Data Management

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.

Webinar Date/Time: Thursday, June 4th, 2026 at 11am EDT|8am PDT|4pm BST|5pm CEST

Pediatric trial participation shapes children's and caregivers' long-term psychological outcomes, yet protocol design often overlooks experience as a variable affecting recruitment, retention, and data integrity—a gap increasingly recognized by regulators and quality standards

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 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.

Early integration of clinical, operational, and patient-level insights during trial development can help close the gap between evidence generation and commercial performance, improving alignment between product value and real-world adoption.

When using electronic clinical outcome assessments (eCOA), ensuring clear stakeholder alignment throughout the lifecycle of a study regarding data management activities is critical to success.

Integrating technology and collaboration to close the evidence gap.

Webinar Date/Time: Tue, May 12, 2026 11:00 AM EDT

In this Q&A, Jenna DiRito, PhD, COO and co-founder of Revalia Bio, discusses how earlier, human-relevant data is reshaping go/no-go decision-making in drug development and what a truly front-loaded workflow looks like in practice.

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.

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.

Webinar Date/Time: Thu, May 7, 2026 1:00 PM EDT

Webinar Date/Time: Thursday, April 30th, 2026 at 11am EDT | 8am PDT | 4pm BST | 5pm CEST

Real-world data is increasingly used to optimize trial design, reduce recruitment burden, and support regulatory decisions, but adoption remains uneven due to challenges around data quality, integration, and internal alignment across functional areas.

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.

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.

Sample integrity and traceability often fail not because of science but because clinical trials rely on manual processes and fragmented systems that obscure problems until samples are already compromised.

Moving beyond vendor evaluation to incentive design in Phase II/III rare and genetic disease trials.

In the first months of 2026, the FDA has moved on multiple fronts to modernize how drugs are developed, evaluated, and approved, signaling a broader regulatory shift toward flexibility, mechanism-based evidence, and human-centric science.