© 2015 Elsevier B.V. The pharmaceutical industry is under stringent regulations on quality control of their products because is critical for both, productive process and consumer safety. According to the framework of "process analytical technology" (PAT), a complete understanding of the process and a stepwise monitoring of manufacturing are required.Near infrared spectroscopy (NIRS) combined with chemometrics have lately performed efficient, useful and robust for pharmaceutical analysis. One crucial step in developing effective NIRS-based methodologies is selecting an appropriate calibration set to construct models affording accurate predictions.In this work, we developed calibration models for a pharmaceutical formulation during its three manufacturing stages: blending, compaction and coating. A novel methodology is proposed for selecting the calibration set -"process spectrum"-, into which physical changes in the samples at each stage are algebraically incorporated.Also, we established a "model space" defined by Hotelling's T2 and Q-residuals statistics for outlier identification - inside/outside the defined space - in order to select objectively the factors to be used in calibration set construction.The results obtained confirm the efficacy of the proposed methodology for stepwise pharmaceutical quality control, and the relevance of the study as a guideline for the implementation of this easy and fast methodology in the pharma industry.
|Journal of Pharmaceutical and Biomedical Analysis
|Published - 1 Oct 2015
- Model space
- Near infrared spectroscopy
- Partial least squares
- Principal component analysis
- Process analytical technology