Identification and Mitigation of Risks using Quality Risk Assessment Tools for Formulation Development of Pazopanib HCl Extrudates by using HME Technique: A Systematic QbD Approach

Abstract

Introduction: Pharmaceutical development ensures to design a valued product and robust manufacturing process to consistently deliver intended performance. It is necessary to recognize that quality cannot be tested into drug products but it should be built in during formulation design and development. Pazopanib HCl is a protein kinase inhibitor molecule approved by USFDA and European agencies for the treatment of renal cell carcinoma (RCC) patients and other renal malignancies, but it has very poor aqueous solubility and drug release. Therefore, it is essential need to improve the solubility and in vitro dissolution characteristics. Objective/Aim: The main objective of this study was to prepare stable Pazopanib HCl extrudates (PZP-Ex) by using the Quality by Design (QbD) approach. Method: Pazopanib HCl extrudates (PZP-Ex) was manufactured using hot melt extrusion technique. Initially, the quality target product profile (QTPP) and critical quality attributes (CQAs) were identified, and then risk assessment was done using a heat map and failure mode and effect analysis (FMEA) approach. A full factorial design (FFD) was used to study the impact of two continuous variables i.e., level of polymer, milling speed and one categorical (milling screen type) factor on particle size distribution (PSD), disintegration time and dissolution of extrudates. Results: The significance (p) value for studied response variables i.e., percent retention on 40 mesh ASTM sieve (420 µ), disintegration time and percent drug release in 15 min were 0.006, 0.0243 and 0.0355 respectively from the actual by a predicted plot which signifies that the model is significant. The polymer-to-drug ratio has a significant impact on drug release and disintegration time of extrudates. Conclusion: Pazopanib HCl extrudates were successfully prepared by HME technique. Critical formulation and process parameters such as polymer to drug ratio, milling screen size and milling speed were optimized using FFD.