DSCSA Compliance
and Faster Distribution. QicScan AI Delivers Both.
Pharmaceutical distributors are required to capture, verify, and exchange serialized product data at every transaction point. Most are doing it one scan at a time.
QicScan AI uses Vision AI to capture barcodes, serial numbers, product images, and case counts simultaneously from a standard handheld device. One capture event replaces dozens of manual scans, without adding hardware, headcount, or infrastructure.
The Compliance Burden Is Real.
The Current Workflow Makes It Worse.
DSCSA full enforcement requires pharmaceutical distributors to capture and exchange enhanced product identifier data at every point in the supply chain. That means serialization verification at receiving, outbound confirmation before shipment, exception documentation for damaged or expired product, and a complete audit trail available on demand.
However, most distribution operations are meeting those requirements today with manual scanning workflows. Each case on a pallet gets scanned individually. Images are captured separately on a phone. Counts are verified by hand. Three separate touchpoints for every product, on every pallet, across every shift.
Compliance requirements are not going away. The question is whether the workflow supporting it is built for the volume you are moving.
Where One-at-a-Time Scanning Creates Risk.
Inbound Receiving
A standard pharma pallet carries 42 cases. At individual scan rates that is 42 discrete scan events before a single unit is verified. Across 300 pallets per day, that is 12,600 manual scans, each one a chance for a missed scan or count mismatch.
Outbound Verification
Before product ships, serialization data must be confirmed and exchanged with the trading partner. Manual scan-by-scan verification at outbound creates the same volume problem as receiving, with the added pressure of shipment timing.
Exceptions Handling
Exception handling requires rapid capture of product data, condition images, and documentation for partner resolution. When that process depends on a separate scanner and a separate phone camera, the case file takes minutes to build.
Cycle Count Accuracy
Comparing on-hand counts against a manifest or spotting EPCIS discrepancies manually is time-consuming and error-prone. A single miscounted pallet can create downstream compliance exposure that takes hours to resolve.
How QicScan AI Handles Pharma Distribution.
QicScan AI replaces the multi-step manual capture process with a single handheld scan event. Point the device at a pallet or a group of cases. The Vision AI engine captures barcodes, serial numbers, 2D codes, OCR label data, product images, and case counts simultaneously. No separate phone for images. Zero manual count. Not one re-scan loop.
Barcode Scanning
Reads all barcode types including 2D Data Matrix and GS1 codes required for DSCSA compliance. Multiple units captured in a single frame, not one at a time.
OCR Label Reading
Captures printed label information beyond what the barcode contains, including lot numbers, expiration dates, and NDC data, without a separate scan step.
Inventory Count
Verifies case counts automatically using Vision AI object detection. Flags discrepancies against expected quantities before product moves.
Audit-Ready Image Storage
Every scan session stores product thumbnails automatically. Full visual audit trail available for inspections, partner disputes, and FDA review without manual documentation.
Operator Assist
Prompts the operator in real time if a product in the camera view has not been captured. Prevents the missed scans that create downstream compliance gaps.
Exception Routing
Routes flagged items directly to your WMS or track-and-trace system for resolution. Reduces exception handling from minutes to seconds.
Built for Pharma Distribution Environments.
QicScan AI installs on existing Android devices. No new scanning hardware, no lengthy IT deployment, and no disruption to current WMS or ERP integrations. Edge computing on the device handles intermittent connectivity common in large distribution center environments. Data syncs to the cloud when connectivity is restored with no lost capture events.
Installs on existing Android devices. No new hardware procurement required.
Edge computing handles low connectivity environments. No lost capture events.
Integrates with your current WMS, ERP, and DSCSA track-and-trace software.
On-premise or cloud deployment available to match your existing infrastructure.
Deployed across 30 distribution centers at a Fortune 20 healthcare company. ROI measurable in weeks.
Use Cases by Stakeholder.
Pharma Manufacturers
Track unit-level serialization from production through packaging. Verify batch numbers, expiration dates, and GS1 compliance at speed. Capture 2D codes required for DSCSA and EU FMD without slowing the production line.
Distributors and Logistics
Scan incoming shipments and update inventory in real time. Maintain a digital chain of custody at every transaction point. Confirm serialization data at outbound before shipment exchanges hands. Handle exceptions faster with simultaneous image and data capture.
Retailers and Pharmacies
Reduce time spent on stocktaking and reordering. Verify medication accuracy at dispensing. Enable mobile ordering and inventory scanning on existing smart devices without dedicated hardware.
Results From the Field.
42-Case Pallet. One Scan.
Barcodes, counts, and images captured simultaneously.
50 to 70%
Reduction in inventory handling time.
Seconds
Exception handling that previously took 5 to 6 minutes.
30 Sites
Distribution centers at a Fortune 20 healthcare company.
Weeks
Typical time to measurable ROI.
No New Hardware
Installs on existing Android devices. Operational from day one.
Ready to See It in Your Distribution Operation?
QicScan AI is built for the volume and compliance requirements of pharmaceutical distribution. See how a single scan event can replace your current manual capture workflow.
Machine Vision-Based Data Capture and Barcode Scanning Solutions for Pharma, Food, Retail & Logistics
Phone: 989-657-6583
Email: info@qicscan.ai
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