Hegazy Doaa, Tag Randa, Habib Basant Ahmed
Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
Int J Nanomedicine. 2022 Mar 12;17:1069-1086. doi: 10.2147/IJN.S337130. eCollection 2022.
This study aims to illustrate the potential of sequential experimentation for statistically scientific based optimization of Tazarotene (TAZA) cubosomes.
Hot melt emulsification method was used for cubosomes preparation. A preliminary (3.2) mixed factorial design (MFD) was conducted to choose suitable types of stabilizer and surfactant that maximize entrapment efficiency (EE) and minimize particle size (PS). These chosen stabilizer and surfactant were to be used in the statistical design proposed for optimization of TAZA cubosomes (I-optimal mixture design) (IOMD). Glyceryl monooleate (GMO), stabilizer and surfactant amounts were the three mixture components (MixCs) studied in that design. Responses (EE, PS and drug percent released after 24 hours (Q24h)) were statistically analyzed. Numerical optimization using desirability function based on different responses' importance was used to find an IOMD-optimized formulation (IOMD-OF) with the predetermined characters. Then, a novel statistical methodology of design space expansion was adopted to enhance Q24h. Suitable models to express EE, PS and Q24h were elucidated over the expanded mixture design (EMD) space. Validity of derived models was verified via prediction intervals and percent deviations of actual values from predicted ones for all the EMD design points. EMD was then navigated to find EMD-OF.
Analysis of MFD showed that Pluronic-F68 and polyvinyl alcohol were the best stabilizer and surfactant to be used. First stage optimization after IOMD analysis led to a formulation with unsatisfactory Q24h of 58.8%. After design space expansion adoption, re-analysis and re-optimization, a satisfactory EMD-OF having EE of 82.1%, PS of 273.0 nm and Q24h of 68.8% was found.
Statistical sequential experimentation with the novel design space expansion approach proved to be a successful paradigm for enhancing TAZA cubosomes optimization. Thus, this paradigm is expected to have promising future applications in various pharmaceutical formulations optimization.
本研究旨在阐明序贯实验在基于统计学科学优化他扎罗汀（TAZA）立方液晶纳米粒方面的潜力。
采用热熔乳化法制备立方液晶纳米粒。进行初步的（3.2）混合因子设计（MFD），以选择能使包封率（EE）最大化且粒径（PS）最小化的合适稳定剂和表面活性剂类型。这些选定的稳定剂和表面活性剂将用于为优化TAZA立方液晶纳米粒而提出的统计设计（I - 最优混合设计）（IOMD）中。单油酸甘油酯（GMO）、稳定剂和表面活性剂用量是该设计中研究的三种混合成分（MixCs）。对响应指标（EE、PS和24小时后药物释放百分比（Q24h））进行统计分析。基于不同响应指标的重要性，使用期望函数进行数值优化，以找到具有预定特性的IOMD优化配方（IOMD - OF）。然后，采用一种新的设计空间扩展统计方法来提高Q24h。在扩展混合设计（EMD）空间上阐明了表达EE、PS和Q24h的合适模型。通过预测区间以及所有EMD设计点实际值与预测值的偏差百分比来验证所推导模型的有效性。然后在EMD中进行探索以找到EMD - OF。
MFD分析表明，泊洛沙姆 - F68和聚乙烯醇是最佳的稳定剂和表面活性剂。IOMD分析后的第一阶段优化得到了一个Q24h为58.8%，不尽人意的配方。采用设计空间扩展、重新分析和重新优化后，发现了一个令人满意的EMD - OF，其EE为82.1%，PS为273.0 nm，Q24h为68.8%。
采用新的设计空间扩展方法进行统计序贯实验被证明是一种成功的范式，可用于加强TAZA立方液晶纳米粒的优化。因此，这种范式有望在各种药物制剂优化中具有广阔的未来应用前景。
