Quality control of an active ingredient in hair creams using near-infrared spectroscopy

Significance of the Topic

Quality control of active ingredients in cosmetic formulations is crucial to ensure product efficacy, safety and compliance with regulatory standards. Traditional methods such as LC-MS require extensive sample preparation and generate chemical waste, making rapid screening challenging. Near-infrared (NIR) spectroscopy offers a non-destructive, reagent-free alternative that significantly accelerates analysis and reduces laboratory burden.

Objectives and Study Overview

This application note describes a feasibility study for the rapid qualification of an antibacterial active ingredient (AI) in hair cream formulations using visible–NIR spectroscopy. The main goals were to develop a fast, out-of-specification screening method and to demonstrate its performance compared to conventional techniques.

Methodology

The study employed 14 hair cream samples with AI concentrations from 0.0% to 3.1%, plus a pure AI reference. Spectra were acquired on a Metrohm DS2500 Vis-NIR analyzer in transflection mode over 400–2500 nm, using gold reflectors and a slurry cup for sample placement. Data preprocessing involved a second derivative to correct for multiplicative scattering, followed by a wavelength-space maximum-distance algorithm focused on two AI-related regions: 1554–1750 nm and 2210–2340 nm. The quality model flagged concentration ranges between 1.8% and 2.5% as within specification.

Used Instrumentation

• NIRS DS2500 Analyzer (Order code 2.922.0010)
• Metrohm NIRS SlurryCup (Order code 6.7490.430)
• 2 mm Gold Diffuse Reflectors (Order code 6.7420.020)
• Vision Air 2.0 Complete Software (Order code 6.6072.208)

Key Results and Discussion

Spectral analysis revealed distinct absorption features of the AI in the designated wavelength regions. The developed calibration model successfully classified samples within and outside the 1.8–2.5% concentration window. Out-of-specification samples (below 1.8% or above 2.5%) were clearly identified, demonstrating robust discrimination between acceptable and non-acceptable batches.

Benefits and Practical Applications

• Rapid, reagent-free screening without chemical extraction
• Reduced analysis time compared to LC-MS (~30 minutes per sample)
• Minimized waste generation and improved laboratory sustainability
• Potential for in-line process control and high-throughput QA/QC

Future Trends and Potential Applications

Advancements in chemometric algorithms and integration with process analytical technology (PAT) will further enhance NIR-based quality control. Combining NIR with machine learning can improve prediction accuracy for complex cosmetic matrices. Portable and fiber-optic NIR probes may enable real-time monitoring in manufacturing lines and end-user settings.

Conclusion

The feasibility study confirms that Vis-NIR spectroscopy is a highly effective tool for rapid qualification of antibacterial actives in hair creams. The developed quality model delivers reliable out-of-spec detection with minimal sample preparation, offering significant time and cost savings for cosmetic quality control laboratories.