Investigative Sites

In part 3 of this three-part series, behavioral science reveals that clinical trial diversity cannot be achieved through last-minute recruitment efforts, but requires designing protocols, sites, and enrollment strategies around the real barriers and needs of underrepresented communities from the outset.

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 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.

In part 2 of this three-part series, behavioral science and service design reveal how poor experiences with confusing information, unreliable technology, and inefficient processes drive site disengagement and patient dropout, and how measuring these experiences early enables practical, evidence-based solutions.

Vaccine developers can reduce participant burden and extend follow-up timelines by strategically combining traditional site visits with real-world data collection, but the choice depends on follow-up duration, data requirements, and the patient population being studied.

In this video interview, Cheryl Kole, vice president of solution strategy and commercialization at Almac Clinical Technologies, makes the case that intuitive, easy-to-navigate technology directly reduces errors, improves site compliance, and prevents the workarounds that quietly undermine study performance.

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.

Investigator-initiated trials operate under the same regulatory and operational requirements as industry-sponsored studies but rely on fragmented, consumer-grade tools, creating a persistent technology gap that can impact data integrity, efficiency, and compliance.

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.

As trials expand into new geographies and decentralized models mature, sponsors are confronting a core operational challenge in 2026: how to scale global execution while reducing system complexity and day-to-day burden on research sites.

Consider how sponsor and CRO practices that prioritize site needs, clarity, and partnership can strengthen trust, sustain momentum, and speed activation without sacrificing the human experience.

Analyze the operational pressures driving longer activation timelines, from protocol complexity to site competition, and learn how earlier, more flexible site engagement can restore momentum.

Examine how practical AI applications can streamline contracts and startup workflows while preserving the central role of investigators, site staff, and patient relationships in clinical research.

Unpack why persistent communication breakdowns between sponsors, CROs, and sites undermine startup efficiency—and how bidirectional, site-informed engagement models can improve collaboration and momentum.

Explore how contract standardization, proactive budget alignment, and AI-enabled negotiation tools can reduce site activation delays and turn agreements into strategic accelerators rather than administrative bottlenecks.

Examine the strategies community research sites can use to secure trial opportunities, from adopting AI-enabled workflows to proving verified access to underrepresented patient populations.

Learn how real-time patient eligibility data is reshaping trial planning and site selection, allowing sponsors to design more inclusive studies based on current patient reality rather than past performance.

Unpack how rising competition for the same high-profile sites is slowing startup and enrollment—and what sponsors must change in their site strategies to ensure AI-enabled efficiencies translate into real-world impact.

Explore how sponsors can recalibrate efficiency efforts to avoid overconcentrating trials at familiar sites and instead expand access through community partnerships, point-of-care research, and intentional outreach models.

By leveraging the Fresh Start Effect at site initiation and shifting from passive training to demonstrated readiness, sponsors and CROs can turn trial launch into a powerful multiplier for early performance, compliance, and execution quality.

Review the performance, engagement, and satisfaction metrics sponsors and CROs should track to determine whether operational improvements are reducing burden and strengthening site relationships.

Learn how AI-enabled automation can streamline existing operational processes, reduce manual effort, and enhance efficiency while allowing sites to work as they do today.