Precisely adjusting the hepatic clearance of highly extracted drugs using the modified well-stirred model

How predictive are isolated perfused liver data of in vivo hepatic clearance? A meta-analysis of isolated perfused rat liver data

Isolated perfused rat liver (IPRL) experiments have been used to answer clearance-related questions, including evaluating the impact of pathological and physiological processes on hepatic clearance (CLH). However, to date, IPRL data has not been evaluated for in vivo CLH prediction accuracy.In addition to a detailed overview of available IPRL literature, we present an in-depth analysis of the performance of IPRL in CLH prediction.While the entire dataset poorly predicted CLH (GAFE = 3.2; 64% within 3-fold), IPRL conducted under optimal experimental conditions, such as in the presence of plasma proteins and with a perfusion rate within 2-fold of physiological liver blood flow and corrected for unbound fraction in the presence of red blood cells, can accurately predict rat CLH (GAFE = 2.0; 78% within 3-fold). Careful consideration of experimental conditions is needed to allow proper data analysis.Further, isolated perfused liver experiments in other species, including human livers, may allow us to address the current in vitro-in vivo disconnects of hepatic metabolic clearance and improve our methodology for CLH predictions.

First-in-Human Predictions of Hepatic Clearance for Drugs With the Well-Stirred Model: Comparative Assessment Between Models of Fraction Unbound Based Either on the Free Drug Hypothesis, Albumin-Facilitated Hepatic Uptake or Dynamic Binding Kinetics

The well-stirred model (WSM) is commonly used to predict the hepatic clearance in vivo (CLH) of drugs. The necessary intrinsic clearance of the unbound drug (CLint-in vitro-unbound) is generated in the in vitro assays in the presence of microsomes or hepatocytes but in the absence of plasma proteins. The value of CLint-in vitro-unbound can be extrapolated with the fraction unbound determined in vitro in plasma (fup) only if the fraction unbound in vivo in liver is the same. However, this approach resulted to a systematic underprediction bias of CLH. 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 CLH with the WSM. The first model was developed by Poulin et al. and is referring to the value of fup that is adjusted (fu-adjusted) 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-dynamic) 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-adjusted was the most accurate approach for predicting CLH. The WSM combined with the values of fu-dynamic 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-dynamic gave an underprediction bias of CLH for these drug properties. However, the values of fu-adjusted are significantly higher than those values of fu-dynamic, 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-dynamic and fu-adjusted are in closer agreement. Finally, for the basic drugs, the models of fu-adjusted and fu-dynamic as well as a third model only considering a pH gradient effect on fup are almost accurately equivalent.

Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio

The well-stirred model (WSM) incorporating the fraction of unbound drug (fu) to account for the effect of plasma binding on intrinsic clearance has been widely used for predicting hepatic clearance under the assumption that drug protein binding reaches equilibrium instantaneously. Our theoretical analysis reveals that the effect of protein binding on intrinsic clearance is better accounted for with the dynamic free fraction (fD), a measure of drug protein binding affinity, which leads to a putative dynamic well-stirred model (dWSM) without the instantaneous equilibrium assumption. Using recombinant CYP3A4 as the in vitro clearance system, we demonstrate that the binding effect of albumin on the intrinsic clearance of both highly bound midazolam and highly free verapamil is fully corrected by their corresponding fD values, respectively. On the other hand, fu only corrects the binding effect of albumin on the intrinsic clearance of verapamil, and yields severe over-correction of the intrinsic clearance of midazolam. The results suggest that the traditional WSM is suitable for highly free drugs like verapamil but not necessarily for highly bound drugs such as midazolam due to the violation of the instantaneous equilibrium assumption or under-estimating the true free drug concentration. In comparison, the dWSM incorporating fD holds true as long as drug elimination follows steady-state kinetics, and hence, it is more broadly applicable to drugs with different protein binding characteristics. Here we demonstrate with 36 diverse drugs, that the dWSM significantly improves the accuracy of predicting human hepatic clearance and liver extraction ratio from in vitro microsomal clearance data, highlighting the importance of drug plasma protein binding kinetics in addressing the under-prediction of hepatic clearance by the WSM.

Plasma Protein-Mediated Uptake and Contradictions to the Free Drug Hypothesis: A Critical Review

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

Evidence of the Need for Modified Well-stirred Model in In Vitro to In Vivo Extrapolation

In vitro to in vivo extrapolation (IVIVE), an approach for hepatic clearance (CL_H) prediction used worldwide, remains controversial due to systematic underprediction. Among the various probable factors, the original assumption of the hepatic mathematical model (i.e., the well-stirred model, WSM) may become problematic, leading to the underestimation of drug CL_H. Having a similar prerequisite that the well-stirred conditions are homogenous with perfectly mixed reactants, but using a different driving concentration, the modified well-stirred model (MWSM) stands apart from the WSM. However, we believe that both models should coexist so that the entire well-stirred scenario can be completely illustrated. Consequently, we collected published data from the literature and employed a logistic regression method to differentiate the optimal timing of use between WSM and MWSM in drug CL_H prediction. Generally, variances adopted in the regression, including partition coefficient (logP), fraction unbound (fu), volumes of distribution at steady-state (Vss), and mean residence time (MRT), corresponded to our assumption when protein-facilitated uptake was considered. Furthermore, a new empirical approach was introduced to allow practical use of the MWSM. The results showed that this model could provide a more precise prediction compared to previous empirical approaches. Therefore, these preliminary results not only delineated a more detailed structure and mechanism of MWSM but also highlighted its necessity and potential.