Clinical Support
Turn biological depth into stronger trials, clearer readouts, and confident regulatory conversations.
Features
We optimize the design and mine the data—so every trial works harder.
Synthetic Controls & External Comparator Analysis
Build regulator-ready external control arms without requiring a placebo group. We construct propensity-matched cohorts from our longitudinal real-world datasets, matching on clinical, molecular, and treatment variables, then apply ML-driven causal inference to quantify relative treatment effects with statistical rigor.
This isn’t a generic real-world evidence play. Our external comparator arms are built on deeply curated, clinically annotated data with single-cell molecular context, a level of depth that strengthens both the scientific credibility and the regulatory positioning of the analysis.
What your team gets: Statistically credible external control arms that support regulatory submissions, reduce patient burden, and enhance trial interpretability.
Correlative Science Analysis
Explain why a therapy works or fails, at single-cell resolution. We integrate clinical trial data with molecular and single-cell profiling to identify the biological drivers of response and resistance in specific patient populations. These aren’t retrospective observations. They’re prospective insights that inform ongoing trial decisions and shape the design of next-stage programs.
What your team gets: Mechanistic explanations for clinical signals, resistance pathway identification, and translational evidence packages that strengthen both internal decision-making and external regulatory narratives.
Patient Selection & Stratification
The single highest-leverage decision in trial design is who you enroll. Our platform identifies the patient subpopulations hypothesised to respond, using single-cell molecular profiles linked to clinical outcomes, so enrollment criteria are grounded in biology, not broad eligibility windows. The result: sharper trials that are smaller, faster, and more statistically powerful.
What your team gets: Biology-driven enrollment criteria, biomarker strategies for responder identification, and risk models that can be embedded in clinical decision support.
The essential data layer for AI-driven medicine
Let’s build the evidence that moves your program forward.