Abstract

Background: Despite being in use for over 50 years, the physicochemical challenges posed by methyldopa remain ever present. Methyldopa is not only significantly hygroscopic, but also prone to oxidative and hydrolytic degradation that can be accelerated by moisture. Poor compression behaviour, another limitation of methyldopa, leaves the formulation scientist with a constellation of formulation hurdles that must be faced, understood, and overcome. This is a task that can be tackled using elements of the Quality by Design (QbD) approach. Objective: The study aimed at developing an optimal formulation of methyldopa into 250 mg immediate release tablets by direct compression using elements of QbD. Method: Excipients of pharmaceutical grade were selected for the candidate formulation, preliminary concentrations set for each and settings for mixing and compression variables established. The risk posed by all these factors was evaluated using Failure Modes and Effects Analysis (FMEA). The preliminary experiment was executed using a 12 run Plackett Burman design. A 16 run Box-Behnken experimental design successfully aided in the identification of excipient concentrations and manufacturing conditions that yield tablets of optimal quality. Results: FMEA revealed that magnesium stearate, colloidal silica, sodium starch glycolate (SSG), citric acid monohydrate, mixing speed, duration of pre-lubrication mixing, duration of lubrication and compression speed were critical risk factors. The optimal formulation was achieved at the following settings: 1 % m/m magnesium stearate, 1 % m/m colloidal silica, 3.9 % m/m sodium starch glycolate, 1.7 % m/m citric acid monohydrate, mixing speed of 101 rpm, 6 minutes of pre-lubrication mixing, 2 minutes of lubrication and compression speed of 20 rpm. Conclusion: The QbD tools used in this study enabled, not only achievement of optimal quality, but also a better understanding of the impact of critical formulation variables on tablet quality. Challenges to pharmaceutical development can be effectively overcome using the QbD approach.

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