Opaque Container Analysis Capabilities of the Agilent Vaya Handheld Raman Spectrometer

Significance of the Topic

Ensuring accurate and efficient raw material identification is critical in pharmaceutical and biopharmaceutical production. Traditional Raman methods often require opening containers, posing risks such as contamination, sample exposure, and added labor. Spatially offset Raman spectroscopy (SORS) overcomes these limitations by enabling noninvasive analysis through opaque packaging, streamlining workflows in warehouse quarantine areas.

Study Objectives and Overview

This application note evaluates the Agilent Vaya handheld Raman spectrometer’s capability to identify common pharmaceutical excipients and active ingredients through opaque blue high-density polyethylene barrels. The study demonstrates how the built-in SORS-based container subtraction algorithm isolates pure Raman signatures of materials inside barrels without specialized sampling procedures.

Methodology and Instrumentation

The Agilent Vaya instrument employs SORS by acquiring two spectra:

• Zero‐offset spectrum: laser and detector aligned, capturing container‐dominant signal.
• Offset spectrum: laser laterally shifted, enriching subsurface (content) signal.

An on‐board algorithm scales and subtracts the zero spectrum from the offset to remove container interference. Experimental materials included acetaminophen, citric acid, ibuprofen salt, lactose monohydrate, polyethylene glycol 8000, povidone, and sorbitol. Each powder (200 g) was sealed in an LDPE bag and placed inside a blue HDPE barrel. A UV-Vis–NIR Cary 5000 confirmed the barrel’s high absorption at 830 nm (Vaya’s laser wavelength). The method development wizard guided users to collect reference spectra of samples in vials, empty containers, and materials through containers, automatically selecting optimal laser offsets and subtraction workflows.

Main Results and Discussion

SORS-based measurements through blue barrels yielded distinct, high‐quality Raman spectra for each material within ~50 seconds per sample. The optimized container subtraction algorithm effectively removed barrel contributions, even for low‐cross‐section materials like lactose. The Vaya’s sensitivity and wizard‐guided method development ensured robust identification without user expertise in spectroscopy.

Benefits and Practical Applications

Using the Vaya for raw material identification at receipt offers:

• Noninvasive testing without container opening or sampling booths.
• Reduced risk of contamination and no need for consumables or PPE.
• Faster decision-making in quarantine areas, supporting higher throughput.
• Compliance with global pharmacopeia requirements (USP, EP, Chinese and Japanese Pharmacopeias).

Future Trends and Possibilities

Advances may include enhanced algorithms for thicker or multi‐layered containers, expansion to other packaging types (e.g., metal or composite barrels), and integration with digital traceability systems. Real‐time connectivity and cloud-based spectral libraries could further streamline supply‐chain verification and quality assurance across industries.

Conclusion

The Agilent Vaya handheld Raman spectrometer, leveraging SORS and automated container subtraction, provides a disruptive solution for point‐of‐need raw material identification through opaque barrels. It enhances safety, efficiency, and regulatory compliance in pharmaceutical and biopharmaceutical warehouse operations.