Watanabe K H, Bois F Y
Department of Mechanical Engineering, University of California at Berkeley, California 94720, USA.
Risk Anal. 1996 Dec;16(6):741-54. doi: 10.1111/j.1539-6924.1996.tb00825.x.
Three methods (multiplicative, additive, and allometric) were developed to extrapolate physiological model parameter distributions across species, specifically from rats to humans. In the multiplicative approach, the rat model parameters are multiplied by the ratio of the mean values between humans and rats. Additive scaling of the distributions is defined by adding the difference between the average human value and the average rat value to each rat value. Finally, allometric scaling relies on established extrapolation relationships using power functions of body weight. A physiologically-based pharmacokinetic model was fitted independently to rat and human benzene disposition data. Human model parameters obtained by extrapolation and by fitting were used to predict the total bone marrow exposure to benzene and the quantity of metabolites produced in bone marrow. We found that extrapolations poorly predict the human data relative to the human model. In addition, the prediction performance depends largely on the quantity of interest. The extrapolated models underpredict bone marrow exposure to benzene relative to the human model. Yet, predictions of the quantity of metabolite produced in bone marrow are closer to the human model predictions. These results indicate that the multiplicative and allometric techniques were able to extrapolate the model parameter distributions, but also that rats do not provide a good kinetic model of benzene disposition in humans.
开发了三种方法(乘法、加法和异速生长法)来推断跨物种的生理模型参数分布,特别是从大鼠到人类。在乘法方法中,将大鼠模型参数乘以人类与大鼠平均值之比。分布的加法缩放定义为将人类平均值与大鼠平均值之间的差值加到每个大鼠值上。最后,异速生长缩放依赖于使用体重幂函数建立的推断关系。基于生理的药代动力学模型分别拟合大鼠和人类的苯处置数据。通过推断和拟合获得的人类模型参数用于预测骨髓对苯的总暴露量以及骨髓中产生的代谢物量。我们发现,相对于人类模型,推断对人类数据的预测效果较差。此外,预测性能在很大程度上取决于所关注的量。相对于人类模型,推断模型低估了骨髓对苯的暴露量。然而,骨髓中产生的代谢物量的预测更接近人类模型的预测。这些结果表明,乘法和异速生长技术能够推断模型参数分布,但同时也表明大鼠不能很好地提供人类苯处置的动力学模型。