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Prediction of human clearance of therapeutic proteins: simple allometric scaling method revisited

机译:预测人类对治疗性蛋白质的清除率:重新探讨了简单的异度缩放法

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摘要

In this report, the utility of a commonly used interspecies scaling method to predict the systemic clearance (CL) of therapeutic proteins in humans was evaluated. Based on analysis of a pharmacokinetic data set of 34 therapeutic proteins, including 12 monoclonal antibodies (mAbs) and Fc fusion proteins, human CL can generally be predicted reasonably well with simple allometric scaling and a fixed exponent of 0.8:∼95% of the cases predicted values within 2-fold of the observed values when using CL data from multiple species, or∼90% simply using CL from monkeys. Specific to mAbs/Fc fusion proteins, scaling from monkey CL using a fixed exponent of 0.8 gave an excellent prediction; all predicted CL values were within 2-fold of the corresponding observed values. Compared with the simple allometric scaling method that uses a fitted exponent from CL data of ≥3 preclinical species, the fixed exponent approach with 1–2 preclinical species is simple, resource-saving and minimizes systematic bias. Together with its overall satisfactory prediction accuracy, especially in the absence of non-linear pharmacokinetics and species-specific clearance mechanisms, this fixed exponent method affords a viable alternative to other published allometric methods, including the Rule of Exponents (ROE). Copyright © 2010 John Wiley & Sons, Ltd.
机译:在此报告中,评估了常用的种间缩放方法预测人类治疗性蛋白质的系统清除率(CL)的实用性。基于对34种治疗性蛋白质(包括12种单克隆抗体(mAbs)和Fc融合蛋白)的药代动力学数据集的分析,通常可以通过简单的异速缩放和固定指数为0.8:〜95%的病例合理地预测人类CL当使用多个物种的CL数据时,预测值在观测值的2倍以内,或者仅使用猴子的CL时,预测值约为90%。对mAbs / Fc融合蛋白具有特异性,使用固定的0.8指数从猴子CL缩放可得出很好的预测;所有预测的CL值均在相应观察值的2倍以内。与使用≥3个临床前物种的CL数据使用拟合指数的简单异体缩放方法相比,使用1-2种临床前物种的固定指数方法更为简单,节省资源并最大程度地减少了系统偏差。加上其总体令人满意的预测准确性,尤其是在没有非线性药代动力学和物种特异性清除机制的情况下,这种固定指数方法可为包括指数规则(ROE)在内的其他已发表的异速测量方法提供可行的替代方法。版权所有©2010 John Wiley&Sons,Ltd.

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