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

Abstract

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 hepatocytefibroblast 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/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 11 of 17 compounds (59%; predicted clearance within 2-fold of observed human in vivo clearance values). The accuracy of prediction increased to 82% (14 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 70% within 2-fold and 100% 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.

Prediction of human pharmacokinetics for low‐clearance compounds using pharmacokinetic data from chimeric mice with humanized livers

“…In suspended hepatocyte assays, low‐CL int compounds frequently display no significant turnover within the incubation period in which enzymatic activity can be maintained. Therefore, an in vitro metabolic stability assay to detect slow turnover for a longer period, such as the Hepatopac, 13 HμREL, 2 and relay methods, 14 have been developed, whereas in vivo prediction methods specific for low‐CL int compounds have not been developed.…”

“…A total of 16 commercially available compounds were selected, including those expected to have low CL int based on clinical data (<5 ml/min/kg 13 ) and those metabolized by cytochrome P450 (CYP) and non‐CYP enzymes. Because most of these compounds were metabolized in the liver, this study assumed that total CL (CL t ) is equal to hepatic CL.…”

Latest impact of engineered human liver platforms on drug development

“… 54 For instance, Boehringer Ingelheim showed that long-term incubations on MPCCs could be used to predict the clearance of ten low clearance compounds within an acceptable threshold of threefold of reported clinical values, and that compound turnover was twofold higher in MPCCs than in suspension PHHs. 38 In a follow-up study, we showed that MPCCs predicted the clearance of 92% of 26 drugs within threefold of their clinical clearance values [ Fig. 2(d) ], whereas conventional 2D PHH monocultures and PHH suspensions were only 20% predictive and could not metabolize several drugs.…”

“…Furthermore, 3T3-J2 fibroblasts have advantages for use as a PHH-supporting stromal cell since the fibroblasts are expandable, contact-inhibited, and lack liver- and human-specific functions and gene expression, such as CYP enzymes. 7 The MPCC platform and its variants have been rigorously validated for several applications within drug development, such as prediction of drug clearance, 38,39 drug metabolite identification across different species, 40,41 drug–drug interactions (DDIs), 39,42 DILI prediction, 6,43,44 infection with hepatitis B/C viruses (HBV/HCV), 45,46 malaria infection, 47 and early stages of nonalcoholic fatty liver disease (NAFLD). 36,48,49 We provide representative examples below from pharmaceutical practice where available.…”

PBPK Modeling as a Tool for Predicting and Understanding Intestinal Metabolism of Uridine 5′-Diphospho-glucuronosyltransferase Substrates

“…Therefore, coculture models, such as Hµrel ® and HepatoPac ® , including primary human hepatocytes cocultured with supporting cell types to allow longer-term incubations with consistent metabolic activity and hepatocyte viability throughout incubation, have been established. Evaluation of these coculture models have focused initially on compounds metabolized primarily via CYP enzymes [45,52,53], but promising quantitative prediction performance has also been demonstrated with compounds metabolized primarily by UGTs [16].…”