SHAARPEC applies trajectory intelligence to three commercial problems: finding patients before they're visible, protecting patients before they're lost, and correcting dosing before outcomes degrade.
Each application uses the same trajectory architecture and foundation model — targeted to a specific decision that determines brand performance.
Refill gaps don't appear in isolation. They're preceded by care fragmentation, urgent care visits, and access friction events that appear in claims weeks before the first missed fill. SHAARPEC identifies this pattern and ranks the HCPs whose panels carry the highest concentration of at-risk patients.
Flat dose lines, rescue medication onset, shortened refill intervals — these signals are in your claims. SHAARPEC assembles them into a pre-switch trajectory and flags patients before the prescription moves, with a competitive flow map showing which prescribers are losing share and at what velocity.
Claims contain the titration schedule. Trajectory analysis reads the velocity and pattern of that schedule — distinguishing on-label titration from plateaus and dose regression, and separating institutional under-titration from patient-specific hesitation so the right intervention reaches the right HCP.
Conventional claims analytics report on what happened. By the time a quarterly utilization report reaches your field team, the patient has already initiated — or switched — or dropped off. The intervention window is closed.
SHAARPEC reads the same claims differently. It sequences them into longitudinal patient trajectories and trains a foundation model to recognize the patterns that reliably precede clinical events — before those events appear in prescription data.
AI-enriched trajectory analysis applied to population-scale atrial fibrillation screening across 330,000 patients. The model identified patients at optimal screening windows based on longitudinal care progression — not static risk factors.
Explainable machine learning trained on complete longitudinal heart failure patient histories. Deployed live inside a commercial EHR system as clinical decision support — the same architecture that underlies SHAARPEC's commercial trajectory models.
SHAARPEC is currently running a structured pilot 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.
We start with your data question and show you what the signal looks like for your therapy.
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