Johnson Trevor N, Rostami-Hodjegan Amin, Tucker Geoffrey T
Simcyp Limited, Sheffield, UK.
Clin Pharmacokinet. 2006;45(9):931-56. doi: 10.2165/00003088-200645090-00005.
Prediction of the exposure of neonates, infants and children to xenobiotics is likely to be more successful using physiologically based pharmacokinetic models than simplistic allometric scaling, particularly in younger children. However, such models require comprehensive information on the ontogeny of anatomical, physiological and biochemical variables; data that are not available from single sources. The Simcyp software integrates demographic, genetic, physiological and pathological information on adults with in vitro data on human drug metabolism and transport to predict population distributions of drug clearance (CL) and the extent of metabolic drug-drug interactions. The algorithms have now been extended to predict clearance and its variability in paediatric populations by incorporating information on developmental physiology and the ontogeny of specific cytochrome P450s.
Values of the clearance (median and variability) of 11 drugs (midazolam [oral and intravenous], caffeine, carbamazepine, cisapride, theophylline, diclofenac, omeprazole, S-warfarin, phenytoin, gentamicin and vancomycin) were predicted for 2,000 virtual subjects (birth to 18 years). In vitro enzyme pharmacokinetic parameters (maximum rate of metabolism [Vmax] and Michaelis-Menten constant [Km]) and in vivo clearance data were obtained from the literature.
In neonates 70% (7/10) of predicted median clearance values were within 2-fold of the observed values. Corresponding results for infants, children and adolescents were 100% (9/9), 89% (17/19) and 94% (17/18), respectively. Predicted variability (95% confidence interval) was within 2-fold of the observed values in 70% (7/10), 67% (6/9), 63% (12/19) and 55% (10/18) of cases, respectively. The accuracy of the physiologically based model incorporated in the Simcyp software was superior to that of simple allometry, especially in children <2 years old.
The in silico prediction of pharmacokinetic behaviour in paediatric patients is not intended to replace clinical studies. However, it provides a valuable aid to decision-making with regard to first-time dosing in children and study design. The clinical study then becomes 'confirmatory' rather than 'exploratory'.
相较于简单的异速生长比例缩放法，使用基于生理的药代动力学模型预测新生儿、婴儿及儿童对外源化学物质的暴露情况可能会更成功，尤其是对于年龄较小的儿童。然而，此类模型需要有关解剖学、生理学和生物化学变量个体发育的全面信息，而这些数据并非来自单一来源。Simcyp软件将成人的人口统计学、遗传学、生理学和病理学信息与人体药物代谢及转运的体外数据相结合，以预测药物清除率（CL）的群体分布及代谢性药物 - 药物相互作用的程度。现在，通过纳入发育生理学和特定细胞色素P450个体发育的信息，该算法已扩展到预测儿科人群的清除率及其变异性。
针对2000名虚拟受试者（从出生到18岁）预测了11种药物（咪达唑仑[口服和静脉注射]、咖啡因、卡马西平、西沙必利、茶碱、双氯芬酸、奥美拉唑、S - 华法林、苯妥英、庆大霉素和万古霉素）的清除率值（中位数和变异性）。体外酶药代动力学参数（最大代谢速率[Vmax]和米氏常数[Km]）及体内清除率数据均来自文献。
在新生儿中，70%（7/10）的预测清除率中位数在观察值的2倍范围内。婴儿、儿童和青少年的相应结果分别为100%（9/9）、89%（17/19）和94%（17/18）。预测变异性（95%置信区间）在70%（7/10）、67%（6/9）、63%（12/19）和55%（10/18）的病例中在观察值的2倍范围内。Simcyp软件中基于生理的模型的准确性优于简单的异速生长法，尤其是在2岁以下儿童中。
儿科患者药代动力学行为的计算机模拟预测并非旨在取代临床研究。然而，它为儿童首次给药和研究设计的决策提供了有价值的帮助。临床研究随后成为“验证性”而非“探索性”的。
