CluePoints Shortlisted for 2026 Scrip Awards for the Third Time in Eight Years
Clinical Trial Vanguard covers CluePoints’ 2026 Scrip Awards shortlisting and what it signals about data oversight technology in clinical research.
The Unquantified Value of RBQM: Reduced Rework, Data Integrity, and Inspection Readiness
In this video interview, Sylviane de Viron of CluePoints and Abigail Dirks of Tufts CSDD discuss what the RBQM financial model left out—reduced rework, improved data integrity, and inspection readiness—and why those excluded factors could represent even greater value than what was modeled.
Why Time Savings Is the Largest Driver of RBQM’s Financial Value
In this video interview, Sylviane de Viron of CluePoints and Abigail Dirks of Tufts CSDD explain why time savings dominates the eNPV model for RBQM—and what that means for how sponsors should frame the internal case for investment.
Why Quantifying the Financial Value of RBQM Has Been So Hard- and What This Study Did Differently
In this video interview, Sylviane de Viron of CluePoints and Abigail Dirks of Tufts CSDD explain how combining real-world deployment data with eNPV modeling finally made it possible to put a number on the financial value of RBQM—and why oncology was chosen as a conservative starting point.
Trial Complexity is the New Normal
Clinical trial complexity is now the norm: more endpoints, more procedures, narrower eligibility criteria, and more data sources, with Phase III protocols collecting approximately 5.9 million data points on average and volume rising around 11% annually since 2020.
Making the Financial Case for Risk-Based Quality Management in Clinical Research- Q&A
New peer-reviewed research puts hard numbers to the financial value of RBQM, showing ROI multiples up to 23x and up to 19% shorter clinical phase durations, with time savings as the biggest driver.
The CRA of the Future
Clinical research associates are evolving from compliance-focused manual monitors to data-enabled strategic site partners, but organizations need analytics training, clear operating models, and active change management to make the shift stick.
Applying Risk-Based Oversight to Ensure Real-World Data Integrity
Clinical trials have undergone a period of immense change. Use of real-world data (RWD) is increasing. Regulators are backing both risk-based approaches and the use of real-world evidence (RWE). Artificial intelligence (AI) allows us to unlock better insights than ever before.
How RBQM Fits Into An AI World
How risk-based quality management (RBQM) can harness the power of AI and advanced analytics to transform clinical trial execution and oversight.
How agentic AI is shifting data management from time-consuming investigation to confident confirmation
AI is reshaping clinical data management (DM), moving the industry away from time-consuming, inefficient processes and towards continuous, intelligent oversight.