(583e) Near-Infrared Spectroscopy As a PAT Tool for Monitoring and Controlling Active Pharmaceutical Ingredient Crystallinity in High-Risk Drug-Product Manufacturing

Advancements in pharmaceutical manufacturing methodologies necessitate successful in-line monitoring tools, especially for critical quality attributes, which have safety and efficacy implications. The crystal form or polymorphism of active pharmaceutical ingredients has the potential to impact patients if not carefully monitored and controlled. The current standard for crystallinity monitoring is off-line analysis, which has limitations as manufacturing schemes move towards continuous modes. Near-infrared (NIR) spectroscopy is widely used for its ability to measure in-line real-time information about dynamic samples, which is advantageous in advanced manufacturing settings. Detection of crystallinity via NIR spectroscopy has been explored in a limited number of publications, providing foundational work for studying this phenomenon in the context of a control strategy for drug-product manufacturing. This work investigates NIR spectroscopy as a means of detecting crystallinity changes in both binary systems and multi-component systems.

This approach challenges the ability of NIR to detect crystallinity changes by introducing multiple excipients and trace amounts of API in the undesired crystal form. This multi-component system is more realistic than previously studied binary systems and provides the platform for a control strategy focused on maintaining the desired API crystal form

Figure 1. PC score plots highlighting the confidence ellipse for pure amorphous samples. Labeling is performed according to amorphous content (A) and by inclusion in the confidence ellipse (B).

Principal component analysis (PCA, Figures 1A & 1B) is used to visualize samples which deviate from the desired crystal form, and a partial least squares (PLS) regression model is applied to predict the concentrations of API crystal forms. This method demonstrates NIR as a reliable process analytical technology tool for real-time detection of crystallinity changes, facilitating control strategies for advanced manufacturing systems.

Disclaimer: This article reflects the views of the author and should not be construed to represent FDA’s views or policies.