Technology

Participant adherence depends on readiness—a combination of knowledge, calibrated confidence, and real-world mastery—not simply on digital tools, reminders, or education, which are forms of exposure rather than preparation for sustained performance.

As imaging-heavy clinical trials grow more complex and globally distributed, sponsors are increasingly re-evaluating traditional infrastructure models, with cloud-native platforms showing potential to reduce operational burden, accelerate site activation, improve imaging quality oversight, and lower total trial costs.

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.

Limited evidence surrounds direct-to-patient clinical trial site models, despite growing literature showing that decentralized approaches can improve patient access, enrollment performance, and operational efficiency while reducing participant burden.

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.

In this video interview, Hal Green, senior solution architect and life sciences vertical lead EMEA at Loftware, discusses why sponsors must now treat disruption as an expected condition and how real-time visibility and connected systems enable faster, more adaptive responses.

In this video interview, Mark Freitas, managing director and life sciences practice lead at Alvarez & Marsal, identifies governance inertia and review cycle lag as the most underappreciated risks when AI speeds up protocol development faster than organizations can act on the insights it generates.

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.

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.

In this video interview, Nick Frenzer, general manager of site solutions at Veeva Systems, discusses why eSource has been difficult to implement at scale, how FHIR-based technology is changing that, and what Veeva eSource means for sites, sponsors, and the broader clinical trial ecosystem.

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.

Risk-based monitoring requires integrated data systems, validated analytics, and strong governance to work effectively across global trials, but sponsors face significant technical and operational challenges that demand strategic solutions and organizational alignment.

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.

Digital twin technology can reliably simulate standard-of-care treatment outcomes using historical clinical trial data, offering a practical pathway to virtual control arms that reduce recruitment burden and address ethical concerns around placebo designs.

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.