Technology

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.

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 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.

In this video interview from the 2026 DIA Global Annual Meeting, Angie Maurer, VP of AI-enabled clinical development at Medable, describes how digitizing protocols transforms manual amendment workflows into automated, AI-orchestrated processes—and why structured data from the start is the foundation the FDA's continuous review model depends on.

In this video interview from the 2026 DIA Global Annual Meeting, Stacy Hurt, chief patient officer at Parexel, explains how federated AI is expanding what's possible in oncology research, why the patient voice gets lost earliest in development, and why someone in every organization needs to explicitly own patient needs from the very beginning.

In this video interview from the 2026 DIA Global Annual Meeting, Angie Maurer, VP of AI-enabled clinical development at Medable, explains the three structural barriers that kept protocol digitization out of reach and why the convergence of LLMs, industry standards, and validated environments has finally changed the equation.

In this video interview, Raj Indupuri, CEO and co-founder of eClinical Solutions, describes how giving sponsors the ability to inject their own SOPs, protocols, and governance frameworks into AI systems is the key to building the trust needed for real-world adoption.

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.

In this video interview, Raj Indupuri, CEO and co-founder of eClinical Solutions, argues that study-by-study RBM is no longer sufficient and describes what enterprise-wide, AI-enabled risk and quality management looks like in practice.

In this Q&A, Robert Hummel, chief operating officer at Suvoda, discusses how agentic AI is compressing RTSM build and deployment timelines, what safeguards are needed to maintain compliance and oversight at speed, and how intelligent automation will reshape the broader clinical trial technology stack over the next decade.

In this video interview, Raj Indupuri, CEO and co-founder of eClinical Solutions, makes the case that governance and quality must be built into every stage of the trial life cycle—not enforced at database lock or submission—and what that requires from teams and technology.

From rising costs and regulatory uncertainty to persistent vaccine hesitancy, sponsors face mounting pressure to standardize operations, build community trust, and develop the behavioral capabilities needed to run vaccine trials effectively in a rapidly shifting environment.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, makes the case for moving beyond trial-by-trial planning toward cross-asset site partnerships—and explains why sites are three times more likely to share patient data when sponsors make that shift.

As clinical trials grow increasingly complex and multi-modal, the pharmaceutical industry is pivoting toward AI-driven agentic orchestrators and lakehouse architectures to untangle disparate data streams, ensure regulatory compliance, and accelerate time-to-insight.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, explains why asking sites to use different technology for every sponsor remains a major barrier to AI adoption and what a site-first approach to technology development looks like in practice.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, shares results from a Sanofi COPD study where AI-enabled sites screened patients 33% faster and achieved 100% enrollment success—including one site that had been non-performing for over 100 days.

In this video interview, Liz Beatty, co-founder and chief strategy officer at Inato, explains how AI is replacing unreliable feasibility estimates with precise, real-time patient matching—and what that means for reducing non-enrolling sites and screen failure rates.