Solutions for Accelerated Raw Materials Identification

Importance of the Topic

In pharmaceutical manufacturing, verifying the identity of incoming raw materials is a regulatory requirement under current Good Manufacturing Practices (cGMP) and critical to ensuring product quality and patient safety. Traditional raw material identification (RMID) methods involve quarantine, container opening, sampling, and laboratory analysis, leading to delays, increased costs, and safety risks from chemical exposure. Rapid, non-destructive verification directly through packaging can streamline supply chain operations, reduce inventory dwell time, minimize hazards, and lower analytical workloads.

Objectives and Study Overview

This study evaluates the Agilent Vaya handheld Raman spectrometer, which integrates Spatially Offset Raman Spectroscopy (SORS), for in-container verification of pharmaceutical raw materials. The goals are to demonstrate how Vaya accelerates RMID workflows through opaque and transparent containers, compare its time and cost performance against conventional handheld Raman and FTIR methods, and assess its suitability for use by non-specialist operators in GMP environments.

Methodology

SORS leverages offset illumination and collection points to enhance subsurface signal collection from diffusely scattering media. Vaya automatically acquires both zero-offset (container-rich) and offset (subsurface-rich) spectra and computes a scaled subtraction to isolate the raw material signal. Experiments quantified identification times for common excipients—lactose monohydrate, microcrystalline cellulose, sucrose, mannitol, citric acid, and EDTA—through various packaging formats including multilayer paper sacks, plastic drums, and FIBCs. A cost-time model compared annual operator hours and expenses for processing 1,200 monthly samples using Vaya versus conventional Raman and FTIR workflows.

Used Instrumentation

The Agilent Vaya handheld Raman system features:

• SORS-enabled 830 nm laser with automatic zero-offset and offset measurements.
• NIST-traceable system check test piece for performance qualification.
• Integrated barcode scanner, Wi-Fi connectivity, and ergonomic chemical-resistant housing.
• Wizard-based software with pass/fail results, batch mode, and FDA 21 CFR Part 11 compliance.

Main Results and Discussion

Vaya identified raw materials through sealed containers in under 90 seconds, versus days-long RMID cycles with conventional methods. The system achieved over a 55% reduction in operator time and cost per sample (from $5.80 to $2.50). Case studies demonstrated clear identification of sucrose in 1.5 mm polypropylene, citric acid in white HDPE, and EDTA in brown paper sacks. By eliminating sampling booth operations, container handling, PPE use, and lab queuing, Vaya released materials to production on the same day of receipt.

Benefits and Practical Applications

Deploying Vaya in pharmaceutical warehouses offers:

• Faster RMID throughput without additional personnel or equipment.
• Reduced inventory holding and improved supply responsiveness.
• Enhanced safety by maintaining sealed packaging and minimizing exposure.
• Lower consumable and maintenance costs by bypassing sampling booths.
• Compliance with USP <858>/<1858>, ICH Q2(R1), and FDA 21 CFR Part 11.

Future Trends and Opportunities

Advancements may include integrating Vaya data with laboratory information management systems (LIMS) and AI-driven spectral analysis for automated anomaly detection. Expansion into biologics manufacturing, cosmetic supply chains, and food safety testing could further capitalize on non-destructive through-container screening. Continued miniaturization and enhanced chemometric algorithms will broaden its applicability to complex mixtures and low-concentration APIs.

Conclusion

The Agilent Vaya handheld Raman spectrometer streamlines raw material verification by applying SORS for reliable, rapid in-container analysis. It significantly reduces turnaround times, costs, and safety risks while supporting regulatory compliance. Vaya’s ease of use and connectivity features make it a practical solution for modern pharmaceutical quality control.

References

• Prullière F., Presly O. Solutions for Accelerated Raw Materials Identification with the Agilent Vaya Handheld Raman System. Agilent Technologies White Paper, 2021.
• USP General Chapter <858> Raman Spectroscopy; USP <1858> Validation of Infrared and Raman Spectrometric Methods.
• ICH Q2(R1): Validation of Analytical Procedures, International Council for Harmonisation, 2005.
• EU GMP Annex 8: Sampling of Starting Materials and Packaging Materials, European Medicines Agency.
• Title 21 Code of Federal Regulations Part 211: Current Good Manufacturing Practice for Finished Pharmaceuticals, U.S. Food and Drug Administration.