Artificial Intelligence/Machine Learning

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, 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.

In this video interview, Marc Buyse, ScD, founder and CEO of IDDI, examines the most common threats to trial data reliability, including opaque methodologies, synthetic controls, and the limits of AI-driven analysis, while making the case for explainable, transparent trial design.

Closing the gender gap in data science and tech requires tackling barriers at every stage, from early education through career advancement, while actively challenging the unconscious biases that continue to hold women back.

Jonathan Andrus, co-CEO of CRIO, discusses how governance across the data lifecycle, site-focused technology adoption, and scalable AI-enabled workflows will define operational readiness in 2026.

At SCOPE Summit 2026, site leaders shared how AI is transforming feasibility, patient identification, and enrollment strategies, enabling research sites to boost performance, strengthen sponsor relationships, and deliver more precise, patient-centered clinical trials.

As sponsors navigate rising complexity, AI adoption, and global scale, outsourcing strategies are shifting toward hybrid models, deeper CRO collaboration, and function-level flexibility to support execution in 2026.

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.

Angela Zubel, chief development officer, Debiopharm, emphasizes that organizations willing to standardize data and adopt practical AI tools are already gaining efficiency, cost savings, and stronger real-time oversight across development programs.