
Metrics & Benchmarks
Latest News

Beyond the Molecule: Why Radiopharmaceutical Trials Require a New Operating Model

FDA Releases Transparency Roadmap Outlining Disclosure Priorities Across Drug Development and Regulatory Review

ACT Brief: Ibogaine Trial Design Guidance, Outsourcing Model Oversight Gaps, and Kidney Disease Partnership

Mixed Outsourcing Models Are Spreading. Is Sponsor Oversight Keeping Up?

FDA Seeks Public Input on Early-Phase Clinical Trial Design for Ibogaine

Shorts










Podcasts
Videos
All News

In today's ACT Brief, we examine practical guidance for clinical operations teams beginning AI adoption, how hierarchical endpoints better reflect treatment benefit, and why early-stage program failures signal smarter pipeline management.

Hierarchical composite endpoints analyzed through pairwise comparisons more accurately reflect multifaceted treatment benefit than time-to-first-event composites, but transparent outcome prioritization, patient involvement in ranking, and reporting of Net Treatment Benefit remain underutilized despite their importance to interpretation.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, offers practical guidance for clinical operations teams beginning their AI journey—making the case that the tools are more accessible than many assume and that waiting to start is a competitive risk in itself.

In today's ACT Brief, we examine how AI enables sponsors to pressure-test protocols before enrollment, HHS's multi-initiative effort to accelerate trial design and execution, and FDA approval expanding heart disease therapy to adolescents.

The new effort combines adaptive platform trial design, AI-enabled site activation, nationwide data infrastructure, and patient data contribution tools to reduce timelines, costs, and patient burden across clinical development.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, explains how AI is shifting trial risk management from reactive to proactive—enabling sponsors to pressure-test protocols and anticipate pivots before a single patient is enrolled.

In today's ACT Brief, we examine AI's role as trial design advisor with human leadership, how to govern autonomous agents in regulated operations, and real-world outcomes from switching to oral weight-loss therapy.

AI agents in clinical operations acquire broader autonomous capability through expanded permissions, tools, memory, and delegated authority, requiring governance focused on whether effective capability has shifted outside approved boundaries rather than whether software has changed.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, makes the case for AI as a sophisticated strategic advisor in trial design while arguing that humans must remain in the lead—especially when factors the model can't fully account for are at stake.

In today's ACT Brief, we examine how data drives honest enrollment assumptions, why RWE infrastructure lags ambition, and the disconnect between FDA rulemaking and enforcement on compounded therapies.

RWE is finding a role earlier in drug development than ever before, but the data quality, integration, and organizational alignment required to make it regulatory-grade are still catching up to the ambition.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, explains why combining analog trial performance data with real-world patient data and site-level recruitment history gives sponsors a far more honest picture of whether their enrollment assumptions are actually achievable.

In today's ACT Brief, we examine what AI simulations surface in trial design, how RBQM delivers measurable financial returns, and three new FDA-approved treatments across hair loss, movement disorder, and bone disease.

In this Q&A, Sylviane de Viron of CluePoints and Abigail Dirks, MS, of Tufts CSDD discuss the findings of a collaborative study quantifying the financial value of RBQM, why time savings emerged as the largest driver, and what sponsors struggling to justify adoption now have that they didn't before.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, walks through the categories of hidden protocol risk that AI-driven simulations can identify—from overly restrictive eligibility criteria to patient dropout patterns and structural trial assumptions.























