A Unified Model for Predicting Human Hepatic, Metabolic Clearance From in Vitro Intrinsic Clearance Data in Hepatocytes and Microsomes

Abstract

ABSTRACT:The aim of this study was to evaluate a unified method for predicting human in vivo intrinsic clearance (CL int, in vivo ) and hepatic clearance (CL h ) from in vitro data in hepatocytes and microsomes by applying the unbound fraction in blood (fu b ) and in vitro incubations (fu inc ). Human CL int, in vivo was projected using in vitro data together with biological scaling factors and compared with the unbound intrinsic clearance (CL int, ub, in vivo ) estimated from clinical data using liver models with and without the various fu terms. For incubations conducted with fetal calf serum (n ‫؍‬ 14), the observed CL int, in vivo was modeled well assuming fu inc and fu b were equivalent. CL int, ub, in vivo was predicted best using both fu b Existing methods for the prediction of drug clearance in humans involve the use of in vitro human metabolic stability (intrinsic clearance, CL int ) data (Iwatsubo et al., 1997), consideration of preclinical animal data (Boxenbaum, 1982), or a combination of these approaches (Lave et al., 1997a;Naritomi et al., 2001). In vitro drug metabolism kinetic parameters can provide an estimate of in vivo CL int via "scaling" with established biological scaling factors (SFs) e.g., hepatocellularity for isolated hepatocytes, or a SF for microsomes based on incomplete microsomal recovery from human liver tissue using the cytochrome P450 (P450) content in homogenate and microsomes (Houston, 1984). CL int may subsequently be used to provide an estimate of hepatic clearance (CL h ) using several liver models (Houston, 1984;Ito and Houston, 2004).To date, the more extensive analyses of human clearance predictions have concentrated on P450 substrates, and data have therefore been generated in human liver microsomes (Iwatsubo et al., 1997;Obach, 1999;Naritomi et al., 2001). In general, these studies have been less comprehensive in the range of approaches investigated, with only occasional attention given to chemical class (Obach et al., 1997). Interestingly, these reports have also assessed the ability to predict human CL h rather than the more fundamental parameter, CL int , as advocated initially (Houston, 1984;Ito and Houston, 2004). Some controversy also still exists over use of fu inc , with some laboratories having suggested that fu inc and fu b may cancel, negating their inclusion in liver models (Obach et al., 1997). Recent reports have challenged this assumption (Obach, 1999;Austin et al., 2002) and perhaps suggest that consideration of CL h rather than CL int, in vivo may desensitize such analyses, particularly to errors associated with higher enzyme activities (Ito and Houston, 2004).The aim of this study was to investigate direct in vitro-in vivo scaling of human in vitro data generated in hepatocytes and microsomes for predicting human clearance in vivo by applying recently described models for estimating fu inc (Austin et al., 2002(Austin et al., , 2005. To provide a more mechanistic insight, in vitro human CL int data were compiled from recent in-house and published stud...

Clearance Prediction of HIV Protease Inhibitors in Man: Role of Hepatic Uptake

“…Previous research has shown that the in vivo hepatic Cl can accurately be estimated from in vitro data in both microsomes and hepatocytes. 36 Nevertheless, hepatic uptake transporters have been shown to modulate Cl of compounds that is predominantly mediated by metabolic enzymes when measured in hepatocyte systems. 31 Therefore, the metabolic intrinsic Cl of HIV PI was measured in pooled liver microsomes (Table 6).…”

Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies

“…Additional input information for the well-stirred model such as f up , the B:P ratio and f umic were determined experimentally. If these were not available, the B:P ratio was assumed to be 1 (for compounds that are either neutral or basic, 0.55 may be assumed for acids [10]) and f umic and f up were calculated in Simcyp W [26]. The successful performance of IVIVE in preclinical species was used as a means to add confidence to human IVIVE.…”

“…An important aspect of PBPK modeling for compounds cleared primarily by the liver is the application of IVIVE methods to predict in vivo clearance from in vitro metabolic data. The utility of IVIVE for hepatic metabolic clearance has been well established in the literature [8][9][10] and is developing to improve poor predictions by incorporating hepatic uptake and/or biliary excretion [11,12]. Briefly, the in vitro intrinsic clearance (CL int ) or enzyme kinetic data (K m and V max ) are scaled to an in vivo CL int by accounting for the microsomal protein content or hepatocellularity and liver weight.…”

Prediction of Oral Pharmacokinetics of cMet Kinase Inhibitors in Humans: Physiologically Based Pharmacokinetic Model Versus Traditional One-Compartment Model

“…The use of these scaling factors resulted in 15 to 30% lower CL hep values of PF02341066 and PF04217903. For consistency with previous reports (Obach et al, 1997;Obach 1999;Naritomi et al, 2003;Riley et al, 2005;Hosea et al, 2009), the scaling factors indicated above were used for this study.…”

“…Although allometric scaling is an empirical approach, it has been widely used and provided reliable predictions for a number of highly metabolized and renally excreted drugs (Boxenbaum, 1984;Mordenti, 1986;Mahmood and Balian, 1996). Over the last two decades, the methods for extrapolating in vivo CL from in vitro data (i.e., IVIVE) have been applied extensively with the increased availability of human liver samples (e.g., microsomes, hepatocytes, liver slices, and others) and have demonstrated prediction accuracy for metabolic CL of low to high hepatic extraction compounds (Houston and Carlile, 1997;Obach et al, 1997;Obach, 1999;Riley et al, 2005;Shiran et al, 2006). In recent years, there has been growing interest in the physiologically based pharmacokinetic (PBPK) model, which provides the disposition profiles in various species to be predicted from physicobiochemical properties of compounds with the species-specific physiological parameters (Jones et al, 2006;De Buck et al, 2007;Lavé et al, 2007;Nestorov, 2007).…”