Experimental Medicine, Vol. 1, Issue 1, Sep  2018, Pages 31-44; DOI: 10.31058/j.em.2018.11003 10.31058/j.em.2018.11003

Variable and Attribute Control Charts in Trend Analysis of Active Pharmaceutical Components: Process Efficiency Monitoring and Comparative Study

Experimental Medicine, Vol. 1, Issue 1, Sep  2018, Pages 31-44.

DOI: 10.31058/j.em.2018.11003

Mostafa Essam Eissa 1*

1 Microbiology and Immunology Department, Faculty of Pharmacy, Cairo University, Cairo, Egypt

Received: 28 May 2018; Accepted: 15 June 2018; Published: 30 June 2018

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Abstract

Assessment of pharmaceutical product quality is important prerequisite to justify safe and effective release of the medicinal dosage form to the drug market. However, without rigorous implementation of good manufacturing practice (GMP), routine quality control testing may be not adequate to conclude compliance with reproducible procedures. Accordingly, the current study aimed to investigate manufacturing quality of pharmaceutical product batches through monitoring assay results and trends retrospectively for three components of the active ingredients using two types of control charts and to compare the value of each in-process monitoring. This product was manufactured in a pharmaceutical firm and subjected to the assay (expressed as relative potency to the claimed labeled dose per tablet) in quality control laboratory. The active components are Paracetamol (Acetaminophen) (Pa), Chlorpheniramine Maleate (CM) and Pseudoephedrine Hydrochloride (PH). General performance and trend of the studied batches were compared using Individual-Moving Range and Laney U΄ chart which were constructed using statistics software. Box-and-Whisker diagram that was constructed for the assay of the three active constituents showed that CM relative potency was significantly higher than Pa and PH using ANOVA (p<0.05). Capability analysis showed that Pa and PH assays have met the requirement of analysis. In contrast to CM potency which demonstrated a failure to be maintained within the specification window level as strong shift outside the upper border (right drift) could be observed. Both types of control charts variable (Individual-Moving Range) and attribute (Laney U΄) showed same control limits. But Individual-Moving Range was more sensitive in detection of out-of-control states.

Keywords

Individual-Moving Range, Laney U΄, Capability Analysis, Upper Control Limit, Lower Control Limit, GMP

Copyright

© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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