By the time traditional claims data signals emerging demand, your competition has already moved. SHAARPEC models patients as dynamic entities moving through care over time — so your commercial team identifies eligible patients and the HCPs most likely to treat them before that signal ever appears in prescription data.
Most pharma commercial teams build targeting lists from prescription data — which means they're acting on signals that are already months old. The physicians writing scripts today were identifiable well before those prescriptions appeared, if you were looking at the right signals.
The data exists. It's in the claims your team already has access to. What's been missing is a model that reads clinical trajectory — the sequence of encounters, diagnoses, and interventions that precede treatment — rather than waiting for treatment to appear.
Built on a graph architecture designed from the ground up for longitudinal healthcare data.
SHAARPEC identifies the clinical trajectory that precedes treatment initiation — so your field force has a prioritized target list weeks or months before those physicians appear in prescription data.
Every encounter, diagnosis, referral, and intervention is a connected event in time — not a row in a table. This structure is what makes it possible to detect patterns that flat claims analytics cannot see.
HCP targeting lists ranked by predicted future eligibility. Demand estimates by geography and specialty. Retention risk flags before patients switch. Outputs designed for specific commercial decisions — not retrospective reports.
Validation study underway with PrecisionAQ — one of the leading pharma commercialization analytics organizations in the US. A national breast cancer cohort of 23,000+ patients, structured from open and closed claims.
Built by clinicians and researchers from Harvard Medical School and Mass General Brigham — institutions where clinical pattern recognition and real-world evidence methodology are core disciplines.
We're putting the methodology in front of the people most qualified to evaluate it — submitting pilot results for peer review at leading forums for health economics and outcomes research.
We start with your indication and your data question — not a generic product demo. If the signal is there, we'll show you what it looks like.
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