Abstract
Herein, we aimed to develop a strategy to assess quality consistency of a drug product, with a focus on two typical cases of injection. Multi-variable analysis using a sequencing combination of factor analysis, one-way analysis of variance and cluster analysis identified all potential Critical Quality Attributes (CQAs) for each manufacturing process, which were identified from the attributes of quality standard (QAs) using supervised (cefazolin sodium pentahydrate, α-CEZ-Na) or unsupervised (cephathiamidine, CETD) analysis. All CQAs from QAs were applied to set up an integrated index, quality consistency attribute (QCA), to evaluate product quality consistency in a specific aspect. Meanwhile, real-time analysis by chemometrics-assisted near-infrared spectroscopy (NIR) was used to obtain useful information corresponding to the CQAs from the process attributes (PAs) of some of the critical processes. The quantitative results of characteristic signals of NIR by multiple linear regression was defined as the process consistency attribute (PrCA), and was used to assess the product quality consistency in another aspect. Therefore, either values of QCA or PrCA displayed sensitivity to changes in product quality, allowing us to establish a strategy with strong practicality, comprehensiveness and visualization to demonstrate the quality consistency of a specific product. Such strategy is not only conducive to the improvement of quality standards, but to the retrospective investigation of manufacturing processes which ultimately allowed maintenance of product consistency.
Highlights
The quality of a drug product should be strictly controlled to ensure its safety and efficacy; this serves as a basis for formulating quality standards
The samples from one type of production conditions was represented using Y1 = 0 and samples from another production condition type represented using Y2 = 1. b The procedure to reduce the data dimensions. c The procedure to assess quality consistency using the index of quality consistency attribute (QCA). d The recognition rate of changes (RRC) is the matching rate between cluster results given by cluster analysis and real groups identified by the production conditions
RRCmax was the highest RRC of possible Critical Quality Attributes (CQAs) in a production process. e The process consistency attribute (PrCA) is the discriminant value calculated by multiple linear regression, another index to assess quality consistency
Summary
The quality of a drug (medicinal) product should be strictly controlled to ensure its safety and efficacy; this serves as a basis for formulating quality standards. The quality standards of drugs contain attributes such as drug definition, identification, assay, and impurities. Many other attributes such as crystal form, particle size, and bacterial contamination are significantly influenced by changes in the manufacturing process. These changes may in turn affect the quality of the drugs as discussed in the 60th Technical Report of the Parenteral Drug Association The ICH Q8 (R2) defines the Critical Quality Attribute (CQA) as the physical, chemical, biological, or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality is achieved (International Conference on Harmonisation, 2009).
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