Why Quantifying the Financial Value of RBQM Has Been So Hard—and What This Study Did Differently

In a recent video interview with Applied Clinical Trials, Sylviane de Viron, data and knowledge manager at CluePoints, and Abigail Dirks, MS, senior data scientist at Tufts CSDD, discussed the findings of a collaborative study aimed at quantifying the financial value of risk-based quality management—a question the industry has struggled to answer empirically for decades. They opened by explaining why the problem has been so difficult: early in adoption, there is simply not enough real-world use data to model ROI, while leadership demands for that ROI assessment remain urgent. The study addressed that gap by combining CluePoints' deployment data with Tufts CSDD's benchmarking expertise and expected net present value modeling, focusing on oncology as a conservative case given its high development costs and lower relative commercial potential.

Time savings emerged as the largest driver of financial value in the model, a finding both speakers described as confirmation of a longstanding intuition. Dirks explained that time savings almost always dominates eNPV models in drug development, because long timelines combined with high commercial potential mean that even small time gains carry outsized financial weight. De Viron connected that finding directly to RBQM's operational logic: earlier issue detection, centralized documentation, and faster database lock all compound to accelerate the path to market.

The speakers were candid about what the model could not capture—reduced rework, improved data integrity, and inspection readiness were excluded not because they lack value, but because they are genuinely difficult to quantify. De Viron illustrated the stakes with an example: a late-detected issue could force the exclusion of entire centers, wasting the cost of all that data collection and potentially undermining study results. Dirks noted that if improved regulatory success were incorporated into the model, the eNPV delta would be substantially larger.

They closed by situating the study within the broader adoption challenge, arguing that sponsors now have two things they have historically lacked: regulatory encouragement through ICH E6(R3) and empirical financial evidence. De Viron added a practical caveat—RBQM only delivers its full value when it replaces, rather than supplements, traditional monitoring approaches like 100% SDV.