Solutions for Accelerated Raw Materials Identification

Significance of the Topic

Ensuring the identity of pharmaceutical raw materials at receipt is a regulatory requirement and a critical quality control step. Conventional sampling based methods are time consuming, resource intensive, and introduce contamination risks and inventory delays. A rapid noninvasive approach can improve safety, reduce costs, accelerate production flow, and support First Time Quality goals.

Objectives and Study Overview

This white paper evaluates the Agilent Vaya handheld Raman system, which integrates Spatially Offset Raman Spectroscopy SORS for through container raw material verification. The study compares this technology with traditional cGMP raw material identification workflows and quantifies time and cost savings in a medium sized pharmaceutical warehouse.

Methodology and Instrumentation

The Agilent Vaya system combines an 830 nm excitation laser with offset and zero offset measurement geometry and automatic spectral subtraction to produce container free Raman spectra. Key hardware features include a NIST traceable system check test piece, ergonomic housing, integrated barcode scanner, Wi Fi connectivity, and chemical resistance. Software provides wizard based method development, pass fail decisions, batch processing, work in progress mode, user access control, and data integrity logic to support FDA 21 CFR Part 11 compliance. SORS enables acquisition of subsurface signals through opaque and scattering containers such as multilayer paper sacks, flexible intermediate bulk containers, plastic drums, and liners without opening or sampling.

Main Results and Discussion

In a comparative study of 1200 monthly samples, Vaya reduced annual raw material identification time from 22 370 to 1 047 hours and cut QA labor costs from USD 83 320 to USD 36 808. Per sample cost dropped from USD 5.80 to USD 2.50. Case examples on lactose monohydrate, sucrose, microcrystalline cellulose, and mannitol in multilayer paper sacks demonstrated reliable identification within 15 to 80 seconds per sample, eliminating bottlenecks associated with sampling booths and QC laboratory queues.

Benefits and Practical Applications

• Non destructive through container analysis preserves sterile conditions and product integrity
• Elimination of sampling booths reduces personal protective equipment use, consumables, and cross contamination risk
• Immediate release of raw materials accelerates production scheduling and reduces inventory levels
• Scalable 100 percent container verification supports evolving regulatory requirements without additional personnel

Future Trends and Opportunities

Integration of SORS based handheld Raman into warehouse management systems and laboratory information management systems will further streamline supply chains. Advances in chemometric libraries and machine learning driven spectral matching may enhance selectivity and enable real time quality monitoring across global distribution networks. Broader adoption in regulated industries such as food and specialty chemicals is anticipated as container compatibility expands.

Conclusion

The Agilent Vaya handheld Raman system leverages SORS to enable rapid noninvasive raw material identification through sealed containers, transforming cGMP workflows. It delivers substantial reductions in time, cost, and safety risks while meeting USP, EP, FDA 21 CFR Part 11, and ICH validation guidelines. Vaya provides a future proof solution for accelerating material release and reinforcing quality assurance in pharmaceutical manufacturing.

References

• Title 21 Code of Federal Regulations Part 211 Subpart I Section 211.84 on sampling and testing of incoming components
• European GMP Annex 8 Sampling of Starting and Packaging Materials