Batch Statistical Process Monitoring Approach to a Cocrystallization Process.

Area of Science:

• Pharmaceutical Science
• Materials Science
• Chemical Engineering

Background:

• Cocrystals enhance drug solubility, bioavailability, and stability while preserving active pharmaceutical ingredient (API) bioactivity.
• Noncovalent interactions form cocrystals, offering a method to improve drug properties.
• Furosemide and nicotinamide cocrystals are investigated for improved therapeutic potential.

Purpose of the Study:

• To implement and validate near-infrared spectroscopy (NIRS) for on-line monitoring of furosemide-nicotinamide cocrystallization.
• To utilize process analytical technology (PAT) for real-time control and detection of process deviations.
• To establish statistical process control models for ensuring consistent cocrystal formation.

Main Methods:

• Cocrystallization of furosemide and nicotinamide was achieved via solvent evaporation.
• On-line monitoring was performed using near-infrared spectroscopy (NIRS).
• Principal component analysis (PCA) and batch statistical process monitoring (BSPM) were employed for spectral analysis and control charting.

Main Results:

• NIRS successfully monitored the cocrystallization process in real-time.
• Statistical process models effectively detected abnormal variations in critical process parameters, such as solvent and component amounts.
• Control charts provided clear visualization of process trajectories under normal and non-normal conditions.

Conclusions:

• NIRS is a viable PAT tool for on-line monitoring and control of pharmaceutical cocrystallization processes.
• The integration of NIRS with statistical process models enhances the ability to detect and manage process deviations, ensuring product quality and consistency.
• This approach facilitates robust manufacturing of furosemide-nicotinamide cocrystals with improved properties.