The extrapolation of metabolism data from in vitro experiments to in vivo clearances can provide useful information in the fields of pharmacokinetics and toxicokinetics. Depending on the purpose, different toxicokinetic models are used, and these different models require the in vivo metabolic information in different forms. In this study, a comprehensive toolbox for in vitro–in vivo extrapolation (IVIVE) of hepatic metabolism is presented addressing a variety of different extrapolation goals: extrapolation to hepatic blood clearance, extrapolation to organ clearance, extrapolation to whole-body clearance, and extrapolation to clearance at the level of hepatocytes. The use of the extrapolated clearances for calculation of extraction efficiencies and the use in physiologically based pharmacokinetic models are discussed. Furthermore, a sensitivity analysis demonstrates which parameters affect the accuracy of the extrapolation results the most, and the presented extrapolation procedure is evaluated by comparison to experimental data from perfused liver experiments.
For in vitro−in vivo extrapolation of biotransformation data, the different sorptive environments in vitro and in vivo need to be considered. The most common approach for doing so is using the ratio of unbound fractions in vitro and in vivo. In the literature, several algorithms for prediction of these unbound fractions are available. In this study, we present a theoretical evaluation of the most commonly used algorithms for prediction of unbound fractions in S9 assays and blood and compare prediction results with empirical values from the literature. The results of this analysis prove a good performance of "composition-based" algorithms, i.e. algorithms that represent the inhomogeneous composition of in vitro assay and in vivo system and describe sorption to the individual components (lipids, proteins, water) in the same way. For strongly sorbing chemicals, these algorithms yield constant values for the ratio of unbound fractions in vitro and in vivo. This is mechanistically plausible, because in these cases, the chemicals are mostly bound, and the ratio of unbound fractions is determined by the volume ratio of sorbing components in both phases. 8 f u,plasma : Saunders et al. 2020 8 2. Algorithms for Estimation of Fraction Unbound in S9 in Vitro Assays (f u,S9 ) 8 f u,S9 :
When present in blood, most chemicals tend to bind to the plasma protein albumin. For distribution into surrounding tissues, desorption from albumin is necessary, because only the unbound form of a chemical is assumed to be able to cross cell membranes. For metabolism of chemicals, the liver is a particularly important organ. One potentially limiting step for hepatic uptake of the chemicals is desorption from albumin, because blood passes the human liver within seconds. Desorption kinetics from albumin can thus be an important parameter for our pharmacokinetic and toxicokinetic understanding of chemicals. This work presents a dataset of measured desorption rate constants and reveals a possibility for their prediction. Additionally, the obtained extraction profiles directly indicate physiological relevance of desorption kinetics, because desorption of the test chemicals is still incomplete after time frames comparable to the residence time of blood in the liver.
Until now, the question whether slow desorption of compounds from transport proteins like the plasma protein albumin can affect hepatic uptake and thereby hepatic metabolism of these compounds has not yet been answered conclusively. This work now combines recently published experimental desorption rate constants with a liver model to address this question. For doing so, the used liver model differentiates the bound compound in blood, the unbound compound in blood and the compound within the hepatocytes as three well-stirred compartments. Our calculations show that slow desorption kinetics from albumin can indeed limit hepatic metabolism of a compound by decreasing hepatic extraction efficiency and hepatic clearance. The extent of this decrease, however, depends not only on the value of the desorption rate constant but also on how much of the compound is bound to albumin in blood and how fast intrinsic metabolism of the compound in the hepatocytes is. For strongly sorbing and sufficiently fast metabolized compounds, our calculations revealed a twentyfold lower hepatic extraction efficiency and hepatic clearance for the slowest known desorption rate constant compared to the case when instantaneous equilibrium between bound and unbound compound is assumed. The same desorption rate constant, however, has nearly no effect on hepatic extraction efficiency and hepatic clearance of weakly sorbing and slowly metabolized compounds. This work examines the relevance of desorption kinetics in various example scenarios and provides the general approach needed to quantify the effect of flow limitation, membrane permeability and desorption kinetics on hepatic metabolism at the same time.
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