The aim of these studies was to determine the miscibility of different API with lipid excipients to predict drug loading and encapsulation properties for the production of solid lipid nanoparticles and nanostructured lipid carriers. Five API exhibiting different physicochemical characteristics, viz., clarithromycin, efavirenz, minocycline hydrochloride, mometasone furoate, and didanosine were used and six solid lipids in addition to four liquid lipids were investigated. Determination of solid and liquid lipids with the best solubilization potential for each API were performed using a traditional shake-flask method and/or a modification thereof. Hansen solubility parameters of the API and different solid and liquid lipids were estimated from their chemical structure using Hiroshi Yamamoto’s molecular breaking method of Hansen Solubility Parameters in Practice software. Experimental results were in close agreement with solubility parameter predictions for systems with ΔδT < 4.0 MPa^1/2. A combination of Hansen solubility parameters with experimental drug-lipid miscibility tests can be successfully applied to predict lipids with the best solubilizing potential for different API prior to manufacture of solid lipid nanoparticles and nanostructured lipid carriers.

这些研究的目的是确定不同的API与脂质赋形剂的混溶性，以预测用于生产固体脂质纳米颗粒和纳米结构脂质载体的载药量和包封性质。五个API表现出不同的理化特性，即，使用了克拉霉素，依法韦仑，盐酸米诺环素，糠酸莫米松和去羟肌苷，除了四种液体脂质外，还研究了六种固体脂质。使用传统的摇瓶法和/或其修改方法，确定每种API具有最佳增溶潜能的固体和液体脂质。API的Hansen溶解度参数以及不同的固体和液体脂质的化学结构是使用Hiroshi Yamamoto的《 Hansen溶解度参数在实践》软件中的分子分解方法从其化学结构估算出来的。对于ΔδT<4.0 MPa ^1/2的系统，实验结果与溶解度参数预测非常吻合。Hansen溶解度参数与实验性药物-脂质混溶性测试的结合可以成功地用于预测在制造固体脂质纳米颗粒和纳米结构脂质载体之前对不同API具有最佳增溶潜力的脂质。