Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA; email:
Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, USA.
Annu Rev Anal Chem (Palo Alto Calif). 2018 Jun 12;11(1):79-100. doi: 10.1146/annurev-anchem-061417-125611. Epub 2018 Jan 11.
The creation of a pharmacokinetic (PK) curve, which follows the plasma concentration of an administered drug as a function of time, is a critical aspect of the drug development process and includes such information as the drug's bioavailability, clearance, and elimination half-life. Prior to a drug of interest gaining clearance for use in human clinical trials, research is performed during the preclinical stages to establish drug safety and dosing metrics from data obtained from the PK studies. Both in vivo animal models and in vitro platforms have limitations in predicting human reaction to a drug due to differences in species and associated simplifications, respectively. As a result, in silico experiments using computer simulation have been implemented to accurately predict PK parameters in human studies. This review assesses these three approaches (in vitro, in vivo, and in silico) when establishing PK parameters and evaluates the potential for in silico studies to be the future gold standard of PK preclinical studies.
建立药代动力学（PK）曲线是药物开发过程中的一个关键方面，该曲线可反映给药后药物在血浆中的浓度随时间的变化。PK 曲线提供了药物的生物利用度、清除率和消除半衰期等信息。在有前景的药物获得用于人体临床试验的许可之前，会在临床前阶段进行研究，从 PK 研究中获得的数据来确定药物的安全性和给药剂量指标。由于物种差异以及相关的简化，体内动物模型和体外平台在预测人体对药物的反应方面都存在局限性。因此，已采用计算机模拟的计算实验来准确预测人体研究中的 PK 参数。本综述评估了在建立 PK 参数时这三种方法（体外、体内和计算），并评估了计算研究成为 PK 临床前研究未来金标准的潜力。
