Savla Ronak, Browne Jeff, Plassat Vincent, Wasan Kishor M, Wasan Ellen K
a Catalent Pharma Solutions , Somerset , NJ , USA.
b Catalent Pharma Solutions , St. Petersburg , FL , USA.
Drug Dev Ind Pharm. 2017 Nov;43(11):1743-1758. doi: 10.1080/03639045.2017.1342654. Epub 2017 Jul 6.
Lipid-based drug delivery systems (LBDDS) are one of the most studied bioavailability enhancement technologies and are utilized in a number of U.S. Food and Drug Administration (FDA) approved drugs. While researchers have used several general rules of thumb to predict which compounds are likely to benefit from LBDDS, formulation of lipid systems is primarily an empiric endeavor. One of the challenges is that these rules of thumb focus in different areas and are used independently of each other. The Developability Classification System attempts to link physicochemical characteristics with possible formulation strategies. Although it provides a starting point, the formulator still has to empirically develop the formulation. This article provides a review and quantitative analysis of the molecular properties of these approved drugs formulated as lipid systems and starts to build an approach that provides more directed guidance on which type of lipid system is likely to be the best for a particular drug molecule.
基于脂质的药物递送系统（LBDDS）是研究最多的生物利用度提高技术之一，并被用于许多美国食品药品监督管理局（FDA）批准的药物中。虽然研究人员已经使用了一些经验法则来预测哪些化合物可能从LBDDS中受益，但脂质系统的配方主要是一项凭经验的工作。其中一个挑战是，这些经验法则关注的领域不同，且相互独立使用。可开发性分类系统试图将物理化学特性与可能的配方策略联系起来。尽管它提供了一个起点，但配方设计师仍需凭经验开发配方。本文对这些制成脂质系统的获批药物的分子特性进行了综述和定量分析，并开始构建一种方法，为特定药物分子哪种脂质系统可能是最佳选择提供更具针对性的指导。
