The mechanisms of pharmacokinetic food-drug interactions - A perspective from the UNGAP group.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences(2019)

引用 209|浏览31
暂无评分
摘要
The simultaneous intake of food and drugs can have a strong impact on drug release, absorption, distribution, metabolism and/or elimination and consequently, on the efficacy and safety of pharmacotherapy. As such, food-drug interactions are one of the main challenges in oral drug administration. Whereas pharmacokinetic (PK) food-drug interactions can have a variety of causes, pharmacodynamic (PD) food-drug interactions occur due to specific pharmacological interactions between a drug and particular drinks or food. In recent years, extensive efforts were made to elucidate the mechanisms that drive pharmacokinetic food-drug interactions. Their occurrence depends mainly on the properties of the drug substance, the formulation and a multitude of physiological factors. Every intake of food or drink changes the physiological conditions in the human gastrointestinal tract. Therefore, a precise understanding of how different foods and drinks affect the processes of drug absorption, distribution, metabolism and/or elimination as well as formulation performance is important in order to be able to predict and avoid such interactions. Furthermore, it must be considered that beverages such as milk, grapefruit juice and alcohol can also lead to specific food-drug interactions. In this regard, the growing use of food supplements and functional food requires urgent attention in oral pharmacotherapy. Recently, a new consortium in Understanding Gastrointestinal Absorption-related Processes (UNGAP) was established through COST, a funding organisation of the European Union supporting translational research across Europe. In this review of the UNGAP Working group "Food-Drug Interface", the different mechanisms that can lead to pharmacokinetic food-drug interactions are discussed and summarised from different expert perspectives.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要