
Metrics & Benchmarks
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The Evolution of Global Trial Strategies in Today's Complex Healthcare Landscape

Centering Site Experience to Accelerate Study Activation

ACT Brief: Life Sciences Hold the Line on DEI, Startup Timelines Stretch Further, and Regulators Align on AI Governance

Why Startup Timelines Are Worsening—and How to Reverse the Trend

The Business Case for DEI in Pharmaceutical Innovation: Why Organizational Commitment Matters for Inclusive Clinical Trials

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In today’s ACT Brief, we look at why durable signal closure is emerging as a defining metric in risk-based quality management, how AI can reduce startup delays without burdening sites, and how patient-centric drug design is reshaping the CDMO landscape.

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.

Examine how practical AI applications can streamline contracts and startup workflows while preserving the central role of investigators, site staff, and patient relationships in clinical research.

In today’s ACT Brief, we look at efforts to address sex-based evidence gaps in Parkinson’s disease research, why communication failures continue to delay study startup, and how a new White House healthcare plan aims to reduce drug and insurance costs.

As Parkinson’s disease cases surge worldwide, growing evidence gaps around women’s biology, care access, and outcomes are driving new data-driven and digital strategies to advance sex-specific research and precision medicine.

Unpack why persistent communication breakdowns between sponsors, CROs, and sites undermine startup efficiency—and how bidirectional, site-informed engagement models can improve collaboration and momentum.

In today’s ACT Brief, we look at how AI is reshaping clinical trial registries into discovery tools, why contract and budget negotiations remain the biggest drag on site activation timelines, and how integrated data platforms are closing gaps across payer, provider, and patient care.

Explore how contract standardization, proactive budget alignment, and AI-enabled negotiation tools can reduce site activation delays and turn agreements into strategic accelerators rather than administrative bottlenecks.

As AI-driven search becomes the primary way patients discover research opportunities, the quality and structure of clinical trial registry data will determine whether transparency translates into real, equitable access.

ACT Brief: Moving Beyond AI Pilots, FDA Advances Bayesian Trials, and Sites Strained by Trial Design
In today’s ACT Brief, we examine what will separate sponsors that scale AI beyond pilots in 2026, break down the FDA’s new draft guidance on Bayesian statistical methods in clinical trials, and explore how poor planning and trial design continue to place operational strain on research sites.

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve efficiency, reduce timelines, and support regulatory decision-making.

See what will distinguish sponsors that scale AI into core operations from those stuck in experimentation, and why redesigning underlying processes—not just optimizing workflows—is critical to realizing long-term value.

In today’s ACT Brief, we look at how community research sites can stay competitive under efficiency pressure, why 2026 is shaping up as a turning point for platform-based clinical operations, and how AI is being positioned to better match patients to therapies.

The clinical trial ecosystem is entering a phase of consolidation and reinvention driven by the collapse of boundaries between functions, data, and even companies themselves.

In today’s ACT Brief, we examine how community research sites can stay competitive under rising efficiency pressures, why clinical outcome assessment licensing remains a drag on trial start-up, and what’s holding back AI-driven pharmacovigilance at scale.






















