Habib Basant A, AbouGhaly Mohamed H H
a Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy , Cairo University , Cairo , Egypt.
Expert Opin Drug Deliv. 2016 Jun;13(6):777-88. doi: 10.1517/17425247.2016.1166202. Epub 2016 Apr 4.
This study aims to illustrate the applicability of combined mixture-process variable (MPV) design and modeling for optimization of nanovesicular systems.
The D-optimal experimental plan studied the influence of three mixture components (MCs) and two process variables (PVs) on lercanidipine transfersomes. The MCs were phosphatidylcholine (A), sodium glycocholate (B) and lercanidipine hydrochloride (C), while the PVs were glycerol amount in the hydration mixture (D) and sonication time (E). The studied responses were Y1: particle size, Y2: zeta potential and Y3: entrapment efficiency percent (EE%). Polynomial equations were used to study the influence of MCs and PVs on each response. Response surface methodology and multiple response optimization were applied to optimize the formulation with the goals of minimizing Y1 and maximizing Y2 and Y3.
The obtained polynomial models had prediction R(2) values of 0.645, 0.947 and 0.795 for Y1, Y2 and Y3, respectively. Contour, Piepel's response trace, perturbation, and interaction plots were drawn for responses representation. The optimized formulation, A: 265 mg, B: 10 mg, C: 40 mg, D: zero g and E: 120 s, had desirability of 0.9526. The actual response values for the optimized formulation were within the two-sided 95% prediction intervals and were close to the predicted values with maximum percent deviation of 6.2%.
This indicates the validity of combined MPV design and modeling for optimization of transfersomal formulations as an example of nanovesicular systems.
本研究旨在阐明混合过程变量（MPV）设计与建模相结合在纳米囊泡系统优化中的适用性。
采用D - 最优实验设计方案，研究三种混合成分（MCs）和两个过程变量（PVs）对乐卡地平传递体的影响。混合成分包括磷脂酰胆碱（A）、甘氨胆酸钠（B）和盐酸乐卡地平（C），而过程变量为水合混合物中的甘油量（D）和超声处理时间（E）。所研究的响应指标为Y1：粒径，Y2：zeta电位，Y3：包封率百分比（EE%）。使用多项式方程研究混合成分和过程变量对每个响应指标的影响。应用响应面法和多响应优化来优化制剂，目标是使Y1最小化，Y2和Y3最大化。
所得到的多项式模型对Y1、Y2和Y3的预测R(2)值分别为0.645、0.947和0.795。绘制了等高线图、皮佩尔响应轨迹图、扰动图和相互作用图以表示响应情况。优化后的制剂配方为：A：265mg，B：10mg，C：40mg，D：0g，E：120s，可取性为0.9526。优化制剂的实际响应值在双侧95%预测区间内，且与预测值接近，最大偏差百分比为6.
