Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model.

Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of comedicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A, leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and human liver microsomes (HLM) to predict clinically relevant drug-drug interactions was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate, and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were preincubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition was detected in HLM for four moderate/strong inhibitors, suggesting that some optimization of incubation conditions (i.e., lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters maximal rate of enzyme inactivation (min-1) (kinact) and concentration of inhibitor resulting in 50% of the maximum enzyme inactivation (KI) into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models, which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within twofold of the observed value. SIGNIFICANCE STATEMENT: Coupling time-dependent inactivation parameters derived from pooled human hepatocytes and human liver microsomes (HLM) with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical drug-drug interaction risk from in vitro data. Optimization is needed to evaluate time-dependent inhibition (TDI) for weak and moderate inhibitors using HLM. Recommendations are made with respect to input parameters for in vitro to in vivo extrapolation (IVIVE) of TDI with non-CYP3A enzymes using available data from HLM and human hepatocytes.

Biopharmaceutics permeability classification of lorcaserin, a selective 5-hydroxytryptamine 2C agonist: method suitability and permeability class membership.

The objectives of the study were (1) to demonstrate that a Caco-2 cell-based permeability assay, developed in our laboratory, is suitable to identify the permeability classification according to the US Food and Drug Administration Biopharmaceutics Classification System guidance, and (2) to use the validated Caco-2 method to determine permeability class membership of lorcaserin. Lorcaserin, marketed in United States as Belviq, is a selective human 5-hydroxytryptamine 2C agonist used for weight management. First, the permeability of twenty commercially available drugs was determined in the apical-to-basolateral direction at a final concentration of 10 µM, with the pH of transporter buffer in the apical and basolateral compartments being 6.8 and 7.4, respectively. A rank-order relationship between in vitro permeability results and the extent of human intestinal absorption for the drugs tested was observed. Second, the apparent permeability coefficient values of lorcaserin at 2, 20, and 200 µM and apical pH values of 6.8 and 7.4 in the apical-to-basolateral direction were determined using the validated method and found to be comparable to those of the high-permeability internal standard metoprolol. Lorcaserin permeability across Caco-2 cell monolayers was not dependent on the variation of apical pH. Furthermore, lorcaserin was not a substrate for efflux transporters such as P-glycoprotein. In conclusion, using the validated Caco-2 permeability assay, it was shown that lorcaserin is a highly permeable compound.

Time-dependent inhibition and estimation of CYP3A clinical pharmacokinetic drug-drug interactions using plated human cell systems.

The current studies assessed the utility of freshly plated hepatocytes, cryopreserved plated hepatocytes, and cryopreserved plated HepaRG cells for the estimation of inactivation parameters k(inact) and K(I) for CYP3A. This was achieved using a subset of CYP3A time-dependent inhibitors (fluoxetine, verapamil, clarithromycin, troleandomycin, and mibefradil) representing a range of potencies. The estimated k(inact) and K(I) values for each time-dependent inhibitor were compared with those obtained using human liver microsomes and used to estimate the magnitude of clinical pharmacokinetic drug-drug interaction (DDI). The inactivation kinetic parameter, k(inact), was most consistent across systems tested for clarithromycin, verapamil, and troleandomycin, with a high k(inact) of 0.91 min(-1) observed for mibefradil in HepaRG cells. The apparent K(I) estimates derived from the various systems displayed a range of variability from 3-fold for clarithromycin (5.4-17.7 µM) to 6-fold for verapamil (1.9-12.6 µM). In general, the inactivation kinetic parameters derived from the cell systems tested fairly replicated what was observed in time-dependent inhibition studies using human liver microsomes. Despite some of the observed differences in inactivation kinetic parameters, the estimated DDIs derived from each of the tested systems generally agreed with the clinically reported DDI within approximately 2-fold. In addition, a plated cell approach offered the ability to conduct longer primary incubations (greater than 30 min), which afforded improved ability to identify the weak time-dependent inhibitor fluoxetine. Overall, results from these studies suggest that in vitro inactivation parameters generated from plated cell systems may be a practical approach for identifying time-dependent inhibitors and for estimating the magnitude of clinical DDIs.

Characterization of aldehyde oxidase enzyme activity in cryopreserved human hepatocytes.

Substrates of aldehyde oxidase (AO), for which human clinical pharmacokinetics are reported, were selected and evaluated in pooled mixed-gender cryopreserved human hepatocytes in an effort to quantitatively characterize AO activity. Estimated hepatic clearance (Cl(h)) for BIBX1382, carbazeran, O6-benzylguanine, zaleplon, and XK-469 using cryopreserved hepatocytes was 18, 17, 12, <4.3, and <4.3 ml · min⁻¹ · kg⁻¹, respectively. The observed metabolic clearance in cryopreserved hepatocytes was confirmed to be a result of AO-mediated metabolism via two approaches. Metabolite identification after incubations in the presence of H2¹8O confirmed that the predominant oxidative metabolite was generated by AO, as expected isotope patterns in mass spectra were observed after analysis by high-resolution mass spectrometry. Second, clearance values were efficiently attenuated upon coincubation with hydralazine, an inhibitor of AO. The low exposure after oral doses of BIBX1382 and carbazeran (∼5% F) would have been fairly well predicted using simple hepatic extraction (f(h)) values derived from cryopreserved hepatocytes. In addition, the estimated hepatic clearance value for O6-benzylguanine was within ∼80% of the observed total clearance in humans after intravenous administration (15 ml · min⁻¹ · kg⁻¹), indicating a reasonable level of quantitative activity from this in vitro system. However, a 3.5-fold underprediction of total clearance was observed for zaleplon, despite the 5-oxo metabolite being clearly observed. These data taken together suggest that the use of cryopreserved hepatocytes may be a practical approach for assessing AO-mediated metabolism in discovery and potentially useful for predicting hepatic clearance of AO substrates.

Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models.

BACKGROUND AND OBJECTIVE: Induction of drug-metabolizing enzymes can lead to drug-drug interactions (DDIs); therefore, early assessment is often conducted. Previous reports focused on true positive cytochrome P450 3A (CYP3A) inducers leaving a gap in translation for in vitro inducers which do not manifest in clinical induction. The goal herein was to expand the in vitro induction dataset by including true negative clinical inducers to identify a correction factor to basic DDI models, which reduces false positives without impacting false negatives. METHODS: True negative clinical inducers were identified through a literature search, in vitro induction parameters were generated in three human hepatocyte donors, and the performance of basic induction models proposed by regulatory agencies, concentration producing twofold induction (F2), basic static model (R3) and relative induction score (RIS), was used to characterize clinical induction risk. RESULTS: The data demonstrated the importance of correcting for in vitro binding and metabolism to derive induction parameters. The aggregate analysis indicates that the RIS with a positive cut-off of < 0.7-fold area under the curve ratio (AUCR) provides the best quantitative prediction. Additionally, correction factors of ten and two times the unbound peak plasma concentration at steady state (Cmax,ss,u) can be confidently used to identify true positive inducers when referenced against the concentration resulting in twofold increase in messenger ribonucleic acid (mRNA) or using the R3 equation, respectively. CONCLUSIONS: These iterative improvements, which reduce the number of false positives, could aid regulatory recommendations and limit unnecessary clinical explorations into CYP3A induction.