Institute of Pharmacy, Faculty I of Natural Sciences, Martin Luther University Halle-Wittenberg, 06120, Halle/Saale, Germany; Department of Pharmaceutical Technologies, Merck KGaA, 64293 Darmstadt, Germany.
Department of Pharmaceutical Technologies, Merck KGaA, 64293 Darmstadt, Germany.
Eur J Pharm Sci. 2018 Nov 1;124:339-348. doi: 10.1016/j.ejps.2018.08.035. Epub 2018 Aug 30.
The predictability of preformulation screening tools for polymer selection in amorphous solid dispersions (ASD) regarding supersaturation and precipitation was systematically examined. The API-polymer combinations were scaled up by means of hot-melt extrusion and spray-drying to verify the predictions. As there were discrepancies between a solvent-based screening and performance of ASD, a new screening tool with improved predictability at minimal investments of time and material is presented. The method refinement resulted in a better correlation between the screening and ASD prototypes. So far, a purely solvent-based screening was used which consisted of film casting by rapid solvent evaporation. This approach was improved by applying a heating step after film casting. Four representative polymers were tested with two different model active pharmaceutical ingredients (API) under non-sink dissolution conditions. Polyvinylpyrrolidone (PVP) based polymers showed no benefit towards pure API in the solvent-based screening but good supersaturation as ASD formulations. The extrudates with the cellulose derivatives hydroxypropylmethylcellulose acetate succinate (HPMCAS) and cellulose acetate phthalate (CAP) showed lower supersaturation than predicted by the solvent-based screening but performed especially well as spray-dried dispersions (SDD). False negative results for PVP-co-vinyl acetate (PVP-VA64) could be avoided by using the new melt-based screening. Furthermore, comparing the results from the two different screening methods allowed predicting the performance of extrudates vs. SDD with cellulose derivatives as polymeric excipients.
系统地考察了预配方筛选工具在预测无定形固体分散体（ASD）中聚合物选择方面对超饱和度和沉淀的可预测性。通过热熔挤出和喷雾干燥将 API-聚合物组合放大，以验证预测。由于溶剂型筛选与 ASD 的性能之间存在差异，因此提出了一种新的筛选工具，该工具在时间和材料投入最小的情况下具有更高的可预测性。方法改进导致筛选和 ASD 原型之间的相关性更好。到目前为止，一直使用基于溶剂的筛选，该筛选由快速溶剂蒸发的薄膜铸造组成。通过在薄膜铸造后施加加热步骤，改进了该方法。在非溶出条件下，用两种不同的模型活性药物成分（API）测试了四种代表性聚合物。基于聚乙烯吡咯烷酮（PVP）的聚合物在溶剂型筛选中对纯 API 没有益处，但作为 ASD 制剂具有良好的超饱和度。与溶剂型筛选预测相比，具有羟丙基甲基纤维素醋酸琥珀酸酯（HPMCAS）和醋酸邻苯二甲酸纤维素（CAP）的纤维素衍生物挤出物的超饱和度较低，但作为喷雾干燥分散体（SDD）的性能特别好。通过使用新的熔融基筛选，可以避免 PVP-co-醋酸乙烯酯（PVP-VA64）的假阴性结果。此外，比较两种不同筛选方法的结果允许预测纤维素衍生物作为聚合物赋形剂的挤出物与 SDD 的性能。
