Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, Lexington, KY 40536, US.
Department of Pharmaceutical Engineering, Inje University, Gimhae-si, Gyeongsangnam-do, South Korea.
J Control Release. 2015 Nov 10;217:82-91. doi: 10.1016/j.jconrel.2015.08.024. Epub 2015 Aug 23.
Reliable and predictive models of drug release kinetics in vitro and in vivo are still lacking for liposomal formulations. Developing robust, predictive release models requires systematic, quantitative characterization of these complex drug delivery systems with respect to the physicochemical properties governing the driving force for release. These models must also incorporate changes in release due to the dissolution media and methods employed to monitor release. This paper demonstrates the successful development and application of a mathematical mechanistic model capable of predicting doxorubicin (DXR) release kinetics from liposomal formulations resembling the FDA-approved nanoformulation DOXIL® using dynamic dialysis. The model accounts for DXR equilibria (e.g. self-association, precipitation, ionization), the change in intravesicular pH due to ammonia release, and dialysis membrane transport of DXR. The model was tested using a Box-Behnken experimental design in which release conditions including extravesicular pH, ammonia concentration in the release medium, and the dilution of the formulation (i.e. suspension concentration) were varied. Mechanistic model predictions agreed with observed DXR release up to 19h. The predictions were similar to a computer fit of the release data using an empirical model often employed for analyzing data generated from this type of experimental design. Unlike the empirical model, the mechanistic model was also able to provide reasonable predictions of release outside the tested design space. These results illustrate the usefulness of mechanistic modeling to predict drug release from liposomal formulations in vitro and its potential for future development of in vitro - in vivo correlations for complex nanoformulations.
对于脂质体制剂,仍然缺乏可靠且可预测的体内外药物释放动力学模型。开发稳健、可预测的释放模型需要系统地、定量地表征这些复杂的药物传递系统,以了解控制释放驱动力的物理化学性质。这些模型还必须考虑由于溶解介质和用于监测释放的方法而导致的释放变化。本文展示了成功开发和应用一种数学机械模型的情况,该模型能够预测类似于 FDA 批准的纳米制剂 DOXIL®的脂质体制剂中阿霉素(DXR)的释放动力学,使用动态透析法。该模型考虑了 DXR 的平衡(例如自缔合、沉淀、电离)、由于氨释放导致的囊内 pH 变化以及 DXR 通过透析膜的转运。该模型使用 Box-Behnken 实验设计进行了测试,其中包括释放条件(例如囊外 pH、释放介质中的氨浓度以及制剂的稀释(即悬浮液浓度))在内的变化。该机械模型的预测与观察到的 DXR 释放结果一致,直到 19 小时。预测结果与使用常用于分析此类实验设计生成的数据的经验模型的计算机拟合相似。与经验模型不同,机械模型还能够在测试设计空间之外提供合理的释放预测。这些结果说明了机械建模在预测脂质体制剂体外药物释放方面的有用性,以及其对复杂纳米制剂体内外相关性未来发展的潜力。