首页> 外文期刊>European journal of pharmaceutical sciences >In silico prediction of the solubility advantage for amorphous drugs - Are there property-based rules for drug discovery and early pharmaceutical development?
【24h】

In silico prediction of the solubility advantage for amorphous drugs - Are there property-based rules for drug discovery and early pharmaceutical development?

机译:在计算机模拟中预测无定形药物的溶解度优势-药物发现和早期药物开发是否有基于属性的规则?

获取原文
获取原文并翻译 | 示例
           

摘要

Oral delivery of poorly water-soluble compounds is often a substantial challenge. Once a drug candidate is selected, it is desirable to predict, based on chemical structure, which formulation technology has the highest potential to enhance drug solubility and absorption. Due to the importance of amorphous drug formulations, this work aimed at calculating the solubility ratio of amorphous and crystalline drug using in silico methods only. Molecular modeling together with multivariate methods was employed and a particular aim was to find simple structure-based rules for the technology selection of amorphous drug formulations. As a result, calculated estimates for reference compounds were generally higher than experimentally obtained amorphous solubility ratios; however, the rank order of the values revealed a significant correlation (p = 0.036). Subsequently, a set of 56 neutral poorly water-soluble compounds resulted in a good partial least square model with R2 of 0.803. Most important for the amorphous solubility ratio was molecular weight, number of hydrogen bond acceptors, melting point, number of torsional bonds and polar surface area. By considering the Lipinsky rules, we proposed suitable ranges of these molecular predictors with respect to selecting promising amorphous drug formulations. Such structure- based guidance can help in early formulation development of challenging drug candidates, thereby leading to substantial cost savings. However, there is certainly more experimental research needed to finally assess how broadly the presented concepts can be applied. ? 2012 Elsevier B.V. All rights reserved.
机译:口服递送水溶性差的化合物通常是一个重大挑战。一旦选择了候选药物,就需要根据化学结构预测哪种配制技术具有提高药物溶解度和吸收率的最高潜力。由于无定形药物制剂的重要性,这项工作旨在仅使用计算机方法计算无定形药物和结晶药物的溶解度比。使用了分子建模和多元方法,一个特殊的目的是为无定形药物制剂的技术选择找到简单的基于结构的规则。结果,参考化合物的计算估计值通常高于实验获得的无定形溶解度比。但是,这些值的排名顺序显示出显着的相关性(p = 0.036)。随后,一组56种中性水溶性差的化合物产生了一个良好的偏最小二乘模型,R2为0.803。对于无定形溶解度比而言,最重要的是分子量,氢键受体的数目,熔点,扭转键的数目和极性表面积。通过考虑Lipinsky规则,我们就选择有希望的无定形药物制剂提出了这些分子预测因子的合适范围。这种基于结构的指导可以帮助具有挑战性的候选药物的早期配方开发,从而节省大量成本。但是,当然需要更多的实验研究来最终评估所提出概念的应用范围。 ? 2012 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号