Abstract
The fundamental principle of Quality by Design (QbD) is that the product quality should be designed into the process through an upstream approach, rather than be tested in the downstream. The keystone of QbD is process modeling, and thus, to develop a process control strategy based on the development of design space. Multivariate statistical analysis is a very useful tool to support the implementation of QbD in pharmaceutical process development and manufacturing. Nowadays, pharmaceutical process modeling is mainly focused on one-unit operations and system modeling for the development of design space across multi-unit operations is still limited. In this study, a general procedure that gives a holistic view for understanding and controlling the process settings for the entire manufacturing process was investigated. The proposed framework was tested on the Panax Notoginseng Saponins immediate release tablet (PNS IRT) production process. The critical variables and the critical units acting on the process were identified according to the importance of explaining the variability in the multi-block partial least squares path model. This improved understanding of the process by illustrating how the properties of the raw materials, the process parameters in the wet granulation and the compaction and the intermediate properties affect the tablet properties. Furthermore, the design space was developed to compensate for the variability source from the upstream. The results demonstrated that the proposed framework was an important tool to gain understanding and control the multi-unit operation process.
Highlights
In recent decades, pharmaceutical industries have made great contributions to human health by discovering and developing new drugs
Quality by Design (QbD) is defined as “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control based on sound science and quality risk management” [4]
The dried and milled granules were characterized by their bulk density (Db), tapped density (Dt), particle size distribution (D10, D50, D90, span), moisture content (MC), angle of repose (AOR) and Hausner ratio (HR)
Summary
Pharmaceutical industries have made great contributions to human health by discovering and developing new drugs. Pharmaceutical industries are mainly based on experience and fixed procedures for product and process development, and product manufacturing [3]. This is partly due to the strict regulatory framework under which pharmaceutical industries operate their business. The design space is a keystone of QbD approaches and allows the development of a robust and stable manufacturing process with a science-based rationale [6]. The main aim of this step is to study how the variables in different units are related and interact, in order to illustrate how the downstream units or intermediate and final product properties are affected by the raw materials properties or process parameters in the upstream units. The variable importance in the projection (VIP) [46] helps identify the CPPs that contribute most to the product quality
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