Duquesne University Graduate School of Pharmaceutical Sciences, 600 Forbes Ave., Pittsburgh, PA 15282, USA.
Int J Pharm. 2011 Oct 14;418(2):217-26. doi: 10.1016/j.ijpharm.2011.06.003. Epub 2011 Jul 3.
The use of a novel, in silico method for making an intelligent polymer selection to physically stabilize small molecule organic (SMO) solid compounds formulated as amorphous molecular solid dispersions is reported. 12 compounds (75%, w/w) were individually co-solidified with polyvinyl pyrrolidone:vinyl acetate (PVPva) copolymer by melt-quenching. Co-solidified products were analyzed intact using differential scanning calorimetry (DSC) and the pair distribution function (PDF) transform of powder X-ray diffraction (PXRD) data to assess miscibility. Molecular descriptor indices were calculated for all twelve compounds using their reported crystallographic structures. Logistic regression was used to assess correlation between molecular descriptors and amorphous molecular solid dispersion potential. The final model was challenged with three compounds. Of the 12 compounds, 6 were miscible with PVPva (i.e. successful formation) and 6 were phase separated (i.e. unsuccessful formation). 2 of the 6 unsuccessful compounds exhibited detectable phase-separation using the PDF method, where DSC indicated miscibility. Logistic regression identified 7 molecular descriptors correlated to solid dispersion potential (α=0.001). The atomic mass-weighted third-order R autocorrelation index (R3m) was the only significant descriptor to provide completely accurate predictions of dispersion potential. The three compounds used to challenge the R3m model were also successfully predicted.
报道了一种新颖的、基于计算的方法，用于智能选择聚合物，将小分子有机（SMO）固体化合物物理稳定在无定形分子固体分散体中。12 种化合物（75%，w/w）分别与聚乙烯吡咯烷酮-醋酸乙烯酯（PVPva）共聚物通过熔融淬火共固化。使用差示扫描量热法（DSC）和粉末 X 射线衍射（PXRD）数据的配对分布函数（PDF）变换对完整的共固化产物进行分析，以评估其混溶性。使用所有 12 种化合物的报告晶体结构计算了分子描述符指数。使用逻辑回归评估分子描述符与无定形分子固体分散体潜力之间的相关性。最后使用三个化合物对模型进行了挑战。在 12 种化合物中，有 6 种与 PVPva 混溶（即成功形成），有 6 种相分离（即不成功形成）。6 种不成功形成的化合物中有 2 种使用 PDF 方法检测到相分离，而 DSC 表明混溶性。逻辑回归确定了 7 个与固体分散体潜力相关的分子描述符（α=0.001）。原子质量加权三阶 R 自相关指数（R3m）是唯一能够准确预测分散体潜力的重要描述符。用于挑战 R3m 模型的三种化合物也得到了成功预测。
