Romanian Society of Pharmaceutical Sciences
 

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APPLYING THE PRINCIPLES OF QUALITY BY DESIGN (QbD) COUPLED WITH MULTIVARIATE DATA ANALYSIS (MVDA) IN ESTABLISHING THE IMPACT OF RAW MATERIAL VARIABILITY FOR EXTENDED RELEASE TABLETS

KINGA ILYÉS 1, TIBOR CASIAN 1*, DANA HALES 1, GHEORGHE BORODI 2, LUCIA RUS 3,
RAREȘ ȘTIUFIUC 4,5, IOAN TOMUȚĂ 1

1Department of Pharmaceutical Technology and Biopharmacy, Faculty of Pharmacy, “Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
2National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
3Department of Drug Analysis, Faculty of Pharmacy, “Iuliu Hațieganu” University of Medicine and Pharmacy, ClujNapoca, Romania
4Department of Pharmaceutical Biophysics, Faculty of Pharmacy, “Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
5MedFuture Research Centre for Advanced Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, ClujNapoca, Romania

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The raw material is acknowledged to be a source of variability, however, the conventional, empirical development approach does not offer much information regarding its critical attributes and how processes can be modulated to remain in the constant quality region of the product. The study aimed to develop extended release hydrophilic matrix tablets with indapamide based on the Quality by Design (QbD) concept, evaluating the impact of interchanging different types and suppliers of raw material on the finished product quality profile. Results showed significant in vitro release test variability, with 16 - 71% failure rates when compared to four different EMA and FDA dissolution specification recommendations. Design of experiments based impact assessment concluded that the active pharmaceutical ingredient, hydroxypropyl methylcellulose and compression force was accountable for the variation, while orthogonal partial least squares (O2PLS) based root cause analysis extension redefined results in term of critical material attributes. Findings suggest that a risk-based, multivariate analysis assisted control strategy for the incoming raw materials could prevent quality concerns within routine manufacturing.