While risk-based quality management (RBQM) has gained increasing acceptance across the clinical research enterprise as an operational framework aligned with the International Council for Harmonization (ICH) E6(R3) guideline for Good Clinical Practice, quantitative evidence on its financial impact has been limited.
To address this gap, an analysis coauthored by experts from CluePoints, a provider of statistical and artificial intelligence (AI)-driven software solutions, and the Tufts Center for the Study of Drug Development (CSDD) combined real-world RBQM data from 18 oncology trials conducted on the CluePoints platform with published/proprietary oncology benchmarks maintained by Tufts CSDD to model financial value across clinical development phases.
The study, published in Therapeutic Innovation & Regulatory Science, derived two primary financial measures:
- Clinical trial–level return on investment (ROI) based on the direct financial return from RBQM in individual trials due to monitoring-cost efficiencies and shorter trial durations; and
- Development program–level ROI based on the risk-adjusted financial value of RBQM across the broader oncology development pathway, accounting for costs, timelines, probability of success, and discounted commercial performance.
With the topline findings (also announced in a press release) making a strong case for RBQM practices in terms of their benefits for sponsors, ACRP asked for further input on the real-world impacts of more routine use of RBQM, and received the following feedback from Abigail Dirks, Senior Data Scientist at Tufts CSDD, and Sylviane de Viron, Data and Knowledge Manager at CluePoints. (The published paper was coauthored by de Viron and Kenneth McFarlane from CluePoints alongside primary author Dirks and Kenneth Getz from Tufts CSDD.)
Q: Why is there a need to quantify the financial ROI of RBQM?
A: Existing RBQM literature has primarily focused on operational rather than financial outcomes. This study addresses this gap by demonstrating the magnitude of financial return RBQM-enabled trials can achieve—including up to 23x ROI and 19% shorter phase durations.
Q: Can you share some of the headline findings of this research?
A: RBQM-enabled trials were associated with measurable financial efficiencies across all clinical trial phases. At the clinical trial level, estimated financial returns ranged from $3.2 million in Phase I to $18.9 million in Phase III, corresponding to between 6x and 23x ROI multiples. At the development program level, expected net present value gains ranged from $3.8 million in Phase I to $13.8 million in Phase III, corresponding to between 4x and 14x ROI multiples.
Q: What was the main driver of that increase in ROI?
A: The largest contributor to financial value was time savings. RBQM-enabled trials were associated with 8% to 19% reductions in clinical phase durations. This demonstrates that the strategic value of proactive, data-driven oversight extends beyond monitoring-cost reduction alone.
Q: What implications does this have for industry?
A: Sponsor companies often cite uncertainty about the financial return on RBQM investments as a primary barrier to broader adoption, even as regulatory expectations for risk-based oversight continue to intensify. What is particularly powerful about this study is that it translates RBQM impact into the language of clinical development decision-making factors: time, cost, ROI, and portfolio value. The fact that most of the financial value was driven by time savings is especially important because protecting development timelines is one of the most important strategic levers sponsors have.
Q: Are there any other benefits of RBQM-supported oversight?
A: Absolutely. The research also identified monitoring-cost reductions of up to 18% under a 10% source data verification (SDV) scenario, compared to the baseline assumption of 100% SDV. Other broader benefits discussed in the study and supporting literature include improved data quality oversight and earlier risk detection, increased development efficiency, and speed and enhanced portfolio productivity. Combined with the increased ROI generated by time savings, these results make an incredibly strong business case for RBQM adoption.
About the Contributors
Abigail Dirks, MA, MS, is a Senior Data Scientist at Tufts CSDD, where she specializes in analyzing large datasets pertaining to all aspects of industry-funded drug development performance, including protocol design complexity, investigative site burden and experience, RBQM adoption, clinical research associate performance, decentralized clinical trials use and impact, patient recruitment and retention, and study volunteer participation burden.
Sylviane de Viron, PhD, Data and Knowledge Manager at CluePoints, is responsible for creating knowledge on RBQM using CluePoints-accumulated data. She has worked for the last 13 years in the medical and pharmaceutical sector in various positions.
Edited by Gary Cramer
