Adulterated Pharmaceutical Product Detection Using Statistical Process Control

Authors

  • Mostafa Essam Eissa Microbiology and Immunology Department, Cairo University, Cairo

DOI:

https://doi.org/10.3329/bpj.v21i1.37900

Keywords:

cGMP, FDA, Statistical process control, QC, PC, API

Abstract

Drugs manufactured in pharmaceutical companies - that do not comply to current Good Manufacturing Practice (cGMP) - are considered by Food and Drug Administration (FDA) as "adulterated medicines", even if they did not impose any health or quality risk to the final consumers. Non compliance to cGMP has adverse effects on both customers and companies with think again escalating legal penalties may be issued. In the current study, newly established pharmaceutical plant launched film coated tablet for treatment of common cold symptoms. The local regulatory agency in collaboration with quality team of a well-established pharmaceutical company in the area has conducted large survey that covered new firms to elucidate the compliance of the facilities of those newly emerging companies to cGMP, partially using statistical process control (SPC). The generated results for the product by quality control (QC) and in-process control (IPC) were processed using statistical software packages. Trending of data brought the focus on hardness test which later highlight the need to investigate dissolution pattern of the three active components of the dosage form. Time series plot of hardness for 195 batches manufactured during 2016 showed non consistency and stability of the process which can be segmented chronologically into three distinct segments. A significant negative correlation (-0.64 by Spearman correlation) was found between the hardness and the dissolution of one the active pharmaceutical ingredient (API) viz, Pseudoephedrine Hydrochloride. Inconsistent operation during hardness as IPC test was reflected in the dissolution QC test. Effect on other properties should be investigated.

Bangladesh Pharmaceutical Journal 21(1): 7-15, 2018

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Published

2018-08-15

How to Cite

Eissa, M. E. (2018). Adulterated Pharmaceutical Product Detection Using Statistical Process Control. Bangladesh Pharmaceutical Journal, 21(1), 7–15. https://doi.org/10.3329/bpj.v21i1.37900

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