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Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions

机译:使用体外渗透率测量和计算机模拟渗透率预测代谢程度

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摘要

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72±9%, 49±10%, and 66±7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74±7%, 85±2%, and 73±8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly, respectively when the permeability rate is determined in vitro.
机译:可根据药物的代谢程度和溶解度,利用生物制药药物处置分类系统(BDDCS)来预测药物处置,包括与其他药物和转运蛋白或代谢酶的相互作用。但是,确定代谢程度取决于临床数据。表现出高被动肠通透率的药物被广泛代谢。因此,我们旨在确定通透率的体外测量或计算机模拟通透率预测是否可以预测新陈代谢的程度,确定代表通透率的参考化合物,超过该参考值,该化合物将被广泛代谢,并预测利用渗透率和先前发布的模型预测消除母体药物的主要途径的两层方法中消除化合物的主要途径。从文献中收集了Caco-2和MDCK细胞系和PAMPA中的22个体外通透率测量数据集,而使用ADMET Predictor 或VolSurf +计算了计算机通透率预测。利用接收器工作特性曲线分析了渗透率在广泛代谢和代谢较差的化合物之间进行区分的可能性。选择产生最高灵敏度-特异性平均值的化合物作为渗透率参考标准。消除渗透性差的药物的主要途径是由我们先前发布的模型预测的,并计算了准确性和预测值。对于体外测得的渗透率,接收器工作曲线下的面积> 0.90,对于渗透率的VolSurf +模型,> 0.80,表明它们能够预测化合物的代谢程度。 Labetalol和齐多夫定分别在Caco-2和MDCK中正确预测了80%以上的广泛代谢药物和80%以上的不良代谢药物,而茶碱在PAMPA中预测了80%以上的代谢广泛且代谢不良的药物。当通过计算机模拟预测通透率时,采用两层方法预测消除途径可正确预测广泛代谢,胆道消除和肾消除的母体药物的72±9%,49±10%和66±7%体外测定通透率时,分别正确,广泛地代谢,胆道清除和肾清除的母体药物中,分别有85±2%和73±8%。

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