What is it about?
This article is about using Statistical Quality Control (SQC) tools, specifically Statistical Process Control (SPC), to monitor and inspect the quality characteristics of a sustained-release capsule product (Vitamin C pellets in a hard gelatin capsule) in a pharmaceutical company. The study monitored properties like: Average filling weight Potency determination (assay of active pharmaceutical ingredient) Dissolution profile (DR1, DR4, DR8 - dissolution rate after one, four, and eight hours) Bulk and finished product yield (BLK and FN yield) Disintegration The goal was to ensure the stability of the pharmaceutical properties, identify areas for improvement, and check compliance with Good Practices guidelines (GxP), such as Good Manufacturing Practice (GMP). The findings showed that while none of the batches were "out-of-specification" (OOS), the SPC analysis revealed intermittent "out-of-control" (OOC) states in all monitored properties. This suggests that although the product met the minimum regulatory requirements, the manufacturing process itself was not consistently stable and predictable.
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Why is it important?
The study highlights the critical importance of using proactive process monitoring like SPC, rather than solely relying on the final product testing, especially in the highly regulated pharmaceutical industry. Impact on Health: Pharmaceutical products are unique and must meet the highest quality standards because they directly affect the health of the final consumers. Early Warning System: SPC provides a valuable tool to detect non-conformance of processes and deviations from GxP rules before a true quality failure (a catastrophic excursion or an OOS result) occurs in the final product. Process Stability: Compliance with GxP is meant to ensure a consistent, predictable, and reproducible manufacturing process. The study's results—OOC states despite OOS compliance—demonstrate that the product's quality can mask an underlying deviating system. A process not under statistical control has abnormal variability that could be due to factors like machine wear, procedure issues, or material changes, requiring corrective and preventive actions (CAPA). SISPQ: The consistent quality of pharmaceuticals is linked to five essential characteristics: Safety, Identity, Strength, Purity, and Quality (SISPQ). Monitoring and controlling the process is vital to embedding these properties reliably.
Perspectives
Industry Perspective (Pharmaceutical Manufacturing) The study serves as a warning alarm for pharmaceutical manufacturers, even those with products that pass final inspection. The presence of out-of-control points indicates that the manufacturing process is unstable and prone to future catastrophic outcomes, potentially leading to severe financial and reputation loss. Manufacturers must implement strict standard operations and corrective actions based on SPC findings to ensure their processes are consistently under control and predictable, not just compliant with minimum specifications. Regulatory Perspective (FDA, GxP) Regulatory bodies like the United States Food and Drug Administration (USFDA) work to ensure that GxP guidelines are followed. The goal of Current Good Manufacturing Practice (cGMP) is consistency and the ability to prove that the process delivers the expected product properties. The detection of OOC states, even without OOS results, suggests a lack of the reproducible operation that regulatory bodies expect when GxP standards are followed. This indicates that compliance to GxP needs improvement and that the reliance on product testing alone can be misleading for achieving true quality. Scientific/Technical Perspective (Statistical Quality Control) The research demonstrates the utility of advanced SPC tools (specifically, Individual-Moving Range charts and Laney attribute charts) in a pharmaceutical context. It shows that data visualization methods, such as box plots and capability histograms, are crucial for spotting outliers and understanding the shape of process distribution (e.g., bimodal or multimodal) that indicate abnormal process variability or interfering processes. Statistically, a process that is not in a state of control requires investigation and improvement, regardless of whether the product meets specifications.
Independent Researcher & Consultant Mostafa Essam Eissa
Read the Original
This page is a summary of: Application of Statistical Quality Control Tools for Monitoring of Pharmaceutical Product Properties, Biological Sciences - PJSIR, April 2019, PCSIR-Scientific Information Center,
DOI: 10.52763/pjsir.biol.sci.62.1.2019.39.48.
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