Formulation design space for stable, pH sensitive crystalline nifedipine nanoparticles

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• 作者：Rajan Jog ; Kenechi Unachukwu ; Diane J. Burgess ; ^{diane.burgess@uconn.edu" class="auth_mail" title="E-mail the corresponding author} ; ^{d.burgess@uconn.edu" class="auth_mail" title="E-mail the corresponding author} (Distinguished Professor of Pharmaceutics)
• 关键词：API ; active pharmaceutical ingredient ; ANOVA ; analysis of variance ; BCS ; biopharmaceutical classification system ; DoE ; design of experiment ; ICH ; international council for harmonisation of technical requirements for pharmaceuticals for human use ; PDI ; polydispersity index
• 刊名：International Journal of Pharmaceutics
• 出版年：2016
• 出版时间：30 November 2016
• 年：2016
• 卷：514
• 期：1
• 页码：81-92
• 全文大小：2982 K

文摘

Enteric coated formulations protect drugs from degrading in the harsh environment of the stomach (acidic pH and enzymes), and promotes drug delivery to and absorption into the duodenum and/or later parts of the intestine. Four DoE models were applied to optimize formulation parameters for the preparation of pH sensitive nifedipine nanoparticles. Stability studies were performed on the optimized formulations to monitor any possible variation in particle size distribution, homogeneity index, surface charge and drug release (pH 1.2 and pH 6.8). Stability studies were performed for 3 months at 4 °C, 25 °C and 40 °C. A combination of Eudragit^®L 100-55 and polyvinyl alcohol was determined to be the most effective in stabilizing the nanoparticle suspension. The average particle size distribution, polydispersity index and surface charge of the optimized pH sensitive nifedipine nanoparticles were determined to be 131.86 ± 8.21 nm, 0.135 ± 0.008 and −7.631 ± 0.146 mV, respectively. Following three months storage, it was observed that the formulations stored at 4 °C were stable in terms of particle size distribution, polydispersity index, surface charge, drug loading and drug release, whereas those stored at 25 °C and 40 °C were relatively unstable. A predictive model to prepare stable pH sensitive nifedipine nanoparticles, was successfully developed using multiple linear regression analysis.