Background
The application of modeling and simulation approaches in clinical pharmacology studies has gained momentum over the last 20 years.

Objectives
The objective of this study was to develop six empirical models from clearance data obtained from children aged > 2 years and adults to evaluate the suitability of the models to predict drug clearance in children aged ≤ 2 years (preterm, term, and infants).

Methods
Ten drugs were included in this study and administered intravenously: alfentanil, amikacin, busulfan, cefetamet, meperidine, oxycodone, propofol, sufentanil, theophylline, and tobramycin. These drugs were selected according to the availability of individual subjects’ weight, age, and clearance data (concentration–time data for these drugs were not available to the author). The chosen drugs are eliminated by extensive metabolism by either the renal route or both the renal and hepatic routes. The six empirical models were (1) age and body weight-dependent sigmoidal maximum possible effect ( E _max) maturation model, (2) body weight-dependent sigmoidal E _max model, (3) uridine 5′-diphospho [body weight-dependent allometric exponent model (BDE)], (4) age-dependent allometric exponent model (ADE), (5) a semi-physiological model, and (6) an allometric model developed from children aged > 2 years to adults. The model-predicted clearance values were compared with observed clearance values in an individual child. In this analysis, a prediction error of ≤ 50% for mean or individual clearance values was considered acceptable.

Results
Across all age groups and the ten drugs, data for 282 children were compared between observed and model-predicted clearance values. The validation data consisted of 33 observations (sum of different age groups for ten drugs). Only three of the six models (body weight-dependent sigmoidal E _max model, ADE, and semi-physiological model) provided reasonably accurate predictions of clearance (> 80% observation with ≤ 50% prediction error) in children aged ≤ 2 years. In most instances, individual predicted clearance values were erratic (as indicated by % error) and were not in agreement with the observed clearance values.

Conclusions
The study indicated that simple empirical models can provide more accurate results than complex empirical models.



中文翻译：

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使用来自儿童（> 2岁）和成人的数据从经验模型推断≤2岁儿童的药物清除率

背景
技术在过去的20年中，建模和仿真方法在临床药理学研究中的应用获得了强劲的发展。

目的
本研究的目的是从大于2岁的儿童和成人获得的清除率数据中开发六个经验模型，以评估该模型预测2岁以下儿童（早产，足月和婴儿）药物清除率的适用性。

方法
这项研究包括十种药物并通过静脉给药：阿芬太尼，丁胺卡那霉素，白消安，头孢他美，哌替啶，羟考酮，丙泊酚，舒芬太尼，茶碱和妥布霉素。根据各个受试者的体重，年龄和清除率数据的可用性选择这些药物（作者无法获得这些药物的浓度-时间数据）。所选药物通过肾脏途径或肾脏和肝脏途径的大量代谢而消除。六个经验模型是（1）年龄和体重相关的乙状结肠最大可能效应（ E _max）成熟模型，（2）体重相关的乙状结肠 E _max模型，（3）尿苷5'-二磷酸[体重依赖的异体指数模型（BDE）]，（4）年龄依赖的异体指数模型（ADE），（5）半生理模型，以及（6）从大于2岁的儿童到成人的全能模型。将模型预测的间隙值与单个孩子中观察到的间隙值进行比较。在此分析中，对于平均间隙值或单个间隙值，≤50％的预测误差被认为是可以接受的。

结果
在所有年龄段和10种药物中，比较了282例儿童的观察值和模型预测的清除率数据。验证数据包括33个观察值（十个药物不同年龄组的总和）。六个模型中只有三个模型（与体重有关的S形 E _max模型，ADE和半生理模型）为2岁以下的儿童提供了合理准确的清除率预测（观察值> 80％，预测误差≤50％）。在大多数情况下，单个的预测间隙值是不稳定的（如％误差所示），并且与观察到的间隙值不一致。

结论
研究表明，简单的经验模型可以提供比复杂的经验模型更准确的结果。