Serialization authenticates the package. MedSnap authenticates the pills inside.
Serialization authenticates the package. MedSnap authenticates the pills inside.
DSCSA serialization and FMD verification authenticate the package integrity, but cannot authenticate the actual medication inside. This leaves automated systems vulnerable to errors that barcodes and weight checks miss:
These errors bypass standard checks, turning a high-speed automated pharmacy into a high-speed distributor of errors – and regulatory risk.
Make content authentication the 'Snap-to-Enable' guardrail for automated pharmacy.
Other vision systems may verify if tablets or capsules look like a known drug. MedSnap is designed to authenticate them.
MedSnap analyzes 25 distinct visual features—morphology, color, texture, size, and imprint—at a near‑microscopic level against trusted authentic reference models. Patented methods ensure precise pill segmentation, correct lighting and color to ensure reliable comparisons across environments.
Patented technology: U.S. Patents 9,111,357 and 9,466,004.
Pharma origins: Developed in partnership with global pharma product-security teams and validated using globally sourced, visually indistinguishable falsified and look-alike medicines curated over many years (US, EU, Asia). Across these challenge sets: zero false accepts, zero false rejects. References available under NDA.
Field‑validated: A preprint lab evaluation completed in partnership with the Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit (LOMWRU) and Medicine Quality Research Group in Lao PDR reported 100% sensitivity and 100% specificity across 48 samples (MedSnap Evaluation).
This 5 minute video provides a full demonstration of the MedSnap authentication process with two distinct samples: 1) authentic Viagra 100mg, and 2) a professional, nearly visually identical falsified sample of the same dose form.
Note how difficult it would be for a technician or pharmacist to spot the difference in the samples - but it is straightforward for MedSnap.
MedSnap works on Android devices.
The MedSnap platform can integrate at critical points of failure.
What’s a Snap? A calibrated image-capture session that authenticates a pill sample against trusted reference models (25 distinct visual features) and returns a pass/fail result with documented evidence in seconds. By authenticating upstream, MedSnap can reduce downstream rework and pharmacist interventions caused by misloads or verification false positives.
Goods Receiving & Quarantine - Policy: No Snap, No Release
Workflow: At receiving, flag high‑risk NDCs, shortage drugs, new suppliers, or DSCSA exceptions for a mandatory content check. Snap a sample from the bottle; results and images attach to the receipt/exception record. Suspect product is quarantined.
Value: Elevate compliance from data reconciliation to physical content verification, reducing the risk of DSCSA/FMD compliance gaps.
Central Pharmacy Robotics - Policy: No Snap, No Enable
Workflow: Require a MedSnap scan before enabling any bulk oral‑solid canister. A mismatch locks out the canister until a pharmacist resolves it, preventing wrong‑drug‑in‑canister events before they start.
Value: Harden automation against upstream misfills and falsified substitution.
Pouch & Adherence Packaging - Policy: Snap Exceptions Before Release
Workflow: Use MedSnap for spot‑checks on new lots, difficult‑to‑image tablets, and exceptions flagged by existing vision systems. Archive results with the lot or card record.
Value: Extend vision‑grade QA across the portfolio.
Returns-to-Stock (RTS) – Policy: No Snap, No Restock
Workflow: Require a MedSnap scan before any open pack, partial, or returned medication is restocked. A mismatch blocks restock until resolved, ensuring only authenticated product re-enters circulation.
Value: Close a known error pathway by preventing wrong-drug or compromised items from contaminating stock.
MedSnap is a patented, lab and field‑validated technology ready for enterprise deployment.
World-class professionals with decades of experience at the intersection of artificial intelligence, healthcare data analytics, and computer vision. Our founders previously built MedMined, a pioneer in AI-guided hospital-acquired infection surveillance and prevention, acquired by Cardinal Health in 2006 for approximately $100M and, through subsequent transactions, now part of BD (Becton, Dickinson and Company).