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Not Simply More Text, but Better Orientation

How thoughtful labeling can make clinical trials more accessible for people with dyslexia.

Real-Time Trials Need More Than AI: Why Operational Trial Infrastructure Matters

Real-time AI-enabled decision-making only accelerates development when trials have coordinated operational infrastructure for randomization, supply management, and workflows capable of responding to new insights without disrupting execution or compliance.

Enhancing Empowerment in Patient-Focused Research

How the inclusion of measures centered on net treatment benefit can drive an effective multifaceted approach.

Beyond the Horizon: A New Era for Faster, Smarter Clinical Trials

Current industry trends align with the need for improved, fit for purpose technology.

How AI and Regulation are Reshaping the Future of Drug Safety

Balancing the emerging benefits of AI in pharmacovigilance with new responsibilities and demands from regulators in enhancing efficiency and safety.

AI Moves Patient Recruitment from Trial Bottleneck to Competitive Edge: A 2026 Perspective

As sponsors push for faster, more representative studies, AI-enabled matching and EHR integration are emerging as operational levers, but bias, explainability, and governance will determine whether the technology scales.

Beyond Revenue Recognition: Rethinking CRO Contracting Through the CURED Shared Performance Contract

Traditional CRO contracting models create misalignment between effort, progress, and financial outcomes, driving revenue recognition risk and margin volatility, but shared performance contracts linking costs to deliverables can improve transparency and accountability.

AI-Powered Non-Interventional Research Delivers What DCTs Promised

A unified technology approach improves study efficiency and data collection.

The Future is Now: Four Ways AI and Other Tech Advances are Enhancing Clinical Trials

Emerging applications of AI/ML, automation, and digitization are helping sponsors cut clinical trial start-up times to as little as four weeks, reduce data errors, and enhance patient engagement—demonstrating how tech-enabled processes are reshaping trial efficiency and experience across the study lifecycle.

SCOPE Summit 2026: How Sponsors Are Prioritizing AI Adoption Across Clinical Trials

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.

What Clinical Trials Can Learn from the Gig Economy About Payments

Outdated payment methods like prepaid cards and checks create administrative burden and retention friction, but modern flexible payment platforms with multiple payout options and global reach can improve participant experience without adding compliance complexity.

From Study End to Long-Term Insight: Choosing the Right Vaccine Follow-up Strategy

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.

The Transformative Power of Data Analytics in Clinical Trials

Leveraging and benchmarking insights to boost efficiency and optimization.

5 Strategies for Bridging the Sponsor-Site Tech Divide

Results from survey of 100 site personnel suggest a disconnect is present between these stakeholders.

Empowering the Workforce of the Future: The Trends and Training That Will Drive the Future of Drug Development

A new global report finds that clinical research teams are making progress but still lack the skills and tools needed to keep pace with growing trial complexity and emerging technologies.

Applied AI and Advanced Automation in Clinical Trials

Use cases spotlight the growing potential of generative AI in the CRO space.

Beyond Eligibility: Making Trust and Behavioral Readiness Actionable in Clinical Trial Recruitment

Eligibility criteria alone rarely predict enrollment, which depends more on trust, hope, and fear, requiring relationship-based community engagement paired with behavioral readiness assessments rather than transactional outreach.

After the Trial is too Late: The Case for More Active Use of Patient-Reported Outcomes in Oncology Studies

Advancing toward more meaningful use of PRO data by making it systematic, transparent, and built into trial design.

Clinical Trial Monitoring: Should Randomization Be Included?

While randomization is required by regulatory bodies, it is up to the sponsor on how to conduct it.

Foundational Content Consolidation for Regulatory-Ready Digital End Points: Insights From Public-Private Partnerships

Public-private collaboration and structured evidence consolidation are emerging as critical enablers of regulatory-ready digital end points, helping standardize terminology, reduce duplication, and accelerate the integration of digital health technologies into clinical research and decision-making.

Built-In, Not Bolted On: Why Clinical Data Security Has to Be a Design Principle

Clinical data security built into system architecture from the foundation, rather than layered on afterward, reduces regulatory risk and actually accelerates research by removing manual compliance burden and improving team confidence in data integrity.

The Challenges of Buying Blind: Why Providing the Clinical Outcome Assessment Measure Prior to License Execution Would Significantly Benefit Clinical Trial Set-Up

Persistent delays and inefficiencies in COA licensing and translation stem from limited pre-license access and fragmented processes, making a strong case for providing outcome assessment measures earlier to reduce risk and accelerate trial start-up.

A Signal Isn’t Resolved Until It Stays Closed—RBQM Lessons

Analysis of more than 880 clinical trials shows that while statistical data monitoring and key risk indicator signals close on similar timelines, durability—not speed—is the defining differentiator in effective, risk-based quality management.

2026 DIA Global Annual Meeting: Stacy Hurt of Parexel on Federated AI, the Patient Voice, and Accountability for Patient Needs

In this video interview from the 2026 DIA Global Annual Meeting, Stacy Hurt, chief patient officer at Parexel, explains how federated AI is expanding what's possible in oncology research, why the patient voice gets lost earliest in development, and why someone in every organization needs to explicitly own patient needs from the very beginning.

Harnessing Unstructured Data and Hospital Interoperability

The potential of next-generation platforms in transforming patient recruitment.

Realtime Electronic Data Capture at Investigator Sites: Laboratory Data and Beyond

Digital Measures of Health: What’s in it for Patients?

Exploring the different stages in the development of a digital measure, and the activities and steps key to achieving meaningful impact for patients.

What Real-World Data Shows About Current Cancer Care

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

Front-Loading Drug Development: Q&A with Jenna DiRito, PhD, Revalia Bio

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.