索引于
  • 学术期刊数据库
  • 打开 J 门
  • Genamics 期刊搜索
  • 学术钥匙
  • 期刊目录
  • 中国知网(CNKI)
  • 引用因子
  • 西马戈
  • 乌尔里希的期刊目录
  • 电子期刊图书馆
  • 参考搜索
  • 哈姆达大学
  • 亚利桑那州EBSCO
  • OCLC-WorldCat
  • SWB 在线目录
  • 虚拟生物学图书馆 (vifabio)
  • 普布隆斯
  • 米亚尔
  • 大学教育资助委员会
  • 日内瓦医学教育与研究基金会
  • 欧洲酒吧
  • 谷歌学术
分享此页面
期刊传单
Flyer image

抽象的

Model-Based Elaboration of a Limited Sampling Strategy in the Bioequivalence Assessment of Highly Variable Dabigatran

Cassandre Legault and Jun Li*

Background: The bioequivalence (BE) assessment of generic (Test) and brand name (Reference) formulations of drugs with steep exposure-response relationships exhibiting high pharmacokinetic (PK) variability such as dabigatran represent an expensive challenge for pharmaceutical companies. Supported by the population pharmacokinetics (pop-PK) approach, the present article investigates modelling potential to assess BE using a reduced number of blood samples.

Methods: Pop-PK models for the Reference and Test formulations were developed retrospectively using standard modeling techniques for a BE study of dabigatran. Reduced sampling scenarios were selected and the developed pop- PK models were refitted on each dataset for the respective formulations. These models were simulated to generate virtual PK profiles to be tested with the standard BE criteria, in order to identify the scenarios maintaining the original BE conclusions with the least samples required.

Results: The BE study original data was best described as a pop-PK model presenting two compartments with first order elimination and absorption, as well as an absorption lag time. Sex was identified as a significant covariate with impact on bioavailability. Using a rational sampling selection procedure under the framework of modeling and simulation, the results proved that the BE verdict could be maintained with only five of the 20 original blood samples using the current regulatory BE standards and criteria.

Conclusion: We conclude that the pop-PK model-based BE assessment can be an efficient tool for aiding the BE assessment of dabigatran by significantly reducing the number of samples required, and consequently lower trial costs and increase benefits for enrolled participants.