Data Management

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.

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.

Why rigorous testing and validation matter more than ever.

Most protocol deviations start as human problems, not operational ones, but risk-based monitoring typically relies on lagging indicators that arrive too late to prevent these problems instead of measuring readiness during training, when intervention still matters.

In this video interview, Marc Buyse, ScD, founder and CEO of IDDI, discusses how increasing trial complexity is making data interpretation less straightforward and why transparency and reproducibility are now essential.

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.

In this video interview, David Morton, PhD, director of biostatistics at Certara, outlines how increasing FDA support is helping drive adoption of Bayesian methods, particularly in rare disease and small population studies where efficiency is critical.

In this video interview, David Morton, PhD, director of biostatistics at Certara, discusses how growing FDA support is accelerating the adoption of Bayesian approaches, enabling more flexible, data-driven trial designs through external data borrowing, adaptive decision-making, and simulation-based planning.

In this episode of the Applied Clinical Trials Podcast, C.K. Wang, MD, chief medical officer at COTA; and Sujay Jadhav, CEO of Verana Health, discuss how their organizations’ merger is advancing the use of real-world data to inform trial design, patient recruitment, and regulatory decision-making.

As rare disease trials face persistent feasibility challenges, Bayesian designs are gaining momentum by enabling more flexible, data-driven approaches that integrate prior knowledge, reduce sample size demands, and align with evolving FDA guidance to accelerate evidence generation.

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.

Jonathan Andrus, co-CEO of CRIO, highlights the need for earlier cross-functional collaboration and greater site involvement to ensure data quality, workflow alignment, and operational success.

Jonathan Andrus, co-CEO of CRIO, outlines how disconnected systems and inconsistent data collection across sites create risk, while centralized eSource approaches present a major opportunity.

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.

Jonathan Andrus, co-CEO of CRIO, explains how protocol-driven eSource templates and standardized data capture are improving consistency, oversight, and efficiency across clinical trial sites.

Jonathan Andrus, co-CEO of CRIO, discusses how increased reliance on site-based technologies and eSource is strengthening data quality, compliance, and trust at the point of patient encounter.

Rising development costs, low success rates, and increasing trial complexity are reshaping the clinical trial project manager role, demanding stronger digital fluency, adaptive leadership, and expanded stakeholder coordination to deliver studies efficiently.

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.

Angela Zubel, chief development officer, Debiopharm, outlines how predictive models are improving compound selection from early clinical phases, while noting the ongoing challenges of forecasting success from preclinical development to patient outcomes.

Angela Zubel, chief development officer, Debiopharm, explains how AI-enabled site selection, patient allocation, and real-time data monitoring can reduce costs, shorten timelines, and limit inefficiencies caused by non-performing sites.