An Evaluation of the in Vitro Metabolism Data for Predicting the Clearance and Drug-Drug Interaction Potential of Cyp2c9 Substrates

136

114

Generating accurate in vitro intrinsic clearance data is an important aspect of predicting in vivo human clearance. Primary hepatocytes in suspension are routinely used to predict in vivo clearance; however, incubation times have typically been limited to 4-6 hours, which is not long enough to accurately evaluate the metabolic stability of slowly metabolized compounds. HepatoPac is a micropatterened hepatocyte-fibroblast coculture system that can be used for continuous incubations of up to 7 days. This study evaluated the ability of human HepatoPac to predict the in vivo clearance (CL) of 17 commercially available compounds with low to intermediate clearance (<12 ml/min per kg). In vitro half-life for disappearance of each compound was converted to hepatic clearance using the well stirred model, with and without correction for plasma protein binding. Hepatic CL, using three individual donors, was accurately predicted for 10 of 17 compounds (59%; predicted clearance within 2-fold of observed human in vivo clearance values). The accuracy of prediction increased to 76% (13 of 17 compounds) with an acceptance criterion defined as within 3-fold. When considering only low clearance compounds (<5 ml/ min per kg), which represented 10 of the 17 compounds, the accuracy of prediction was 60% within 2-fold and 90% within 3-fold. In addition, the turnover of three slowly metabolized compounds (alprazolam, meloxicam, and tolbutamide) in HepatoPac was directly compared with turnover in suspended hepatocytes. The turnover of alprazolam and tolbutamide was approximately 2-fold greater using HepatoPac compared with suspended hepatocytes, which was roughly in line with the extrapolated values (correcting for the longer incubation time and lower cell number with HepatoPac). HepatoPac, but not suspended hepatocytes, demonstrated significant turnover of meloxicam. These results demonstrate the utility of HepatoPac for prediction of in vivo hepatic clearance, particularly with low clearance compounds.

Section: Introductionmentioning

confidence: 99%

Meeting the Challenge of Predicting Hepatic Clearance of Compounds Slowly Metabolized by Cytochrome P450 Using a Novel Hepatocyte Model, HepatoPac

Chan

Moore³

et al. 2013

136

114

“…CL int, in vitro data derived from hepatocyte (Lave et al, 1997a,b;Lau et al, 2002;Shibata et al, 2002;Naritomi et al, 2003) or microsomal incubations (Carlile et al, 1999;Obach, 1999;Naritomi et al, 2001;Andersson et al, 2004) were generated in the authors' laboratory and collated from several published studies (Tables 1-3). Incubation conditions for data generated in the authors' laboratory have been detailed previously (Austin et al, 2002;McGinnity et al, 2004).…”

Section: Methodsmentioning

confidence: 99%

“…Incubation conditions for data generated in the authors' laboratory have been detailed previously (Austin et al, 2002;McGinnity et al, 2004). Data from microsomal studies reflected a variety of methods including formal Michaelis-Menten kinetic analysis [CL int ϭ V max /K m for specific metabolite(s) formation (Carlile et al, 1999;Andersson et al, 2004)] and substrate depletion at low substrate concentrations (Obach, 1999;Naritomi et al, 2001), which was used for all hepatocyte data. Datasets were compiled with several key objectives in mind: to expand existing databases substantially, to provide some assessment of interlaboratory variability, and to complement external datasets in terms of representation from different chemical classes covering a range of physicochemical properties.…”

Section: Methodsmentioning

confidence: 99%

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

Riley

McGinnity²,

Austin³

2005

334

289

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...

“…Throughout the present study, a wide range of (S)-(ϩ)-IBU and (R)-(Ϫ)-IBU concentrations was used (1-500 M). Such a range encompasses the clinically relevant free (ϳ1 M) and total (ϳ100 M) plasma concentrations of each enantiomer (Davies, 1998;Andersson et al, 2004;Takanohashi et al, 2007). Integration of the above in vitro data, with known human ADME information, may help rationalize reports describing IBU PK-P450 inhibitor combinations and IBU PK-P450 genotype associations (Kirchheiner et al, 2002;Garcia-Martin et al, 2004;Martinez et al, 2005;Hynninen et al, 2006;Bell et al, 2007;Tornio et al, 2007).…”

Section: Cyp2c8 Plays a Minor Role In (R)-(؊)-ibu (<10%) And (S)-(؉)-mentioning

confidence: 99%

Confirmation That Cytochrome P450 2C8 (CYP2C8) Plays a Minor Role in (S)-(+)- and (R)-(-)-Ibuprofen Hydroxylation in Vitro

Chang¹,

Li²,

Traeger³

et al. 2008

ABSTRACT:Various groups have sought to determine the impact of CYP2C8 genotype (and CYP2C8 inhibition) on the pharmacokinetics (PK) of ibuprofen (IBU) enantiomers. However, the contribution of cytochrome P450 2C8 (CYP2C8) in human liver microsomes (HLMs) has not been reported. Therefore, in vitro cytochrome P450 (P450) reaction phenotyping was conducted with selective inhibitors of cytochrome P450 2C9 (CYP2C9) and CYP2C8. In the presence of HLMs, sulfaphenazole (CYP2C9 inhibitor), and anti-CYP2C9 monoclonal antibodies (mAbs) inhibited (73-100%) the 2-and 3-hydroxylation of both IBU enantiomers (1 and 20 M). At a higher IBU concentration (500 M), the same inhibitors were less able to inhibit the 2-hydroxylation of There has been continued interest in the safety and ADME properties of cyclooxygenase inhibitors. This interest has extended to 2-(4-isobutylphenyl)propionic acid (ibuprofen, IBU), which is administered as a racemic mixture of (S)-(ϩ)-and (R)-(Ϫ)-enantiomers (Rodrigues, 2005;Agúndez et al., 2007;Pilotto et al., 2007;Blanco et al., 2008). The metabolism of both enantiomers is complex and involves direct (acyl) glucuronidation, 2-hydroxylation, and 3-hydroxylation (methyl hydroxylation) (Fig. 1). Once formed, the 3-hydroxy metabolite is converted almost completely to the corresponding carboxy derivative via cytosolic dehydrogenases (Rudy et al., 1991;Hamman et al., 1997;Davies, 1998). Only (R)-(Ϫ)-IBU undergoes (unidirectional) chiral inversion, which is significant because pharmacological activity after a racemic dose is attributed largely to the (S)-(ϩ)-enantiomer (Davies, 1998;Hao et al., 2005;Ding et al., 2007). Overall, it seems that P450-dependent metabolism accounts for approximately 70 and 30% of (S)-(ϩ)-IBU and (R)-(Ϫ)-IBU clearance, respectively (Rodrigues, 2005). At first glance, the pharmacokinetic profile of the latter is expected to be minimally affected by P450 inhibitors and genotype (e.g., CYP2C9*1/*3, CYP2C9*3/*3; CYP2C8*1/*3, CYP2C8*3/*3). (S)-(؉)-IBU (32-52%) and (R)-(؊)-IBU (30-64%), whereas the 3-hydroxylation of (S)-(؉)-IBU and (R)-(؊)-Currently available in vitro data show that CYP2C9 plays a major role (Ͼ70%) in the oxidative metabolism of racemic IBU and its individual enantiomers. However, hydroxylation of both enantiomers has also been measured with rCYP2C8 and other P450s (CYP3A4 and CYP2C19) (Leeman et al., 1993;Hamman et al., 1997;McGinnity et al., 2000). Such data have led various groups to conclude that both CYP2C forms catalyze the oxidative metabolism of IBU, and attempts have been made to evaluate the impact of both CYP2C9 and CYP2C8 genotype on the PK, pharmacodynamics, and side-effect profile of IBU enantiomers (Kirchheiner et al., 2002;Garcia-Martin et al., 2004; Martinez et al., 2005;Pilotto et al., 2007;Blanco et al., 2008). Clinical drug interaction studies with known inhibitors of CYP2C9 (e.g., fluconazole) and CYP2C8 (e.g., gemfibrozil) have been conducted also (Hynninen et al., 2006;Tornio et al., 2007).However, it is worth noting that CYP2C8-selective chemica...