Technology

Clinical research coordinators face early burnout driven by gaps between job expectations and operational reality, inadequate mentorship structures, and fragmented technology environments that compound insufficient onboarding and deplete resources needed to sustain engagement.

AbbVie’s head of immunology clinical development, Kori Wallace, MD, PhD, discusses how combination therapies, translational science, and emerging immune-reset approaches could usher in a new era of treatment for inflammatory bowel disease and other autoimmune conditions.

In this Q&A, Richard Graham, PhD, co-founder and chairman of the board at TruTechnologies, discusses why six decades of manual site-level processes continue to undermine clinical trial execution, what national initiatives like Operation TrialBlazer leave unaddressed, and why meaningful modernization has to start with data collected at the point of care.

Real-time AI-enabled decision-making only accelerates development when trials have coordinated operational infrastructure for randomization, supply management, and workflows capable of responding to new insights without disrupting execution or compliance.

Under-enrollment isn't news to teams running oncology trials, and the instinct is to spend more on reach. The evidence, however, says the biggest leak is something else entirely and that most recruitment budgets focus on the least valuable part of the problem.

Real-world oncology data requires hybrid curation combining clinical expertise with technology to address variability in documentation, missing data, and complex concepts like lines of therapy that are often implicit rather than explicitly recorded in EHRs.

Consumer-grade wearables offer promise for reducing trial burden and improving engagement, but accuracy and reliability vary substantially by device, measurement, and population, requiring rigorous fit-for-purpose validation and careful endpoint selection before integration into regulated research.

As agentic AI, automated data harmonization, and real-time monitoring reshape clinical development, the organizations seeing meaningful results are those that have invested in unified data infrastructure and disciplined governance rather than cycling through pilots without the foundation to scale them.

In this video interview, Raviv Pryluk, CEO and co-founder of PhaseV, breaks down the standardization and mapping work that must happen before streaming data can be analyzed meaningfully—and how AI is beginning to make that process fast enough to enable real-time monitoring at scale.

In this video interview, Raviv Pryluk, CEO and co-founder of PhaseV, explains why the gap between data collection and analysis-ready data undermines the promise of continuous trial monitoring and what it will take to close it.

AI churn—repeatedly restarting initiatives before scaling them—stems from organizational execution gaps rather than technology limitations, but agentic AI amplifies these gaps by requiring connected systems, trustworthy data, and disciplined governance from the start.

The European Health Data Space reshapes CRO operations by transitioning them from data custodians to regulated users accessing data within secure, auditable environments, enabling cross-border research but requiring substantial investment in compliance, standardization, and methodological rigor.

Clinical R&D modernization stalls through incremental optimization of individual workflows, but meaningful systemic change requires leaders to visualize structural relationships, understand hidden incentives, and identify leverage points that benefit the whole system rather than parts.

The traditional global-to-local communication model creates fragmented content through sequential adaptation, but a local-first approach using structured data and AI-orchestrated generation can embed stakeholder terminology and preferences from the start, reducing rework while improving clarity and relevance.

In this video interview, Gaynor Anders, chief delivery officer at Trialbee, outlines the organizational, budgetary, and technological changes sponsors need to make to move from study-by-study recruitment to a portfolio-level approach that keeps patients engaged across a therapeutic area.

Eligibility criteria alone rarely predict enrollment, which depends more on trust, hope, and fear, requiring relationship-based community engagement paired with behavioral readiness assessments rather than transactional outreach.

AI-enabled systems medicine could influence which populations are selected for trials, how biomarkers are validated, how products are positioned, how evidence is generated after launch, and how value is demonstrated to payers.

In this Q&A, Liz Beatty, co-founder and chief strategy officer at Inato, discusses how real-time patient data is reducing non-enrolling sites, why sponsor-specific technology remains the biggest barrier to adoption, and what a shift toward cross-asset site partnerships could mean for enrollment efficiency.

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.

In this video interview from the 2026 DIA Global Annual Meeting, Ittai Dayan, co-founder and CEO of Rhino Federated Computing, explains how data fragmentation limits AI in clinical trials, what federated learning can and cannot solve, and what sponsors actually need to deploy these approaches at speed.

In this Q&A, Raj Indupuri, CEO and co-founder of eClinical Solutions, discusses what the FDA's push toward continuous data review actually demands of sponsors operationally, why fragmented systems are the core obstacle, and how AI and real-world evidence fit into a more data-driven regulatory environment.

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.

In this video interview following the 2026 DIA Global Annual Meeting, Jonathan Andrus, co-CEO of CRIO, explains why integrating site-level data systems with sponsor oversight has remained so difficult, what a central eSource model requires to work for all stakeholders, and why the industry needs to stop waiting for perfection and start taking the step.