Aleksandra Galetin

Prediction of Human Intestinal First-Pass Metabolism of 25 CYP3A Substrates from In Vitro Clearance and Permeability Data

Intestinal first-pass metabolism may contribute to low oral drug bioavailability and drug-drug interactions, particularly for CYP3A substrates. The current analysis predicted intestinal availability (FG) from in vitro metabolic clearance and permeability data of 25 drugs using the QGut model. The drug selection included a wide range of physicochemical properties and in vivo FG values (0.07–0.94). In vitro clearance data (CLuint) were determined in human intestinal (HIM) and three liver (HLM) microsomal pools (n = 105 donors) using the substrate depletion method. Apparent drug permeability (Papp) was determined in Caco-2 and Madin-Darby canine kidney cells transfected with human MDR1 gene (MDCK-MDR1 cells) under isotonic conditions (pH = 7.4). In addition, effective permeability (Peff) data, estimated from regression analyses to Papp or physicochemical properties were used in the FG predictions. Determined CLuint values ranged from 0.022 to 76.7 μl/min/pmol of CYP3A (zolpidem and nisoldipine, respectively). Differences in CLuint values obtained in HIM and HLM were not significant after normalization for tissue-specific CYP3A abundance, supporting their interchangeable usability. The FG predictions were most successful when Papp data from Caco-2/MDCK-MDR1 cells were used directly; in contrast, the use of physicochemical parameters resulted in significant FG underpredictions. Good agreement between predicted and in vivo FG was noted for drugs with low to medium intestinal extraction (e.g., midazolam predicted FG value 0.54 and in vivo value 0.51). In contrast, low prediction accuracy was observed for drugs with in vivo FG <0.5, resulting in considerable underprediction in some instances, as for saquinavir (predicted FG is 6% of the observed value). Implications of the findings are discussed.

Mechanistic pharmacokinetic modeling for the prediction of transporter-mediated disposition in humans from sandwich culture human hepatocyte data

With efforts to reduce cytochrome P450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison with that for compounds with passively mediated pharmacokinetics (PK). In this study, we have assessed the predictability of human PK for seven organic anion-transporting polypeptide (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan, and repaglinide) for which clinical intravenous data were available. In vitro data generated from the sandwich culture human hepatocyte system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution, and biliary efflux parameters as inputs into a PBPK model resulted in the overprediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under- and overpredicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only preclinical data. A prediction strategy for novel OATP substrates is discussed.

Intracellular Drug Concentrations and Transporters: Measurement, Modeling, and Implications for the Liver

Intracellular concentrations of drugs and metabolites are often important determinants of efficacy, toxicity, and drug interactions. Hepatic drug distribution can be affected by many factors, including physicochemical properties, uptake/efflux transporters, protein binding, organelle sequestration, and metabolism. This white paper highlights determinants of hepatocyte drug/metabolite concentrations and provides an update on model systems, methods, and modeling/simulation approaches used to quantitatively assess hepatocellular concentrations of molecules. The critical scientific gaps and future research directions in this field are discussed.

Prediction of Drug Clearance by Glucuronidation from in Vitro Data: Use of Combined Cytochrome P450 and UDP-Glucuronosyltransferase Cofactors in Alamethicin-Activated Human Liver Microsomes

Glucuronidation via UDP-glucuronosyltransferase (UGT) is an increasingly important clearance pathway. In this study intrinsic clearance (CLint) values for buprenorphine, carvedilol, codeine, diclofenac, gemfibrozil, ketoprofen, midazolam, naloxone, raloxifene, and zidovudine were determined in pooled human liver microsomes using the substrate depletion approach. The in vitro clearance data indicated a varying contribution of glucuronidation to the clearance of the compounds studied, ranging from 6 to 79% for midazolam and gemfibrozil, respectively. The CLint was ob tained using either individual or combined cofactors for cytochrome P450 (P450) and UGT enzymes with alamethicin activation and in the presence and absence of 2% bovine serum albumin (BSA). In the presence of combined P450 and UGT cofactors, CLint ranged from 2.8 to 688 μl/min/mg for zidovudine and buprenorphine, respectively; the clearance was approximately equal to the sum of the CLint values obtained in the presence of individual cofactors. The unbound intrinsic clearance (CLint, u) was scaled to provide an in vivo predicted CLint; the data obtained in the presence of combined cofactors resulted in 5-fold underprediction on average. Addition of 2% BSA to the incubation with both P450 and UGT cofactors reduced the bias in the clearance prediction, with 8 of 10 compounds predicted within 2-fold of in vivo values with the exception of raloxifene and gemfibrozil. The current study indicates the applicability of combined cofactor conditions in the assessment of clearance for compounds with a differential contribution of P450 and UGT enzymes to their elimination. In addition, improved predictability of microsomal data is observed in the presence of BSA, in particular for UGT2B7 substrates.

Intestinal and Hepatic Metabolic Activity of Five Cytochrome P450 Enzymes: Impact on Prediction of First-Pass Metabolism

The contribution of the gut is not routinely incorporated into in vitro-in vivo predictions of either clearance or drug-drug interactions, and this omission may partially explain the general underprediction trend often observed. In the current study, the metabolic ability of hepatic and intestinal pooled microsomes was compared for eight CYP3A substrates (midazolam, triazolam, diazepam, alprazolam, flunitrazepam, nifedipine, testosterone, and quinidine) and paclitaxel, tolbutamide, S-mephenytoin, and bufuralol as CYP2C8, CYP2C9, CYP2C19, and CYP2D6 probes, respectively. A general agreement in the type of kinetics was observed between the two systems for the substrates investigated. Of the 16 pathways investigated, 75% of Km (S50) values obtained in intestinal microsomes (5.9-769 μM) were within 2-fold of hepatic estimates. Irrespective of the cytochrome P450 (P450) investigated and normalization of Vmax values for the P450 abundance, clearance was 4.5- to 50-fold lower in intestinal microsomes (0.0005-0.51 μl/min/P450) compared with the hepatic estimates (0.002-5.8 μl/min/P450), whereas the rank order was consistent between the systems. Assessment of two enterocyte isolation methods (mucosal scraping or enterocyte elution) was performed at the substrate concentrations corresponding to the determined Vmax conditions for 11 pathways. The activity difference between the methods (3-29-fold) was P450-related in the following rank order: CYP2C19 > CYP3A4 > CYP2C9 ∼ CYP2D6. After correction for the loss of activity between the methods, the intrinsic activities of hepatic and intestinal CYP3A4, CYP2C9, CYP2C19, and CYP2D6 were comparable for the 16 pathways. The implications of these findings on the prediction of intestinal first-pass metabolism are discussed.

Prediction of time-dependent CYP3A4 drug-drug interactions : Impact of enzyme degradation, parallel elimination pathways, and intestinal inhibition

Time-dependent inhibition of CYP3A4 often results in clinically significant drug-drug interactions. In the current study, 37 in vivo cases of irreversible inhibition were collated, focusing on macrolides (erythromycin, clarithromycin, and azithromycin) and diltiazem as inhibitors. The interactions included 17 different CYP3A substrates showing up to a 7-fold increase in AUC (13.5% of studies were in the range of potent inhibition). A systematic analysis of the impact of CYP3A4 degradation half-life (mean t1/2deg = 3 days, ranging from 1 to 6 days) on the prediction of the extent of interaction for compounds with a differential contribution from CYP3A4 to the overall elimination (defined by fmCYP3A4) was performed. Although the prediction accuracy was very sensitive to the CYP3A4 degradation rate for substrates mainly eliminated by this enzyme (fmCYP3A4 ≥ 0.9), minimal effects are observed when CYP3A4 contributes less than 50% to the overall elimination in cases when the parallel elimination pathway is not subject to inhibition. Use of the mean CYP3A4 t1/2deg (3 days), average unbound systemic plasma concentration of the inhibitor, and the corresponding fmCYP3A4 resulted in 89% of studies predicted within 2-fold of the in vivo value. The impact of the interaction in the gut wall was assessed by assuming maximal intestinal inhibition of CYP3A4. Although a reduced number of false-negative predictions was observed, there was an increased number of overpredictions, and generally, a loss of prediction accuracy was observed. The impact of the possible interplay between CYP3A4 and efflux transporters on the intestinal interaction requires further evaluation.

ITC Recommendations for Transporter Kinetic Parameter Estimation and Translational Modeling of Transport‐Mediated PK and DDIs in Humans

This white paper provides a critical analysis of methods for estimating transporter kinetics and recommendations on proper parameter calculation in various experimental systems. Rational interpretation of transporter‐knockout animal findings and application of static and dynamic physiologically based modeling approaches for prediction of human transporter‐mediated pharmacokinetics and drug–drug interactions (DDIs) are presented. The objective is to provide appropriate guidance for the use of in vitro, in vivo, and modeling tools in translational transporter science.

Prediction of in vivo drug-drug interactions from in vitro data : factors affecting prototypic drug-drug interactions involving CYP2C9, CYP2D6 and CYP3A4.

BackgroundQuantitative predictions of in vivo drug-drug interactions (DDIs) resulting from metabolic inhibition are commonly made based upon the inhibitor concentration at the enzyme active site [I] and the in vitro inhibition constant (Ki). Previous studies have involved the use of various plasma inhibitor concentrations as surrogates for [I] along with Ki values obtained from published literature. Although this approach has resulted in a high proportion of successful predictions, a number of falsely predicted interactions are also observed.ObjectivesTo focus on three issues that may influence the predictive value of the [I]/Ki ratio approach: (i) the use of unbound Ki (Ki,u) values generated from standardised in vitro experiments compared with literature values; (ii) the selection of an appropriate [I]; and (iii) incorporation of the impact of intestinal metabolic inhibition for cytochrome P450 (CYP) 3A4 predictions. To this end we have selected eight inhibitors of CYP2C9, CYP2D6 and CYP3A4 and 18 victim drugs from a previous database analysis to allow prediction of 45 clinical DDI studies.MethodsIn vitro kinetic and inhibition studies were performed in human liver microsomes using prototypic probe substrates of CYP2C9 and CYP2D6, with various inhibitors (miconazole, sulfaphenazole, fluconazole, ketoconazole, quinidine, fluoxetine, fluvoxamine). The Ki estimates obtained were corrected for non-specific microsomal binding, and the Ki,u was incorporated into in vivo predictions using various [I] values. Predictions for CYP3A4 were based upon in vitro data obtained from a previous publication within our laboratory, and an assessment of the impact of the interaction in the gut wall is included. Predictions were validated against 45 in vivo studies and those within 2-fold of the in vivo ratio of area under the plasma concentration-time curve of the substrate, in the presence and absence of the inhibitor (AUCi/AUC) were considered successful.ResultsPredictions based upon the average systemic total plasma drug concentration ([I]av) [incorporating the effects of parallel drug elimination pathways] and the Ki,u value resulted in 91% of studies predicted to within 2-fold of the in vivo AUCi/AUC. This represents a 35% improvement in prediction accuracy compared with predictions based upon total Ki values obtained from various published literature sources. A corresponding reduction in bias and an increase in precision were also observed compared with the use of other [I] surrogates (e.g. the total and new unbound maximum hepatic input plasma concentrations). No significant improvement in prediction accuracy was observed by incorporating consideration of gut wall inhibition for CYP3A4.ConclusionDDI predictions based upon the use of Ki,u data obtained under a set of optimal standardised conditions were significantly improved compared with predictions using in vitro data collated from various sources. The use of [I]av as the [I] surrogate generated the most successful predictions as judged by several criteria. Incorporation of either plasma protein binding of inhibitor or gut wall CYP3A4 inhibition did not result in a general improvement of DDI predictions.

Methods for predicting in vivo pharmacokinetics using data from in vitro assays.

Strategies for optimising in vivo predictions from in vitro data on metabolic stability and CYP inhibition are discussed. Potential pitfalls and areas of inaccuracy are highlighted together with recommendations for best practice. The use of both hepatic microsomes and isolated hepatocytes for the assessment of metabolic stability is discussed in terms of scaling from the in vitro system up to whole liver. The importance of integrating metabolic stability data together with other drug pharmacokinetic characteristics (e.g., protein binding and red blood cell uptake) as well as blood flow are presented within the context of different liver models. The assessment of CYP inhibition potential requires in vitro data on the inhibitor potency either in the form of Ki (for reversible inhibition) or KI and kinact (for time-dependent inhibition). The integration of these in vitro parameters together with other pharmacokinetic information is essential for the in vivo prediction. While a qualitative assessment may be made from the I/Ki ratio, a number of additional victim drug and enzyme-related parameters are required for quantitative prediction. Of particular importance is the parameter fmCYP (the fraction of the metabolic clearance of the victim drug that is catalyzed by the enzyme subject to the inhibition). Impact of other victim drug properties (e.g., fractional importance of the intestine) and enzyme properties (e.g., kdeg for time-dependent inhibition) on the drug-drug interaction prediction is discussed. In addition, mechanisms by which false negatives and false positives may result from in vitro strategies are summarized. Finally perspectives for future application and improvements in these predictions strategies are outlined.

Relative importance of intestinal and hepatic glucuronidation-impact on the prediction of drug clearance.

PurposeTo assess the extent of intestinal and hepatic glucuronidation in vitro and resulting implications on glucuronidation clearance prediction.MethodsAlamethicin activated human intestinal (HIM) and hepatic (HLM) microsomes were used to obtain intrinsic glucuronidation clearance (CLint,UGT) for nine drugs using substrate depletion. The in vitro extent of glucuronidation (fmUGT) was determined using P450 and UGT cofactors. Utility of hepatic CLint for the prediction of in vivo clearance was assessed.ResultsfmUGT (8–100%) was comparable between HLM and HIM with the exception of troglitazone, where a nine-fold difference was observed (8% and 74%, respectively). Scaled intestinal CLint,UGT (per g tissue) was six- and nine-fold higher than hepatic for raloxifene and troglitazone, respectively, and comparable to hepatic for naloxone. The remaining drugs had a higher hepatic than intestinal CLint,UGT (average five-fold). For all drugs with P450 clearance, hepatic CLint,CYP was higher than intestinal (average 15-fold). Hepatic CLint,UGT predicted on average 22% of observed in vivo CLint; with the exception of raloxifene and troglitazone, where the prediction was only 3%.ConclusionIntestinal glucuronidation should be incorporated into clearance prediction, especially for compounds metabolised by intestine specific UGTs. Alamethicin activated microsomes are useful for the assessment of intestinal glucuronidation and fmUGTin vitro.