Composition Dependency of the Flory–Huggins Interaction Parameter in Drug–Polymer Phase Behavior

弗洛里-哈金斯解理论 聚合物 溶解度 溶解度参数 材料科学 甲基丙烯酸酯 聚合物混合物 共聚物 药品 热力学 化学 有机化学 物理 心理学 精神科
作者
Jana Klueppelberg,Ulrich A. Handge,Markus Thommes,Judith Winck
出处
期刊:Pharmaceutics [MDPI AG]
卷期号:15 (12): 2650-2650 被引量:3
标识
DOI:10.3390/pharmaceutics15122650
摘要

An innovative strategy to address recent challenges in the oral administration of poorly soluble drugs is the formulation of amorphous solid dispersions (ASDs), where the drug is dissolved in a highly soluble carrier polymer. Therefore, special knowledge of the drug-polymer phase behavior is essential for an effective product and process design, accelerating the introduction of novel efficacious ASD products. Flory-Huggins theory can be applied to model solubility temperatures of crystalline drugs in carrier polymers over the drug fraction. However, predicted solubility temperatures lack accuracy in cases of strong drug/polymer interactions that are not represented in the Flory-Huggins lattice model. Within this study, a modeling strategy is proposed to improve the predictive power through an extension of the Flory-Huggins interaction parameter by a correlation with the drug fraction. Therefore, the composition dependency of the Flory-Huggins interaction parameter was evaluated experimentally for various drug-polymer formulations that cover a wide variety of drug and polymer characteristics regarding molecular weights, glass transition temperatures and melting temperatures, as well as drug-polymer interactions of different strengths and effects. The extended model was successfully approved for nine exemplary ASD formulations containing the drugs acetaminophen, itraconazole, and griseofulvine, as well as the following polymers: basic butylated methacrylate copolymer, Soluplus®, and vinylpyrrolidone/vinyl acetate copolymer. A high correlation between the predicted solubility temperatures and experimental and literature data was found, particularly at low drug fractions, since the model accounts for composition dependent drug-polymer interactions.

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