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Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications.

Lei SunKun MiYixuan HouTianyi HuiLan ZhangYanfei TaoZhenli LiuLingli Huang
Published in: Metabolites (2023)
Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.
Keyphrases
  • machine learning
  • drug induced
  • liver injury
  • emergency department
  • mass spectrometry
  • quantum dots
  • deep learning
  • atomic force microscopy
  • fluorescent probe