Quality control in manufacturing process by near infrared spectroscopy

Area of Science:

• Analytical Chemistry
• Pharmaceutical Sciences
• Spectroscopy

Background:

• Near-infrared spectroscopy (NIR) is a valuable tool for analyzing pharmaceutical products.
• Routine quality control requires methods to assess product conformity and detect process deviations.
• Existing methods may not fully capture all critical quality attributes influencing NIR spectra.

Purpose of the Study:

• To develop and validate a novel method for pharmaceutical mixture qualification using NIR spectroscopy.
• To integrate pattern recognition techniques for enhanced data analysis.
• To assess the capability of the method in identifying critical process deviations.

Main Methods:

• Utilized near-infrared spectroscopy (NIR) for spectral data acquisition.
• Applied pattern recognition techniques in conjunction with standard instrument software.
• Developed and employed a new program (DISPLOT) for advanced data visualization and analysis.
• Analyzed scaled distances versus wavelength plots for deviation detection.

Main Results:

• The combined approach successfully determined the conformity of pharmaceutical mixtures.
• The method demonstrated effectiveness in identifying process deviations, including moisture content, particle size variations, and non-homogeneity.
• The DISPLOT program provided a new way to visualize and interpret spectral data for qualification.

Conclusions:

• The integration of pattern recognition with NIR spectroscopy offers a robust solution for routine pharmaceutical product quality control.
• This method provides a sensitive and reliable means to detect critical deviations in pharmaceutical manufacturing processes.
• The DISPLOT program enhances the analytical capabilities of NIR spectroscopy for pharmaceutical qualification.