Time-series models prioritize sites and subjects at risk so your team can act earlier—with reasoning you can verify.
MyRBQM® Portal uses predictive analytics to forecast the development of clinical trial metrics, helping study teams identify emerging trends, assess potential risks and make informed, proportionate oversight decisions.
Understand how clinical trial metrics may develop over time.
Recognize trends that may warrant earlier review.
Bring forecasts into human-led RBQM oversight.
Watch how dynamic interactions like chart zooms and live filters bring insights to your fingertips.
Predictive analytics highlights how clinical trial metrics may develop over time, helping study teams recognize trends that could warrant attention before predefined thresholds are reached.
Examine projected trends for supported clinical trial metrics, including enrollment and relevant performance indicators. Focus oversight on measures that matter to the study's risks and operational priorities.
Where forecast ranges are displayed, they provide context for interpreting projected values. Consider the uncertainty, available data and study circumstances when deciding whether further review is warranted.
Identify developing trends and potential changes in direction or rate. These patterns may indicate where additional investigation or closer risk monitoring would be appropriate.
Use forward-looking metric trends to anticipate areas that may require additional attention. Study teams can consider these insights when planning proportionate monitoring and operational activities.
Switch between available time horizons and chart views to examine shorter- and longer-term trends. This helps reviewers assess developments at the level relevant to their oversight responsibilities.
Compare historical observations with projected metric trajectories. Review the forecast alongside study-specific risks and operational information to support informed, accountable decisions.
Predictive forecasts complement current monitoring signals and study-specific risk information, helping teams interpret emerging trends, determine whether action is warranted, and document their decision rationale.
Relevant Signals
Informed Oversight
Accountable Decisions
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.
Explore how longitudinal metric forecasting could complement your current risk monitoring and support study-specific oversight decisions.
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