Mylan School of Pharmacy and the Graduate School of Pharmaceutical Sciences
Crushing Strength, Near-Infrared Spectroscopy, Relative Density, Risk Factors, Scale of Scrutiny
Process Analytical Technology (PAT) systems are used in the pharmaceutical industry to enhance the understanding and control the manufacturing processes. They are defined as systems for designing, analyzing, and controlling manufacturing operations through timely measurements of critical quality attributes of raw/in-process materials, with the goal of ensuring quality of final drug products.
Near-Infrared (NIR) spectroscopy is a commonly used analytical part of the PAT toolbox. It offers advantages such as rapid/non-destructive analysis, limited sample preparation, and specificity to physical/chemical quality attributes. The implementation of NIR-based PAT systems enables real-time quality monitoring and process control strategies, which mitigates the risks to process efficiency and product quality. Some examples include reduction in manufacturing cycle times, prevention of rejects, increased automation, real-time release, and improved resource utilization associated with development/manufacturing.
The use of PAT systems mitigates manufacturing risks to product quality; however, they can also introduce additional risks. The uncertainty of PAT methods contributes to the risks of inaccurate quality estimations. These risks depend on factors related to method development such as chemical variability, instrumentation optical design, scale of scrutiny, and calibration algorithms. The performance statistics of PAT methods can be used to represent the risks associated with its use for estimating quality.
This research assessed the risk factors, i.e. chemical variability, instrumentation optical design, scale of scrutiny, and calibration algorithms with respect to impacting the performance of NIR-based PAT methods for predicting quality indices of powder blending, tableting, and roller compaction. The International Conference on Harmonization (ICH) Q9 guidance provides strategies for implementing quality risk management with respect to product development. This dissertation focuses on extending these concepts for assessing risks associated with the use of NIR methods. The knowledge gained by this research enhances our ability to develop accurate and robust NIR methods for prediction of quality attributes of solid oral dosage forms. This will ultimately aid in minimizing risks to product quality and patient health.
Talwar, S. (2015). Near-Infrared (NIR) Spectroscopy-based Pharmaceutical Process Analytical Technology (PAT) Systems: Risk and Performance (Doctoral dissertation, Duquesne University). Retrieved from http://ddc.duq.edu/etd/66