Common outcomes include: AE prediction and burden modeling, adherence drop-off risks, sequencing optimization, guideline concordance gaps, and market-shaping patterns tied to MoA.

Yes. All patient data is fully permissioned and de-identified, with built-in consent and HIPAA-aligned privacy protections. Patients retain full control over how their data is used.

Our dataset spans oncology, rare disease, cardiometabolic, neuro, and more. We specialize in surfacing patterns tied to mechanism of action, treatment sequencing, and AE burden—regardless of indication.

Because our data is structured from the start and models are purpose-built, we can deliver decision-ready insights in days—not months.

We use AI to normalize, clean, and link records across fragmented systems—resulting in longitudinal journeys that are ready for research and predictive modeling from day one. No tokenization or manual stitching required.

Our primary users include teams in Medical Affairs, RWE/HEOR, Commercial Strategy, Market Access and R&D.

Our dataset is sourced directly from patients who use Novellia to unify their health records from across providers, EMRs, and care sites nationwide. Every record is permissioned and structured to support longitudinal analysis.

Unlike fragmented, ‘snapshot-in-time’ datasets, Novellia delivers patient-level, longitudinal records that are automatically cleaned and structured using AI to surface patterns, signals, and insights that traditional RWD simply can’t identify. We deliver precision insights, not just raw cohorts.