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Mike Wenger, chief innovation officer at CRIO, explains how AI can responsibly support data quality and monitoring with proper oversight, and why advancing eSource and EHR systems remains critical to strengthening data integrity and remote trial operations.

Explore how AI, decentralized tools, eSource, and IRT are reshaping clinical development operations in Applied Clinical Trials' February issue.

Raja Shankar, VP of machine learning at IQVIA, discusses which AI capabilities sponsors are most likely to adopt first to streamline trial workflows and reduce operational burden, while also highlighting emerging applications that could shape the next phase of clinical trial design.

As clinical trials grow more global and complex, AI is emerging as a practical enabler of smarter financial management by automating manual processes, improving visibility across fragmented systems, and helping sponsors, CROs, and sites reduce delays, errors, and operational friction.

Jeremy Wyatt, CEO, Ametris, discusses how operational best practices for integrating wearables into oncology trials center on minimizing patient burden through thoughtful workflow design, careful device selection, and early planning to ensure digital measures fit the realities of complex patient populations.

Mike Wenger, chief innovation officer at CRIO, discusses how different site types—from academic medical centers to independent research sites—require distinct eSource approaches, and why aligning technology with site workflows is critical to study execution.

Raja Shankar, VP of machine learning at IQVIA, explains how AI-driven trial simulation and automation are beginning to influence decision-making across every phase of clinical development.

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.

A look at how efficiency, access, platformization, AI, non-traditional players, and regulatory recovery are expected to reshape clinical operations in 2026.

Global clinical development has evolved into a technology-enabled, highly regulated, and geographically diversified enterprise, as sponsors adapt trial design, partnerships, and operations to meet rising demands for scale, speed, and patient-centricity.

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.

As Parkinson’s disease cases surge worldwide, growing evidence gaps around women’s biology, care access, and outcomes are driving new data-driven and digital strategies to advance sex-specific research and precision medicine.

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.

See what will distinguish sponsors that scale AI into core operations from those stuck in experimentation, and why redesigning underlying processes—not just optimizing workflows—is critical to realizing long-term value.

The clinical trial ecosystem is entering a phase of consolidation and reinvention driven by the collapse of boundaries between functions, data, and even companies themselves.

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.

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.

BostonGene has entered a new collaboration with AstraZeneca to apply its foundation AI model to oncology drug development, aiming to improve early trial decision-making around safety, efficacy, and biomarker strategy while accelerating clinical timelines.

Unclear boundaries between investigator-controlled and sponsor-managed data in IRT systems are creating avoidable compliance risk, particularly around investigational product inventory and quality actions.

Learn why combining AI-enabled trial matching with transportation, lodging, and financial assistance is essential to turning trial eligibility into actual participation—and why matching alone is not enough.

Examine how the American Cancer Society’s national ACTS expansion is designed to simplify trial discovery, reduce logistical barriers, and help patients, caregivers, and providers navigate cancer clinical trials through a centralized support model.

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.

New research finds that while eSource adoption is advancing through EHR-to-EDC workflows, scaling its impact will depend on integrating unstructured clinical data using AI, shared standards, and collaborative validation models across sites, sponsors, and vendors.

Learn how clinical operations leaders can build technology adoption, transform workflows, and cultivate digitally savvy talent to successfully implement AI across the entire clinical trial lifecycle.

Discover how remote assessments, wearables, and digital technologies can decentralize data collection, reduce patient burden, and enable trials to reach more diverse and representative populations.













