Albumin-Mediated Uptake Improves Human Clearance Prediction for Hepatic Uptake Transporter Substrates Aiding a Mechanistic In Vitro-In Vivo Extrapolation (IVIVE) Strategy in Discovery Research.

This study focused on exploring various in vitro to in vivo extrapolation (IVIVE) approaches with the primary goal of improving human hepatic clearance (CL) prediction for OATP substrates. To that effect, the impact of albumin-mediated uptake in human hepatocytes was investigated. In vitro hepatic uptake assay using suspended human hepatocytes was performed with 16 selected OATP substrates to determine the uptake CL in the absence and presence of 4% BSA and unbound hepatocyte to media partition coefficient (Kpuu). Substantial enhancement of the unbound uptake CL (PSu,inf) was observed in the presence of 4% BSA, demonstrating "albumin-mediated" uptake. Prediction of human hepatic CL was performed using two non-traditional IVIVE approaches: initial uptake CL (PSu,inf) and intrinsic metabolic CL (CLint,met) corrected by Kpuu based on extended clearance concept. Compared to traditional IVIVE using CLint,met only, the two tested IVIVE approaches significantly improved the prediction of human hepatic CL. Particularly, direct extrapolation from PSu,inf (+BSA) showed the most robust correlation with in vivo human hepatic CL for all 16 compounds with bias of 1.9-2.0 for two lots of human hepatocytes, respectively. In addition, PSu,inf (+BSA) and Kpuu were also determined in suspended cynomolgus monkey hepatocytes. Prediction of monkey hepatic CL was improved by both approaches, although with more bias compared to human. These results suggested supplementing 4% BSA in human hepatocyte uptake assay provides a useful tool to characterize hepatic uptake CL for OATP substrates, enabling more accurate human CL prediction without any empirical scaling factor (ESF).

Comparison of In Vitro to In Vivo Extrapolation Approaches for Predicting Transporter-Mediated Hepatic Uptake Clearance Using Suspended Rat Hepatocytes.

Clearance (CL) prediction remains a significant challenge in drug discovery, especially when complex processes such as drug transporters are involved. The present work explores various in vitro to in vivo extrapolation (IVIVE) approaches to predict hepatic CL driven by uptake transporters in rat. Broadly, two different IVIVE methods using suspended rat hepatocytes were compared: initial uptake CL (PSu,inf) and intrinsic metabolic CL (CLint,met) corrected by unbound hepatocytes to medium partition coefficient (Kpuu). Kpuu was determined by temperature method (Temp Kpuu,ss), homogenization method (Hom Kpuu,ss), and initial rate method (Kpuu,V0). In addition, the impact of bovine serum albumin (BSA) on each of these methods was investigated. Twelve compounds, which are known substrates of organic anion-transporting polypeptides representing diverse chemical matter, were selected for these studies. As expected, CLint,met alone significantly underestimated hepatic CL for all the test compounds. Overall, predicted hepatic CL using PSu,inf with BSA, Hom Kpuu,ss with BSA, and Temp Kpuu,ss showed the most robust correlation with in vivo rat hepatic CL. Adding BSA improved hepatic CL prediction for selected compounds when using the PSu,inf and Hom Kpuu,ss methods, with minimal impact on the Temp Kpuu,ss and Kpuu,V0 methods. None of the IVIVE approaches required an empirical scaling factor. These results suggest that supplementing rat hepatocyte suspension with BSA may be essential in drug discovery research for novel chemical matters to improve CL prediction. SIGNIFICANCE STATEMENT: The current investigation demonstrates that hepatocyte uptake assay supplemented with 4% bovine serum albumin is a valuable tool for estimating unbound hepatic uptake clearance (CL) and Kpuu. Based upon the extended clearance concept, direct extrapolation from these in vitro parameters significantly improved the overall hepatic CL prediction for organic anion-transporting polypeptide substrates in rat. This study provides a practical in vitro to in vivo extrapolation strategy for predicting transporter-mediated hepatic CL in early drug discovery.

Enhanced detection and characterization of glutathione-trapped reactive metabolites by pseudo-MS(3) transition using a linear ion trap mass spectrometer.

We present a simple and label-free approach to characterize glutathione (GSH)-trapped reactive metabolites from a single LC-MS analysis employing a linear ion trap mass spectrometer. The GSH specific fragment anion m/z 272 was first generated from the nonselective in-source fragmentation of intact conjugates. GSH conjugates were then detected by selected reaction monitoring (SRM) of the anion pair m/z 272 → 179 or 210. The resultant SRM peaks represented putative GSH conjugates which were then further characterized from their MS and MS(2) data acquired in both positive and negative ion modes. The method is demonstrated with test compounds that are all known to form GSH conjugates.

Simulation of clinical drug-drug interactions from hepatocyte CYP3A4 induction data and its potential utility in trial designs.

Rifampin and carbamazepine have been recommended in the U.S. Food and Drug Administration draft drug interaction guidance as CYP3A4 inducers for clinical drug-drug interaction (DDI) studies. To optimize the dose regimens of these inducers for use in DDI studies, their effect at various doses and dosing durations on the area under the curve (AUC) of multiple probe substrates was simulated using a population-based simulator. A similar assessment of the inducer phenobarbital was also conducted. CYP3A4 induction by all three inducers was previously determined in hepatocytes, and the results were incorporated into simulations. The pharmacokinetics of the three inducers and their associated CYP3A4 drug interactions were predicted and compared with in vivo observations. The predicted C(max) and AUC of all the inducers and substrates correlated closely with those observed clinically. The predicted magnitudes of the DDIs caused by CYP3A4 induction were also in good agreement with the observed clinical results. Comparison of the maximal CYP3A4 induction potential among the three inducers indicated that rifampin is the most potent inducer and is the best choice for clinical CYP3A4 induction DDI studies. Moreover, a near-maximal CYP3A4 DDI was predicted to result from administration of rifampin for approximately 7 days at 450 to 600 mg q.d. or 200 to 300 mg b.i.d. These results suggest optimal dose regimens for clinical trials that maximize the probability of detecting a DDI caused by CYP3A4 induction. The simulation strategy provides the means to predict the induction profiles of compounds in development.

In vitro metabolism of the novel, highly selective oral angiogenesis inhibitor motesanib diphosphate in preclinical species and in humans.

Motesanib diphosphate is a novel, investigational, highly selective oral inhibitor of the receptor tyrosine kinases vascular endothelial growth factor receptors 1, 2, and 3, the platelet-derived growth factor receptor, and the stem cell factor receptor (Kit). The in vitro metabolic profiles of [(14)C]motesanib were examined by using microsomes and hepatocytes from preclinical species and humans. Several oxidative metabolites were observed and characterized by tandem mass spectrometry, nuclear magnetic resonance spectroscopy, and coinjection with authentic standards. Cytochrome P450 (P450) 3A4 is the major isozyme involved in the oxidative biotransformation of motesanib, but the CYP2D6 and CYP1A isozymes also make minor contributions. In hepatocyte incubations, oxidative and conjugative pathways were observed for all species examined, and indoline N-glucuronidation was the dominant pathway. Three less common and novel phase II conjugates of the indoline nitrogen were detected in hepatocytes and in microsomes supplemented with specific cofactors, including N-carbamoyl glucuronide, N-glucose, and N-linked beta-N-acetylglucosamine. An N-glucuronide metabolite was the most frequently observed phase II conjugate in liver microsomes of all species, whereas the N-acetylglucosamine conjugate was observed only in monkey liver microsomes. Incubations with recombinant human UDP-glucuronosyltransferases (UGTs) and inhibition by the UGT1A4 and UGT1A1 substrates/inhibitors imipramine and bilirubin suggested that UGT1A4 is the major UGT isozyme catalyzing the N-glucuronidation of motesanib, with a minor contribution from UGT1A1. The in vitro metabolic profiles were similar between the human and preclinical species examined. All metabolites found in humans were also detected in other species.

Modeling, prediction, and in vitro in vivo correlation of CYP3A4 induction.

CYP3A4 induction is not generally considered to be a concern for safety; however, serious therapeutic failures can occur with drugs whose exposure is lower as a result of more rapid metabolic clearance due to induction. Despite the potential therapeutic consequences of induction, little progress has been made in quantitative predictions of CYP3A4 induction-mediated drug-drug interactions (DDIs) from in vitro data. In the present study, predictive models have been developed to facilitate extrapolation of CYP3A4 induction measured in vitro to human clinical DDIs. The following parameters were incorporated into the DDI predictions: 1) EC(50) and E(max) of CYP3A4 induction in primary hepatocytes; 2) fractions unbound of the inducers in human plasma (f(u, p)) and hepatocytes (f(u, hept)); 3) relevant clinical in vivo concentrations of the inducers ([Ind](max, ss)); and 4) fractions of the victim drugs cleared by CYP3A4 (f(m, CYP3A4)). The values for [Ind](max, ss) and f(m, CYP3A4) were obtained from clinical reports of CYP3A4 induction and inhibition, respectively. Exposure differences of the affected drugs in the presence and absence of the six individual inducers (bosentan, carbamazepine, dexamethasone, efavirenz, phenobarbital, and rifampicin) were predicted from the in vitro data and then correlated with those reported clinically (n = 103). The best correlation was observed (R(2) = 0.624 and 0.578 from two hepatocyte donors) when f(u, p) and f(u, hept) were included in the predictions. Factors that could cause over- or underpredictions (potential outliers) of the DDIs were also analyzed. Collectively, these predictive models could add value to the assessment of risks associated with CYP3A4 induction-based DDIs by enabling their determination in the early stages of drug development.