Automated moisture analysis in pharmaceutical peptides

Significance of the Topic

Residual moisture in lyophilized pharmaceutical peptides is a critical quality attribute affecting product stability, efficacy, and shelf life. Reliable moisture quantification is essential for quality control, process optimization, and regulatory compliance.

Study Objectives and Overview

The article evaluates near-infrared spectroscopy (NIRS) as a fast, reagent-free, non-destructive method for residual moisture analysis in lyophilized peptides. It compares NIRS predictions to Karl Fischer titration reference values, aiming to develop a robust calibration and validation model.

Methodology

Lyophilized peptide samples with varying moisture levels were measured using a Metrohm NIRS XDS OptiProbe Analyzer and an 815 Robotic Sample Processor. Seventeen samples were divided into calibration (11) and validation (6) sets. Spectral preprocessing involved second derivative treatment, and a partial least squares (PLS) regression model was constructed. Outlier detection was applied using a maximum wavelength distance algorithm on pre-treated spectra.

Used Instrumentation

• NIRS XDS Interactance OptiProbe Analyzer (model 2.921.1510)
• Robotic USB Sample Processor XL (815 Robotic, model 2.815.0010)
• Vision Air 2.0 spectroscopy software (model 6.6072.208)
• tiamo 3.0 light USB titration software (model 6.6056.301)

Main Results and Discussion

The NIRS calibration model achieved a correlation coefficient (R2) of 0.99 when comparing predicted moisture to Karl Fischer titration. Standard errors of calibration (SEC) and validation (SEV) were 0.054% and 0.061%, respectively, demonstrating high sensitivity and accuracy of the NIRS method.

Benefits and Practical Applications

• Non-destructive and reagentless analysis preserving sample integrity.
• Rapid measurement and high-throughput capability with robotic automation.
• Real-time process monitoring potential for freeze-drying optimization.
• Reduced analysis time and operational costs compared to traditional titration.

Future Trends and Possibilities

Integration of NIRS into process analytical technology (PAT) frameworks may enable inline moisture monitoring and advanced process control. Combining NIRS with machine learning algorithms could further enhance predictive performance. Expanding this approach to other dosage forms and scales offers broad analytical applications.

Conclusion

Near-infrared spectroscopy provides a fast, accurate, and non-invasive alternative to Karl Fischer titration for residual moisture determination in lyophilized pharmaceutical peptides. The high correlation and low error metrics support its implementation in routine quality control and process development.