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.

Today's biopharmaceutical landscape demands a fundamental rethinking of outsourcing approaches that embrace collaboration, flexibility, and teams willing to meet halfway.

Some organizations are considering ex-US studies for initial phases. Even with initiatives like the single pivotal trial concept, confidence requirements may still demand larger samples and longer ...

Beyond the design, if enrollment slows due to seasonal effects or difficulty finding a niche patient group, a robust design activates a contingency plan that dynamically adjusts site selection based ...

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 ...

Certain low-risk or mature devices may see reduced trial requirements, but the broader trend is toward augmenting—not ...

Methodological transparency is critical. Sponsors must document how cohorts were built, how missingness was handled, and how ...

In today’s ACT Brief, we examine why ESG efforts in clinical development are shifting into vendor oversight, what data and ...

The FDA and EMA have aligned on ten guiding principles for the responsible use of artificial intelligence across the drug development lifecycle, establishing a shared framework to support innovation, ...

In today’s ACT Brief, we explore why decentralized trial innovations struggle to scale without better change management, ...

Explore how large-scale, de-identified real-world datasets enable more representative trial design, improve site selection, ...

In today’s ACT Brief, we examine why life sciences companies are maintaining DEI commitments amid political pressure, what’s ...