Consultant Patrick Poulin Inc., Québec City, Québec, Canada; School of Public Health, Université de Montréal, Montréal, Québec, Canada.
J Pharm Sci. 2024 Aug;113(8):2641-2650. doi: 10.1016/j.xphs.2024.05.021. Epub 2024 May 24.
The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CL) of drugs. The necessary intrinsic clearance of the unbound drug (CL) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CL can be extrapolated with the fraction unbound determined in vitro in plasma (fu) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CL. With the goal of reducing this bias, two new models of fraction unbound were published in this journal. These models estimate the binding kinetics of the rates of association and dissociation of the drug-protein complex and propose that more dissociation in the liver compared to plasma will increase the fraction unbound available for the metabolism. Consequently, these two models generated higher values of fraction unbound, implying a lower underprediction bias of CL with the WSM. The first model was developed by Poulin et al. and is referring to the value of fu that is adjusted (fu) to quantify the effect of a full dissociation of the drug-protein complex at the hepatocyte membrane in accordance with the theory of the albumin-facilitated hepatic uptake. A second model was developed by Yan et al. who presented a dynamic fraction unbound (fu) measuring the real dissociation kinetics of the drug-protein complex with a new in vitro assay in the presence and absence of a recombinant liver enzyme in plasma. Therefore, the objective of this study was to make the first comparative assessment between these two models. The results indicate that, in general, the WSM combined with the values of fu was the most accurate approach for predicting CL. The WSM combined with the values of fu has underperformed particularly with the acidic and neutral drugs binding to the albumin and presenting a low metabolic turnover in vitro. Therefore, the new in vitro assay for fu gave an underprediction bias of CL for these drug properties. However, the values of fu are significantly higher than those values of fu, and, this resulted to no underprediction bias, which is reinforcing the theory of the ALB-facilitated hepatic uptake. For the other neutral and acidic drugs, the models of fu and fu are in closer agreement. Finally, for the basic drugs, the models of fu and fu as well as a third model only considering a pH gradient effect on fu are almost accurately equivalent.
搅拌池模型（WSM）常用于预测药物在体内的肝清除率（CL）。在存在微粒体或肝细胞的情况下，通过体外试验生成未结合药物（CL）的必要内在清除率，但不存在血浆蛋白。只有当体内肝中未结合分数与体外试验中测定的未结合分数（fu）相同时，才能用体外试验中测定的 fu 来推断 CL 值。然而，这种方法导致 CL 的系统低估偏差。为了减少这种偏差，本杂志发表了两种新的未结合分数模型。这些模型估计药物-蛋白复合物的结合动力学，包括药物-蛋白复合物的结合和解离速率，并提出与血浆相比，肝脏中更多的解离将增加可供代谢的游离分数。因此，这两种模型生成的未结合分数值较高，这意味着 WSM 对 CL 的低估偏差较低。第一个模型由 Poulin 等人开发，指的是经调整的 fu 值（fu），用于根据白蛋白促进肝摄取理论，定量量化药物-蛋白复合物在肝细胞膜上完全解离的影响。第二个模型由 Yan 等人开发，他们提出了一种动态未结合分数（fu），用于测量在存在和不存在血浆中重组肝酶的情况下，药物-蛋白复合物的真实解离动力学，这是一种新的体外试验。因此，本研究的目的是对这两种模型进行首次比较评估。结果表明，一般来说，WSM 与 fu 值相结合是预测 CL 的最准确方法。WSM 与 fu 值相结合的方法在预测酸性和中性药物的 CL 时尤其表现不佳，这些药物与白蛋白结合，并且在体外代谢周转率较低。因此，新的体外 fu 试验对这些药物特性的 CL 产生了低估偏差。然而，fu 值明显高于 fu 值，这导致没有低估偏差，这加强了白蛋白促进肝摄取的理论。对于其他中性和酸性药物，fu 和 fu 的模型更为一致。最后，对于碱性药物，fu 和 fu 的模型以及仅考虑 fu 对 pH 梯度影响的第三个模型几乎是等效的。
