Poggesi Italo
Pharmacia Italia SpA, Pfizer group Inc., Prediction and Modeling Pharmacokinetics, Dynamics and Metabolism Via Pasteur 10, 20014 Nerviano (MI), Italy.
Curr Opin Drug Discov Devel. 2004 Jan;7(1):100-11.
Approaches used for the prediction of pharmacokinetics in relevant populations of human patients mostly rely on in vivo data from animals, using allometric scaling or time-invariant methods. The growth of in vitro and, more recently, in silico screens for evaluating pharmaceutical, pharmacokinetic and toxicity properties can also be used to predict complex in vivo behavior in humans. In most cases, careful and educated application of available approaches provides predictions of pharmacokinetic parameters within 2- or 3-fold of that observed. Attention should now be directed toward integrating information from different sources to increase the precision and accuracy of these pharmacokinetic predictions and to enable a better understanding of the processes underlying ADME behavior in humans.
用于预测人类患者相关群体药代动力学的方法大多依赖于动物体内数据，采用异速生长比例法或时不变方法。用于评估药物、药代动力学和毒性特性的体外筛选，以及最近的计算机模拟筛选的发展，也可用于预测人类复杂的体内行为。在大多数情况下，谨慎且合理应用现有方法可使药代动力学参数的预测值与观测值相差在2至3倍以内。现在应将注意力转向整合来自不同来源的信息，以提高这些药代动力学预测的精度和准确性，并更好地理解人类体内药物吸收、分布、代谢和排泄（ADME）行为背后的过程。
