Rationally designed lipid- and food-based drug formulations to enhance oral bioavailability

摘要 超过40%的上市药物和大约90%的研发管道中的药物存在较差的含水性 溶解度和相关的低生物利用度。食物，尤其是脂质，可以显著增强 此类药物的生物利用度。这种“食物效应”可以通过开发以脂肪和食物为基础的食品来实现。 表现出增强吸收效率的配方，因此可以设计成降低 药物剂量，同时保持相同的全身暴露。值得注意的是，使用食品成分作为配方 辅料还可以减轻食物对生物利用度的影响，从而允许患者服用这些药物。 与食物无关，降低用药方案的复杂性，并最终解决显著的 患者依从性低的问题。然而，脂类和食物在口服给药中的使用受到限制，部分原因是缺乏 能够预测胃肠道的先验脂肪功能及其对药物吸收的影响。我们的团队已经开发出 一种可预测食物数量和组成对药物吸收和生物利用度影响的算法 从机械论的观点来看。具体地说，我们的算法考虑了多个并行的、动态的过程(药物 溶出度、脂肪和蛋白质消化、药物在胶体中的分配、吸收)来定量预测影响 与食物相关的脂肪和蛋白质对口服生物利用度的影响。此方法通过以下方式提供巨大的价值 合理定量指导利用脂类和其他食品成分开发改进的剂型 配方辅料。在这个项目中，我们的目标是开发一种生物利用度较低的口服药物的新配方。 已知受食物影响很大的药物，并被限制只能在饭后服用。这部小说 剂型将显示出增强的能力，因为它们可以以较低的剂量给药 相同的治疗效果和用法，无论有没有食物，都不会影响生物利用度。发展中的 这些公式将证明我们的算法的实际应用，以改善不良的口头表达 通过利用食物效应获得生物可用药物。在第一个目标中，将对现有算法进行修改以预测 脂蛋白乳剂给药后的药物药代动力学。动能 参数将在体外测量，并用作模型输入参数，以指导选择最优的 与上市制剂生物等效性的药物剂量和脂质-蛋白质混合物组合物。在第二个 目的：利用该建模框架，选择一种能够 作为脂类制剂在胶囊内给药。配方参数(例如，药物剂量、赋形剂 成分)将被优化以通知开发与市场上的生物等效性的配方 剂型。所有制剂之间的生物等效性将通过狗的药代动力学研究来证明。 这些目标的成功实现将证明我们的模型可以1)有效地指导合理的设计 具有增强的生物利用度的基于食品和脂类的新配方，以及2)可以开发更低的 剂量配方，同时保持与市场上销售的剂型相同的暴露和治疗效果。

Abstract More than 40% of marketed drugs and about 90% of drugs in development pipelines suffer from poor aqueous solubility and associated low bioavailability. Food, and lipids in particular, can significantly enhance the bioavailability of such drugs. This “food effect” could be exploited by developing lipid- and food-based formulations that demonstrate enhanced efficiency absorption, and as a result can be designed at a reduced drug dose while maintaining the same systemic exposure. Notably, using food components as formulation excipients would also mitigate food effects on bioavailability, thus allowing patients to take these medications irrespective of food, reducing the complexity of medication regiments, and ultimately addressing the significant issue of low patient adherence. However, lipid and food use in oral drug delivery is limited, in part, due to lack of ability to predict a priori lipid function in the GI tract and its effect on drug absorption. Our team has developed an algorithm that can predict the impact of food quantity and composition on drug absorption and bioavailability from a mechanistic point of view. Specifically, our algorithm considers multiple parallel, dynamic processes (drug dissolution, lipid and protein digestion, drug partitioning in colloids, absorption) to quantitatively predict the impact of food-associated lipids and proteins on oral bioavailability. This approach offers tremendous value by enabling rational quantitative guidance in developing improved dosage forms using lipids and other food ingredients as formulation excipients. In this project, we aim to develop novel formulations of a poorly bioavailable oral marketed drug that is known to be significantly impacted by food and is restricted to be taken only after a meal. The novel dosage forms will demonstrate enhanced capabilities in that they can be administered at a lower dose for the same therapeutic effect and administration with or without food will not impact bioavailability. Development of these formulations will demonstrate the practical application of our algorithm to improve oral delivery of poorly bioavailable drugs by exploiting the food effect. In the first aim, the existing algorithm will be adapted to predict drug pharmacokinetics after administration of an aqueous lipid/protein emulsion-based delivery vehicle. Kinetic parameters will be measured in vitro and used as model input parameters to inform selection of the most optimal drug dose and lipid-protein mixture composition that is bioequivalent to the marketed formulation. In the second aim, the modeling framework will be employed to select a lipid-surfactant-cosolvent system that can be administered as a lipid-based formulation inside a capsule. Formulation parameters (e.g., drug dose, excipient composition) will be optimized to inform development of a formulation that is bioequivalent to the marketed dosage form. Bioequivalence among all formulations will be demonstrated via pharmacokinetic studies in dogs. Successful completion of these aims will demonstrate that our model can 1) effectively inform rational design of novel food- and lipid-based formulations with enhanced bioavailability, and 2) can allow development of lower dose formulations while maintaining the same exposure and therapeutic effect as the marketed dosage form.