Artificial Intelligence/Machine Learning

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.

In this video interview, Abraham Gutman, founder and CEO of AG Mednet, shares his key takeaways from SCOPE X, including a pointed caution against the idea that agentic AI can run clinical trials autonomously and why process architecture is the real entry point for AI to deliver on its promise.

In this video interview, Abraham Gutman, founder and CEO of AG Mednet, describes how AI can take on rote reasoning tasks like PHI redaction and document QA, and why offloading that work is what gives human experts the clarity to focus on genuine decision making.

In this video interview, Abraham Gutman, founder and CEO of AG Mednet, explains why decades of progress in data capture have not solved the execution problem in clinical trials, and what an operational architecture for AI actually looks like in practice.

Clinical Trials Day is an international celebration of everyone who makes medical discoveries possible. It is also an opportunity to shine a light on the innovations helping to keep research rising.

In this video interview, Sam Hinsley, statistics manager at Phastar, explains how statisticians can ensure patient data is used responsibly and innovatively across every phase of development, from rare disease to personalized medicine to AI.

Clinical development productivity improved in 2025, but gains remain fragile as end-to-end timelines lengthened again, signaling that future success depends less on individual trial execution and more on program-level orchestration, site engagement, and adaptive operating models.

From payment delays and feasibility misalignment to technology burden and AI adoption, clinical research sites are navigating a convergence of pressures that increasingly determine who sponsors work with and how well trials perform.

In this Q&A, Mark Freitas, managing director and life sciences practice lead at Alvarez & Marsal, discusses how clinical trial design has become a strategic business decision—and why small and midsize companies bear the greatest consequences when those decisions go wrong.

In this video interview, Mark Freitas, managing director and life sciences practice lead at Alvarez & Marsal, offers a measured look at where AI is genuinely accelerating upstream protocol work and why proof points of faster approvals reaching patients are still limited.

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.

In this Q&A, Krishna Cheriath, VP and head of clinical research digital data and AI at Thermo Fisher Scientific, examines how AI is reshaping clinical operations—from case intake and trial design to site burden reduction and the emerging reality of agentic AI in the workforce.

In this video compilation, industry experts share their perspectives on the operational, technological, and methodological shifts defining clinical research in 2026.

Pharma modernization initiatives stall not from lack of ambition but from expanding governance layers that distance leadership from execution, slowing decision velocity and delaying the systems integration that drives competitive advantage.

In this video interview, Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, introduces a practical augmentation scale for thinking about how AI agents will transform clinical trial roles over the next two years and why workforce planning for that shift needs to start now.

In this video interview, Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, maps the highest-impact opportunities for AI across the trial lifecycle—from smarter protocol design and enrollment matching to data collection, cycle time compression, and the emerging potential of synthetic data in rare disease.

In this video interview, Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, argues that effective patient-centered AI must go beyond direct-to-patient tools to address social determinants of health and reduce the administrative burden on sites so that investigators can focus predominantly on the patient.

In this video interview, Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, outlines the leadership priorities, team structures, and boundary-spanning capabilities that separate organizations that realize meaningful AI gains from those that struggle to move beyond the pilot stage.

In this video interview, Krishna Cheriath, vice president and head of clinical research digital data and AI at Thermo Fisher Scientific, explains how AI is being applied to case intake today and why successful adoption depends less on technology than on reimagining workflows and investing in workforce upskilling.

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.

In this Q&A, Mohammed Saeed, MD, PhD, chief medical officer at Solera Health, explores how wearable devices and continuous remote monitoring are reshaping clinical oversight, from early intervention to AI-driven pattern detection.

In this video interview, Mohammed Saeed, MD, PhD, chief medical officer of Solera Health, explores how AI models capable of analyzing continuous wearable data streams alongside broader patient information could detect subtle warning signs of deterioration that no clinician could identify alone.

Why rigorous testing and validation matter more than ever.