At the 2026 SCOPE Summit, Dr. Eliav Barr, Head of Global Clinical Development and Chief Medical Officer at Merck & Co., joined Ken Getz of the Tufts Center for the Study of Drug Development to discuss the evolution of the pharmaceutical pipeline and the operational hurdles facing modern research. The dialogue centered on Merck’s response to one of the largest patent cliffs in the industry’s history, driving a critical need for new medicines across therapeutic areas including oncology, immunology, and ophthalmology. The session underscored that while the scale of research has expanded, the path forward requires a disciplined return to clinical trial simplicity and the purposeful adoption of artificial intelligence.
The Paradox of Choice: Addressing Data Saturation and Complexity
A central theme of the discussion was the industry-wide tendency toward excessive data collection, which often complicates operations without adding proportional scientific value. The panel indicated that a significant portion of the data gathered in clinical trials is never utilized in final analyses. This just in case mentality—driven by fears of regulatory queries or payer demands—creates an immense burden on both site staff and patients. Experts suggested that as data precision moves from 99% toward 99.99%, the return on investment diminishes while data cleaning and management costs escalate exponentially.
The discussion highlighted that trial complexity is often avoidable, yet it persists due to institutional inertia and the reuse of legacy protocol templates. To combat this, Merck has initiated a mandate for teams to justify every procedure within a protocol, often setting modest reduction targets of 7% to 10% for procedures that do not directly address a study’s primary objectives. By forcing teams to prioritize critical questions early in the design phase, the organization aims to reduce the poking and prodding of patients and streamline the data management lifecycle.
Enhancing Patient Access Through Community Empowerment and Practical Design
Addressing the persistent challenge of patient enrollment, the panel shifted focus to the geographical and systematic barriers within the United States. While specialized NCI-designated cancer centers are often congested, a vast majority of patients receive care through community oncology practices. The discussion emphasized that Merck is increasingly focusing on empowering these community sites by ensuring clinical trials mimic the standard of care. By aligning trial requirements with the existing workflows of busy community offices, sponsors can improve participation rates and reach a more diverse patient population.
Barr illustrated that trial design must account for the physical and logistical realities of the participants. For oncology patients, who are often immunocompromised and fatigued, the requirement for frequent hospital visits is a significant deterrent. The session highlighted the strategic move toward subcutaneous and oral medicines, which limit the time patients must spend in clinical settings. Furthermore, practical supports such as daycare services and meal vouchers were cited as historical examples where minor logistical adjustments significantly boosted enrollment in diverse or middle-income regions. The emphasis remains on walking the protocol to ensure that the patient journey is feasible and respectful of their time and health status.
AI as a Catalyst for Operational Efficiency and Quality Control
The conversation regarding technology moved beyond speculative gimmicks to focus on citizen AI—tools that provide immediate utility to clinical scientists and clinical research associates (CRAs). The panel indicated that Merck is leveraging AI to automate manual tasks, such as summarizing trial team meetings and creating a central common truth for trial data. These incremental gains in efficiency, when multiplied across thousands of employees, represent a substantial shift in organizational productivity.
Beyond administrative automation, the discussion underscored the role of AI in complex document generation, including informed consent forms, Investigator Brochures (IBs), and Clinical Study Reports (CSRs). On the analytical side, the experts highlighted the use of AI for proactive signal generation, focusing on detecting systematic errors in data collection, identifying safety signals, and uncovering subpopulation effects. This predictive capability extends to site selection, where AI tools are being refined to predict site behaviors and capacity, ensuring the right drug reaches the right investigator at the optimal time.
Future Outlook: Translating Innovation into Public Health Impact
The future of clinical research, as outlined in the session, depends on the industry’s ability to rebuild public trust and demonstrate the tangible value of science. The discussion noted that while awareness peaked during the pandemic, trust has recently declined, requiring a more empathetic and transparent approach to communication. Panelists emphasized the importance of meeting patients where they are, which involves addressing skepticism with clear, non-hierarchical answers and acknowledging the fallibility inherent in the scientific process of trial and error.
Looking ahead, the clinical research enterprise faces the challenge of balancing high-tech innovation with the need for simplified, real-world relevance. The final takeaways suggested that the most impactful drugs are those developed through simple, robust trials that can be easily implemented in everyday healthcare settings. By focusing on needle-moving therapies and reducing ornate trial designs that may skew hazard ratios without offering true population benefits, the industry can better translate scientific breakthroughs into improved global health outcomes. The session concluded with a call for stakeholders to maintain strategic foresight, prioritizing scalability and collaboration to ensure the sustainability of the drug development ecosystem.
Moe Alsumidaie, MBA, MSF, is founder and Chief Editor of Vanguard Publications, which publishes Clinical Trial Vanguard, Pharma Vanguard and BullScope, and Head of Research at CliniBiz. He has two decades in clinical trial operations and data science, with earlier roles at Genentech, Abbott Vascular and Stanford University Medical Center, and is a guest lecturer in clinical trial sciences at Rutgers University.
