Trial Design

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.

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.

Behavioral science reveals how recruitment failures, site disengagement, and underrepresentation in clinical trials are rooted in early design decisions, and what sponsors can do to address them before they become costly problems.

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.

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 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.

The April issue of Applied Clinical Trials delves into the priorities driving patient engagement approaches today from the technology, regulatory, and site operations fronts.

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.

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 part 1 of this three-part series, behavioral science reveals how slow patient recruitment and enrollment challenges often stem from design and startup decisions made long before recruitment begins, but can be identified and resolved early when they still matter.

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.

In this video interview, Marc Buyse, ScD, founder and CEO of IDDI, examines the most common threats to trial data reliability, including opaque methodologies, synthetic controls, and the limits of AI-driven analysis, while making the case for explainable, transparent trial design.

In this video interview, David Morton, PhD, director of biostatistics at Certara, reflects on the growing role of Bayesian approaches in modern drug development, emphasizing their potential to improve decision-making, efficiency, and overall trial success.

In this video interview, David Morton, PhD, director of biostatistics at Certara, explores the practical challenges of implementing Bayesian designs, including the need for simulation, cross-functional alignment, and clear communication with regulators.

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, explains how regulatory momentum is encouraging sponsors to move beyond traditional methods, leveraging Bayesian frameworks to improve efficiency, particularly in rare disease and small population studies.

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.

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.

Findings from the VA’s Diuretic Comparison Project show pragmatic trial designs can achieve strong provider participation when burden is minimized and patient care remains the primary focus.

When a single pivotal trial can determine the fate of an entire program, success depends less on marginal gains in speed or cost and more on building robust, adaptive trial designs that actively manage uncertainty and protect the probability of a positive outcome.

Charlie Paterson, partner at PA Consulting, outlines how limited FDA guidance on innovative designs, decentralized models, and digital endpoints is forcing clinical operations teams to recalibrate expectations and minimize regulatory risk.

Charlie Paterson, partner at PA Consulting, discusses how fewer new guidance updates are pushing sponsors to rely on historical precedents and non-US standards when making trial design and operational decisions.

See how real-world evidence is enabling smaller, smarter, and more efficient trial designs through hybrid models, external comparators, and continuous patient monitoring—while preserving the role of traditional clinical trials.