is critical for the success of any study. A protocol is the blueprint that outlines every aspect of a trial. In an ideal world, a flawless protocol would require no revisions and include only essential elements. In reality, however, the average protocol undergoes 2–3 amendments and often contains excessive data collection and overly complex entry criteria.
Clinical trials have long been the foundation of medical breakthroughs, but traditional methods often stumble over slow timelines, high costs, and difficulties in finding the right participants. Artificial intelligence (AI) — a technology ready to transform this landscape by making trials faster, more affordable, and smarter. The accelerating adoption of AI in clinical trials signals a major shift in healthcare research. It is already making significant strides in transforming clinical trials.
The key advantage of adaptive clinical trial design is the convenience and flexibility of prospective planning opportunities to modify the study design, test hypotheses based on interim results and control or eliminate bias, which is not possible in conventional clinical trial design. For example, based on interim data, a model-based approach could be employed to modify or optimize Phase 2 clinical trial doses based on patient’s dose-response. This approach could eliminate suboptimal dose risk and improve the drug efficacy rate without any safety signals.
