If you are evaluating RBQM, the key question is not “Will RBQM save money?”
but “How much of this value can we realistically capture, given our operating model?”
If you are evaluating RBQM, the key question is not “Will RBQM save money?”
but “How much of this value can we realistically capture, given our operating model?”
Modeled Phase III oncology value (Tufts CSDD, June 2026)
Shorter phase durations
Lower monitoring costs
Clinical teams today are under more pressure than ever: compressed timelines, rising complexity, and budgets that rarely stretch as far as they need to. Recent Tufts CSDD analysis adds an important external evidence layer to the RBQM value discussion: the strongest value driver is not monitoring cost reduction alone, but faster, more risk-proportionate trial execution.
Understandably, many leaders push back: Does it truly save money, or is it just a polished slide deck promise?
Recent Tufts CSDD analysis adds an important external evidence layer to this discussion.
The strongest value driver is not monitoring cost reduction alone, but faster, more risk-proportionate trial execution — supported by earlier risk detection, focused oversight, and cleaner data earlier in the study.
Evidence note:
Tufts CSDD oncology benchmark model (June, 2026): 10% SDV + DQA + KRIs vs. traditional 100% SDV. Industry evidence; not a Cyntegrity-specific customer ROI claim.
This aligns with what we see in mature RBQM programs: fewer surprises, more focused monitoring effort, earlier issue detection, and tighter control of avoidable work. Across Phase II/III studies, these patterns can translate into meaningful operational efficiencies and better timeline predictability.
The deeper figures — monitoring efficiencies, reduced rework, fewer avoidable amendments, inspection-readiness benefits, and the potential economic value of small timeline gains — are shared in the downloadable case brief.
These are not generic ROI promises. They are data-informed estimates based on modeled scenarios, observed RBQM implementation patterns, and external industry research. Actual value depends on study design, operating model, data availability, maturity, and whether risk signals consistently lead to action.
Targeted Monitoring & SDV Optimization (~$1.5M)
RBQM enables targeted, data-driven allocation of CRA and monitoring effort. It does not remove oversight; it helps focus oversight where risk is higher and reduce routine activity where risk is lower. Calculations can be explored through the Monitoring Cost & SDV Calculator.
Fewer Avoidable Protocol Amendments (~$250K)
RBQM strengthens protocol design by feeding risk, issue, deviation, and data-quality patterns back into planning. In our model, even a modest reduction in avoidable amendments can create meaningful operational savings.
Inspection Readiness & Compliance Efficiency (~$300K)
RBQM supports inspection readiness by keeping risks, signals, decisions, issues, and actions traceable. This does not guarantee a clean inspection, but it can reduce avoidable fire-drill effort linked to poor oversight evidence or missing documentation.
Timeline Acceleration & Market-Access Upside
Operational savings matter, but time is often the larger financial lever. Even small timeline gains can create significant economic value when cleaner data, earlier risk detection, and faster issue resolution help prevent avoidable delays.
Early Risk Detection & Avoided Rework (~$750K)
When deviations, missing endpoints, safety signals, or outlier site patterns are detected earlier, teams can intervene before issues escalate. This reduces avoidable rework and helps keep study execution under better control.
Design out avoidable risk before FPFV. AI-augmented protocol analysis surfaces CtQs, quantifies complexity, predicts deviation hot-spots, and reduces amendment drag, so you lock in patient-safe, inspection-ready design from day one.
Operationalize RBQM with verifiable math. AI-guided RACTs, calculation transparency, RBAC-secured workflows, and cross-study analytics deliver proportionate controls, clear KRI/QTL governance, and faster, defensible decisions at scale.
Move beyond manual cleaning and fragmented reviews. With time-series anomaly detection, protocol-aware deviation checks, and structured reasoning, the MyRBQM® Portal highlights what truly requires attention.
Stay ahead of issues, not behind them. Portfolio-wide, AI-enhanced dashboards fuse KRIs, QTLs, and deviation signals to cut escalation latency and focus monitors on high-value actions, fully aligned with ICH expectations.
See the full patient story—fast. Subject Profiles synthesize visits, AEs, ConMeds, labs, and trendlines, accelerating case review and improving safety decisions with transparent traceability and RBAC-controlled access.
Fast, secure connectivity with your clinical platforms through ready-made endpoints and low-overhead, real-time or batch data sync.
Pre-engineered, validated connectors to major EDC systems — reducing integration time while enabling secure, real-time or scheduled data sync.
Seamlessly connect your enterprise data platforms with secure, governed, low-overhead sync — without restructuring your existing data lake.
Our platform and processes meet internationally recognized security, availability, and confidentiality standards. ISO 27001:2022 certification and SOC 2 examinations provide independently verified assurance of our information security controls.
Our clinical-grade AI is independently certified through Microsoft’s Healthcare AI program, ensuring transparent, human-guided oversight, responsible AI practices, and secure integration with Azure’s validated infrastructure.
The MyRBQM Portal is built in alignment with 21 CFR Part 11 and GAMP 5, ensuring data integrity, traceability, and suitability for use in regulated clinical research environments.
If you are evaluating RBQM, the key question is not “Will RBQM save money?”
but “How much of this value can we realistically capture, given our operating model?”
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