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Predicted values for human total clearance of a variety of typical compounds with differently humanized-liver mouse plasma data
Drug Metabolism and Pharmacokinetics ( IF 2.1 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.dmpk.2020.05.004
Keigo Nakayama 1 , Hidetaka Kamimura 2 , Hiroshi Suemizu 2 , Nao Yoneda 2 , Megumi Nishiwaki 3 , Kazuhiko Iwamoto 1 , Mari Mizunaga 1 , Tamotsu Negoro 1 , Soichiro Ito 1 , Hiroshi Yamazaki 4 , Yukihiro Nomura 1
Affiliation  

Prediction of human pharmacokinetics is important in the preclinical stage. Values for total clearance of compounds from plasma should be one of the most important pharmacokinetic parameters for predictions. Although several physiological and empirical methods including single-species allometry for prediction of values for human clearance of compounds using humanized-liver mice have been reported, further improvement of prediction accuracies would be still expected. To optimize these approaches, we proposed methods for unbound intrinsic clearance in virtually 100% humanized-liver mouse by incorporating unbound plasma fractions of compounds in differently humanized-liver mice. Comparisons of prediction accuracies of values for human clearance of 15 model compounds were performed among our current physiological and previously reported models and single-species allometry using humanized-liver mice. Incorporation of the actual unbound plasma fractions of compounds and correction of residual mice hepatocyte in humanized-liver mice showed comparable prediction accuracy to that by single-species allometry. After exclusion of 3 compounds with large species differences in values of clearance and unbound plasma fractions between mice and humans out of 15 compounds, prediction accuracies were improved in the methods investigated. The previously and present reported physiological methods could show the good prediction accuracy of values for clearance of drugs from plasma.

中文翻译:

具有不同人源化肝脏小鼠血浆数据的各种典型化合物的人类总清除率的预测值

人体药代动力学的预测在临床前阶段很重要。化合物从血浆中的总清除率值应该是预测的最重要的药代动力学参数之一。尽管已经报道了几种生理学和经验方法,包括使用人源化肝小鼠预测人类清除化合物的值的单物种异速生长,但仍有望进一步提高预测准确性。为了优化这些方法,我们提出了通过在不同的人源化肝脏小鼠中加入未结合的化合物血浆部分,在几乎 100% 的人源化肝脏小鼠中进行未结合的内在清除的方法。在我们当前的生理学模型和先前报道的模型以及使用人源化肝小鼠的单物种异速生长中,对 15 种模型化合物的人类清除率值的预测准确性进行了比较。结合化合物的实际未结合血浆组分和校正人源化肝小鼠中残留的小鼠肝细胞显示出与单物种异速生长相当的预测准确性。在排除了 15 种化合物中小鼠和人之间清除率和未结合血浆分数值具有较大物种差异的 3 种化合物后,所研究方法的预测准确性得到了提高。以前和现在报道的生理学方法可以显示从血浆中清除药物的值的良好预测准确性。结合化合物的实际未结合血浆组分和校正人源化肝小鼠中残留的小鼠肝细胞显示出与单物种异速生长相当的预测准确性。在排除了 15 种化合物中小鼠和人之间清除率和未结合血浆分数值具有较大物种差异的 3 种化合物后,所研究方法的预测准确性得到了提高。以前和现在报道的生理学方法可以显示从血浆中清除药物的值的良好预测准确性。结合化合物的实际未结合血浆组分和校正人源化肝小鼠中残留的小鼠肝细胞显示出与单物种异速生长相当的预测准确性。在排除了 15 种化合物中小鼠和人之间清除率和未结合血浆分数值具有较大物种差异的 3 种化合物后,所研究方法的预测准确性得到了提高。以前和现在报道的生理学方法可以显示从血浆中清除药物的值的良好预测准确性。在排除了 15 种化合物中小鼠和人之间清除率和未结合血浆分数值具有较大物种差异的 3 种化合物后,所研究方法的预测准确性得到了提高。以前和现在报道的生理学方法可以显示从血浆中清除药物的值的良好预测准确性。在排除了 15 种化合物中小鼠和人之间清除率和未结合血浆分数值具有较大物种差异的 3 种化合物后,所研究方法的预测准确性得到了提高。以前和现在报道的生理学方法可以显示从血浆中清除药物的值的良好预测准确性。
更新日期:2020-08-01
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