星点设计-效应面法优化美斯地浓聚乳酸纳米粒处方

目的星点设计-效应面法优化美斯地浓聚乳酸纳米粒处方。方法以复乳液中干燥法制备美斯地浓聚乳酸纳米粒,以包封率和载药量为评价指标,在单因素试验的基础上,用星点设计对显著性因素进行优化,并进行二项式方程拟合,以效应面法选取较好的工艺条件进行预测。结果以效应面法优选出的最佳工艺为:美斯地浓投药量为49.20 mg,PLA浓度为3.31%,PVA浓度为3.41%。制备的美斯地浓聚乳酸纳米粒平均包封率和载药量分别为(51.98±1.28)%和(7.01±0.31)%(n=3),与二项式拟合方程预测值相差<2%。结论应用星点设计-效应面法优化美斯地浓聚乳酸纳米粒制备工艺,能够快速、准确的得到最佳制备工艺,预测性良好。

Formulation Optimization of Mestinon Poly (Lactic Acid) Nanoparticles by Central Composite Design and Response Surface Methodology

OBJECTIVE To optimize the preparation technology of mestinon poly (lactic acid) nanoparticle (MTPNP) by using central composite design and response surface methodology. METHODS The MTPNP was prepared by double emulsion solvent evaporation method and evaluated by entrapment efficiency and drug loading. The single factor method was firstly used to investigate preparation technology, and a circumscribed central composite design (CCD) approach was chosen to properly formulate MTPNP. The binomial equations were fitted to the data of overall desirability. Response surface methodology was used to select and predict optimum conditions. RESULTS The optimum conditions for the preparation of MTPNP selected by response surface optimization were: mestinon was 49.20 mg, the PLA concentration was 3.31%, the PVA concentration was 3.41%. Under the optimal conditions, the entrapment efficiency and drug loading capacity was (51.98±1.28) and (7.01±0.31) % (n=3), respectively, and compared with the predict results of quadratic model were less than 2%. CONCLUSION Central composite design-response surface methodology can be used as a quick and accurate method to optimize the preparation technology of MTPNP, and has a good predictability.