期刊文献+

生理药代动力学模型在预测转运体介导药物相互作用中的应用

Application of physiologically based pharmacokinetic models in the prediction of drug-drug interactions mediated by transporters
原文传递
导出
摘要 生理药代动力学模型通过与经典药代动力学模型类似的数学框架构建而成,并按已知的生理学知识设置参数,由大量分别对应于体内不同器官或组织的房室组成,并通过类似血液循环的系统而连接。因能较准确的预测药物在体内过程,故其在药物研发行业尤其是药物相互作用领域,逐渐崭露头角。本文将从生理药代动力学模型的概念、与经典模型的优势比较及其在转运体介导的药物相互作用中的应用等方面进行综述。 Physiologically based pharmacokinetic(PBPK) models are built using a mathematic framework which is similar to these classic pharmacokinetic(PK) models,and are parameterized based on known physiology knowledge,and comprise many compartments corresponding to different organs and tissues in the body,which are connected by flow rates that parallel the circulating blood system.The values of PBPK models are gradually appreciated in the industry of drug development,especially in the field of drug- drug interaction due to their robust ability to predict drugs' kinetic process in vivo.Then some basic concepts,advantages over classic models and their applications in drug- drug interaction fields associated with transporters of PBPK models are reviewed in the next context.
出处 《中国临床药理学杂志》 CAS CSCD 北大核心 2015年第24期2483-2485,共3页 The Chinese Journal of Clinical Pharmacology
基金 国家自然科学基金资助项目(81160411) 江西省自然科学基金资助项目(20151BAB205084) 江西省青年科学家培养计划资助项目(20133BCB23006)
关键词 生理药代动力学模型 转运体 药物相互作用 预测 physiologically based pharmacokinetic transporter drug-drug interaction predicition
  • 相关文献

参考文献12

  • 1Nestorov I. Whole body pharmacokinetic models [ J ]. Clin Phar- macokinet, 2003, 42:883 - 908.
  • 2Jones H, Rowland - Yeo K. Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development [ J ]. COT Pharmacometrics Syst Pharmacol, 2013, 2 : 1 - 12.
  • 3Krishnan K, Brodeur J. Toxic interactions among environmental poilu- tants:corroborating laboratory observations with human experience [ J ]. Environ Health Perspect , 1994,102(Suppl 9) :Sll.
  • 4Krishnan K, Haddad S, Belivean M, et al. Physiological modeling and extrapolation of phannacokinetic interactions from binary to more complex chemical mixtures [ J ]. Environ Health Perspeet, 2002, 110 (Suppl 6) :$989 - S994.
  • 5International Transporter Consortium,, Giacomini KM, Huang SM, et al. Membrane transporters in drug development [ J ]. Nat Rev Drug Discov, 2010, 9:215 -236.
  • 6Zhao Y, Hu ZY. Physiologically based pharmacokinetic modelling and in vivo [ I]/K(1) accurately predict P - glycoprotein - mediated drug - drug interactions with dabigatran etexilate [ J ]. Br J Phar- macol, 2014, 171:1043 - 1053.
  • 7Neuhoff S, Yeo KR, Barter Z, et al. Application of permeability - limited physiologically - based pharmacokinetic models : pan lI - prediction of P - glycoprotein mediated drug - drug interactions with digoxin [ J]. J Pharm Sci, 2013, 102:3161 - 3173.
  • 8Neuhoff S, Yeo KR, Barter Z, et al. Application of permeability - limited physiologically - based pharmacokinetic models : pan I - digoxin pharmacokinetics incorporating P - glycoprotein - mediated eftlux [J]. J Pharm Sci, 2013,102:3145-3160.
  • 9Varma MV, Lai Y, Feng B, et al. Physiologically based modeling of pravastatin transporter- mediated hepatobiliary disposition and drug - drug interactions [ J]. Pharm Res, 2012, 29:2860 - 2873.
  • 10Posada MM, Bacon JA, Schneck KB, et al. Prediction of renal transporter mediated drug - drug interactions for pemetrexed using physiologically based pharmacokinetic modeling [ J ]. Drug Metab Dispos, 2015, 43:325 - 334.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部