• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Symposium on Industrial Crystallization >Structural modelling for the prediction of impurity purge during pharmaceutical crystallizations
【24h】

Structural modelling for the prediction of impurity purge during pharmaceutical crystallizations

机译：用于预测药物结晶期间杂质吹扫的结构模型

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Changes in pharmaceutical development paradigms, spurred by the recent evolution of the regulatory landscape, have reinforced the need for science-based decision making in process development. With the majority of active pharmaceutical ingredients (APIs) formulated as solids crystallization remains not only a key unit operation in pharmaceutical manufacturing, but also a crucial stage gate for the control of physicochemical attributes of APIs. While strategies for the control of solid form [1] and attributes such as particle size [2] are reasonably well developed, predictive tools for the assessment of impurity purge are still somewhat lacking. More recently, an approach has emerged which is rapidly establishing itself within the pharmaceutical industry for the estimation of purge factors for potentially genotoxic impurities (PGIs) on the basis of reactivity, solubility, volatility, ionisability and likelihood of separation via chromatography [3]. This method has been successfully applied to several compounds [4,5], demonstrating that a conservative approach to estimating PGIs purge can enable process development chemists to rapidly identify impurities of concern, and determine the appropriate control and analytical strategies accordingly. While this methodology is successful in determining the appropriate strategies for PGIs, a complementary tool enabling computationally-accessible prediction of partition coefficients of impurities in the product crystal lattice during crystallization remains elusive, despite promising literature reports [6]. Such approach would be complimentary to the one described for PGIs because it would help development chemists understand when the natural limit for impurity purge has been reached and no further optimisation is necessary, or a different purification strategy altogether is required, involving for instance an alternative technique such as chromatography or the implementation of a re-crystallization step. With this in mind, we have worked towards the implementation of molecular mechanics modelling in the prediction of impurity purge for starting materials, intermediates and APIs. Using experimental data from the literature and from Pfizer's impurity purge studies for several compounds to refine and validate the method, a series of categories was defined for impurities depending on the predicted purge, thus informing further steps in process development. The methodology is discussed here, alongside a summary of results and two examples of implementation on literature cases, 4-methyl-2-nitroacetanilide and adipic acid, highlighting the practical implementation of this methodology as an emerging decision-making tool in process development.
机译：由监管景观最近演变的制药发展范式的变化加强了在流程开发中基于科学的决策的需求。对于配制的大多数活性药物成分（API），作为固体结晶，不仅是药物制造的关键单元操作，而且是用于控制API的物理化学属性的关键阶段栅极。虽然对固体形式的策略[1]和诸如粒度[2]的策略合理发达，但用于评估杂质吹扫的预测工具仍然缺乏。最近，已经出现了一种方法，这在制药行业内迅速建立了本身，以估计基于反应性，溶解性，挥发性，电离和通过色谱分离的溶解性，溶解性，挥发性，电离性和可能性[3]来估计潜在的遗传毒性杂质（PGI）的净化因子。该方法已成功应用于几种化合物[4,5]，证明了估计PGI清除的保守方法可以使过程开发化学家能够快速识别关注的杂质，并相应地确定适当的控制和分析策略。虽然该方法是成功确定PGI的适当策略，但尽管有前途的文献报告[6]，但在结晶期间，可以实现互补工具在结晶过程中能够在结晶期间的杂质中的分配系数的分配系数。这种方法将是由对PGI描述的人提供的，因为它将有助于开发化学家了解杂质吹扫的自然限制并且不需要进一步优化，或者需要不同的净化策略，涉及例如替代技术如色谱或再结晶步骤的实施。考虑到这一点，我们已经在预测原料，中间体和API的杂质吹扫中实施了分子力学建模。使用来自文献的实验数据和辉瑞的杂质吹扫研究进行了几种化合物来细化和验证方法，根据预测的清除，为杂质定义了一系列类别，从而了解进一步的过程开发步骤。这里讨论了方法，以及文献病例的结果和实施例，4-甲基-2-硝基丙酮和己二酸的两个实施例，突出了该方法的实际实施，作为过程开发中的新出现决策工具。

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