Multivariate Analysis and Computational Predictability of Modified Release Formulation of Chirally Pure Metoprolol Succinate

Abstract

This study employs computational techniques to predict the performance of a modified-release matrix formulation of chirally pure S (-) metoprolol succinate, using a Quality by Design (QbD) approach. The research defines the Quality Target Product Profile (QTPP) and Critical Quality Attributes (CQAs) of the S (-) metoprolol succinate matrix formulation. To assess risks, an Ishikawa diagram and Failure Mode Effect Analysis (FMEA) following ICH Q8 guidelines were conducted. The formulation screening process utilized Plackett–Burman design, followed by optimization through Box–Behnken design. The modified-release formulation was developed using high shear granulation, incorporating a combination of high and low viscosity Hydroxypropyl Methylcellulose (HPMC) polymers along with other excipients. The impact of polymer composition and stearic acid on the release profile of S (-) metoprolol succinate was investigated, revealing their significant influence on the drug delivery system's desired effect. Specifically, the variables X1: HPMC K4M and X2: HPMC K100M were identified as key factors affecting drug release (Y1). Statistical analysis (ANOVA) confirmed the significance of the selected model, with predicted outcomes aligning well with observed results, comparable to the reference product Seleken® XL range. Both drug content and release performance were found to be similar to the innovator formulation. In summary, this investigation underscores the potential of employing a QbD approach with a combination of low and high viscosity HPMC polymers to achieve precise single-dose delivery of S (-) metoprolol succinate.

Received: 19 July 2023 | Revised: 13 November 2023 | Accepted: 21 December 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.