Patel Bhargavi M, Gohel Mukesh C, Thakkar Vaishali T, Baldaniya Lalji H, Christian Ruby R, Gandhi Tejal R
Gujarat Technological University, Anand Pharmacy College, Anand, Gujarat, India.
Turk J Pharm Sci. 2019 Jun;16(2):211-219. doi: 10.4274/tjps.galenos.2018.54871. Epub 2019 Mar 27.
The aim of the present investigation was to develop a solid dispersion of itraconazole (ITR) using sacrificial excipients like pregelatinized starch and spray-dried lactose alongside hydroxypropyl methylcellulose and Poloxamer 188, thereby arresting the conversion of the amorphous form of ITR to crystalline form, and to assess the dissolution stability of an amorphous form of the drug during short-term storage.
ITR-loaded solid dispersions were prepared by kneading. Formulation optimization was achieved by using a 2 full factorial design on the basis of cumulative percent drug released at t, t, and t min. An artificial neural network (ANN) was also applied as a statistical tool for obtaining better predictive ability and the outcomes of the ANN were compared with that of Design-Expert software.
The spectral data revealed no drug-carrier interactions. The P-X-ray diffraction study of the optimized batch showed a decrease in the crystallinity of drug as compared to the untreated drug. The dissolution studies of the optimized batch showed higher dissolution (92% at 120 min) in comparison to the other formulations. The dissolution stability study was performed at 40°C and 75% relative humidity for 90 days for the optimized formulation. The results of the optimized batch showed insignificant changes in cumulative percentage drug release during storage.
Dissolution stability could be attributed to the presence of sacrificial excipients as they tend to absorb moisture during storage and possibly get converted into crystalline form, thereby minimizing the recrystallization of ITR.
本研究旨在使用预胶化淀粉和喷雾干燥乳糖等牺牲性辅料以及羟丙基甲基纤维素和泊洛沙姆188来制备伊曲康唑（ITR）固体分散体，从而阻止ITR无定形形式向结晶形式的转化，并评估该药物无定形形式在短期储存期间的溶出稳定性。
通过捏合制备载ITR固体分散体。基于在t、t和t分钟时的累积药物释放百分比，采用2全因子设计实现配方优化。人工神经网络（ANN）也被用作一种统计工具以获得更好的预测能力，并将ANN的结果与Design-Expert软件的结果进行比较。
光谱数据显示不存在药物-载体相互作用。优化批次的P-X射线衍射研究表明，与未处理药物相比，药物的结晶度降低。优化批次的溶出研究表明，与其他配方相比，其溶出度更高（120分钟时为92%）。对优化配方在40°C和75%相对湿度下进行90天的溶出稳定性研究。优化批次的结果表明，储存期间药物累积释放百分比变化不显著。
溶出稳定性可归因于牺牲性辅料的存在，因为它们在储存期间倾向于吸收水分并可能转化为结晶形式，从而使ITR的重结晶最小化。
