eClinical

The FDA's launch of real-time clinical trial proof-of-concept studies signals a fundamental shift in regulatory oversight, one that most sponsors are not yet equipped to meet and that demands urgent investment in unified data infrastructure, quality-by-design practices, and protocol digitization.

From real-time evidence generation to federated AI to site-level data integration, ACT spoke with seven experts at DIA 2026 on the trends and challenges defining clinical trial operations today.

Beyond a compliance checkbox, rigorous UAT planning and execution can ensure eCOA platforms function reliably across real-world trial workflows, from study design through post-launch changes.

In this Q&A, Abraham Gutman, founder and CEO of AG Mednet, discusses why the clinical trial industry has mastered data capture but never built the execution architecture needed to act on it, how the right infrastructure changes the role of human experts, and why enthusiasm for agentic AI is outrunning what clinical trials can realistically support.

From planning one Phase III trial at a time to digital standardization on repeat.

Patient Engagement Strategies in Anti-Obesity Medication Clinical Trials: Addressing Drop Out Rate and Improving Retention

As the FDA formally recognizes real-world evidence as eligible confirmatory evidence for drug approval, sponsors face a growing imperative to build the data infrastructure, organizational alignment, and analytical capabilities needed to use RWE effectively across the development lifecycle.

Real-world evidence is shifting from a post-market footnote to a concurrent validation layer running alongside trial data, requiring organizations to build unified data environments that integrate EHRs, claims, and patient-reported outcomes on an ongoing basis rather than retrospectively.

Despite clear data quality and regulatory advantages, paper-based clinical outcome assessments persist due to cost asymmetry, trial complexity, startup timelines, and provider capability gaps, though hidden paper costs and loss of institutional knowledge often outweigh upfront electronic implementation expenses.

In this episode of the Applied Clinical Trials Podcast, Jonathan Andrus, co-CEO, CRIO, and Samir Jain, vice president of product management, healthcare data interoperability and EHR solutions, Medidata, discuss how their new partnership is enabling seamless data flow between eSource and enterprise platforms to reduce site burden and improve data quality across global clinical trials.

When using electronic clinical outcome assessments (eCOA), ensuring clear stakeholder alignment throughout the lifecycle of a study regarding data management activities is critical to success.

The execution translation gap—the failure to convert identified problems into coordinated, timely action—costs millions per trial through delayed amendments, persistent deviations, and slow site activation, yet remains addressable through aligned accountability and proactive execution management.

A collaborative study by the Tufts Center for the Study of Drug Development and CRIO identifies protocol interpretation and source document preparation as an understudied yet significant bottleneck in study start-up timelines that may hold key opportunities for efficiency gains.

Real-world data is increasingly used to optimize trial design, reduce recruitment burden, and support regulatory decisions, but adoption remains uneven due to challenges around data quality, integration, and internal alignment across functional areas.

In this Q&A, Cheryl Kole, vice president of solution strategy and commercialization at Almac Clinical Technologies, examines what it takes to build and sustain a clinical trial technology infrastructure that can keep pace with increasingly complex study designs.

As clinical trials grow more complex, the technology infrastructure supporting them is under renewed scrutiny. Across data validation, AI adoption, and site-based systems, 2026 is shaping up as a year of implementation rather than experimentation.

Moving beyond vendor evaluation to incentive design in Phase II/III rare and genetic disease trials.

Why rigorous testing and validation matter more than ever.

Public-private collaboration and structured evidence consolidation are emerging as critical enablers of regulatory-ready digital end points, helping standardize terminology, reduce duplication, and accelerate the integration of digital health technologies into clinical research and decision-making.

Insights from SCOPE 2026 highlight the industry’s shift toward connected, data-centric clinical trial ecosystems, where digital protocols, shared data, and renewed scientific rigor are driving more efficient, interoperable, and patient-focused research.

As eSource adoption expands, industry leaders are confronting new questions around AI oversight, unstructured data activation, institutional readiness, and regulatory trust. Here’s how experts say the next phase will unfold.

Global clinical development has evolved into a technology-enabled, highly regulated, and geographically diversified enterprise, as sponsors adapt trial design, partnerships, and operations to meet rising demands for scale, speed, and patient-centricity.

Persistent delays and inefficiencies in COA licensing and translation stem from limited pre-license access and fragmented processes, making a strong case for providing outcome assessment measures earlier to reduce risk and accelerate trial start-up.