Strategy for design NIR calibration sets based on process spectrum and model space: An innovative approach for...

Area of Science:

• Pharmaceutical Sciences
• Analytical Chemistry
• Process Engineering

Background:

• Stringent pharmaceutical regulations necessitate robust quality control for product safety and process efficiency.
• Process Analytical Technology (PAT) frameworks require comprehensive process understanding and real-time manufacturing monitoring.
• Near-infrared spectroscopy (NIRS) coupled with chemometrics offers an efficient and reliable analytical tool for pharmaceutical applications.

Purpose of the Study:

• To develop robust NIRS-based calibration models for pharmaceutical formulations across three manufacturing stages: blending, compaction, and coating.
• To propose a novel methodology for selecting calibration sets by incorporating physical sample changes.
• To establish an objective outlier identification system for calibration set construction.

Main Methods:

• Development of calibration models using Near-Infrared Spectroscopy (NIRS) and chemometrics.
• Implementation of a "process spectrum" methodology to integrate physical changes during manufacturing stages.
• Utilization of Hotelling's T(2) and Q-residuals statistics to define a "model space" for objective outlier identification.

Main Results:

• The proposed "process spectrum" methodology effectively improved calibration models for pharmaceutical analysis.
• Objective outlier identification using the "model space" ensured the selection of appropriate factors for calibration sets.
• The methodology demonstrated efficacy in stepwise pharmaceutical quality control across blending, compaction, and coating stages.

Conclusions:

• The developed methodology provides an effective approach for stepwise pharmaceutical quality control.
• The study offers a valuable guideline for implementing NIRS and chemometrics in the pharmaceutical industry.
• This easy and fast methodology enhances the efficiency and reliability of pharmaceutical manufacturing analysis.