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 K(m) (S(50)) values obtained in intestinal microsomes (5.9-769 microM) were within 2-fold of hepatic estimates. Irrespective of the cytochrome P450 (P450) investigated and normalization of V(max) values for the P450 abundance, clearance was 4.5- to 50-fold lower in intestinal microsomes (0.0005-0.51 microl/min/P450) compared with the hepatic estimates (0.002-5.8 microl/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 V(max) conditions for 11 pathways. The activity difference between the methods (3-29-fold) was P450-related in the following rank order: CYP2C19 > CYP3A4 > CYP2C9 approximately 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 in vivo drug-drug interactions from in vitro data: impact of incorporating parallel pathways of drug elimination and inhibitor absorption rate constant

AIMS

Success of the quantitative prediction of drug-drug interactions via inhibition of CYP-mediated metabolism from the inhibitor concentration at the enzyme active site ([I]) and the in vitro inhibition constant (K(i)) is variable. The aim of this study was to examine the impact of the fraction of victim drug metabolized by a particular CYP (f(mCYP)) and the inhibitor absorption rate constant (k(a)) on prediction accuracy.

METHODS

Drug-drug interaction studies involving inhibition of CYP2C9, CYP2D6 and CYP3A4 (n = 115) were investigated. Data on f(mCYP) for the probe substrates of each enzyme and k(a) values for the inhibitors were incorporated into in vivo predictions, alone or in combination, using either the maximum hepatic input or the average systemic plasma concentration as a surrogate for [I]. The success of prediction (AUC ratio predicted within twofold of in vivo value) was compared using nominal values of f(mCYP) = 1 and k(a) = 0.1 min(-1).

RESULTS

The incorporation of f(mCYP) values into in vivo predictions using the hepatic input plasma concentration resulted in 84% of studies within twofold of in vivo value. The effect of k(a) values alone significantly reduced the number of over-predictions for CYP2D6 and CYP3A4; however, less precision was observed compared with the f(mCYP). The incorporation of both f(mCYP) and k(a) values resulted in 81% of studies within twofold of in vivo value.

CONCLUSIONS

The incorporation of substrate and inhibitor-related information, namely f(mCYP) and k(a), markedly improved prediction of 115 interaction studies with CYP2C9, CYP2D6 and CYP3A4 in comparison with [I]/K(i) ratio alone.

In vitro–in vivo correlation for drugs and other compounds eliminated by glucuronidation in humans: Pitfalls and promises

Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily are responsible for the metabolism of many drugs, environmental chemicals and endogenous compounds. Identification of the UGT(s) involved in the metabolism of a given compound ('reaction phenotyping') currently relies on multiple confirmatory approaches, which may be confounded by the dependence of UGT activity on enzyme source, incubation conditions, and the occurrence of atypical glucuronidation kinetics. However, the increasing availability of substrate and inhibitor 'probes' for the individual UGTs provides the prospect for reliable phenotyping of glucuronidation reactions using human liver microsomes or hepatocytes, thereby providing data directly relevant to drug metabolism in humans. While the feasibility of computational prediction of UGT substrate selectivity has been demonstrated, the development of easily interpretable and generalisable models requires further improvement in the datasets available for analysis. Quantitative prediction of the hepatic clearance of glucuronidated drugs and the magnitude of inhibitory interactions based on in vitro kinetic data is more problematic. Intrinsic clearance (CL(int)) values generated using human liver microsomes under-predict in vivo hepatic clearance, typically by an order of magnitude. In vivo clearances of glucuronidated drugs are also generally under-predicted by CL(int) values from human hepatocytes, but to a lesser extent than observed with the microsomal model. While it is anticipated that systematic analysis of the potential causes of under-prediction may provide more reliable in vitro-in vivo scaling strategies, mechanistic interpretation of in vitro-in vivo correlation more broadly awaits further advances in our understanding of the structural and cellular determinants of UGT activity.

Determination of a Human Hepatic Microsomal Scaling Factor for Predicting in Vivo Drug Clearance

PURPOSE

To determine a microsomal scaling factor for human liver suitable for prediction of in vivo drug clearance from in vitro data and to explore the role of inter-liver variability in this factor on the reported underprediction from microsomal parameters.

METHODS

Cytochrome P450 (henceforth P450) content in whole homogenates and microsomes from 38 donor livers was used to determine a microsomal scaling factor. In a subset (n = 20) of these preparations, individual P450 enzymes were examined by Western blotting and selective probe activities were determined.

RESULTS

The scaling factor from 38 livers averaged 40 mg microsomal protein per gram liver with a coefficient of variation of 31%. Western blotting experiments indicated that there was no P450 enzyme-specific trend in the distribution of individual P450 enzymes in liver microsomes relative to whole homogenate. Predictions based on an average scaling factor resulted in a satisfactory prediction of intrinsic clearance of three benzodiazepines similar to that obtained using individual factors for the same livers.

CONCLUSION

A value for human liver microsomal scaling of 40 mg microsomal protein per gram liver has been established. The reason for underprediction previously reported for 52 different drug substrates was not the use of an incorrect value for the scaling factor.

Prediction of In Vivo Drug-Drug Interactions from In Vitro Data

BACKGROUND

Quantitative 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 (K(i)). Previous studies have involved the use of various plasma inhibitor concentrations as surrogates for [I] along with K(i) 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.

OBJECTIVES

To focus on three issues that may influence the predictive value of the [I]/K(i) ratio approach: (i) the use of unbound K(i) (K(i,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.

METHODS

In 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 K(i) estimates obtained were corrected for non-specific microsomal binding, and the K(i,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 (AUC(i)/AUC) were considered successful.

RESULTS

Predictions based upon the average systemic total plasma drug concentration ([I](av)) [incorporating the effects of parallel drug elimination pathways] and the K(i,u) value resulted in 91% of studies predicted to within 2-fold of the in vivo AUC(i)/AUC. This represents a 35% improvement in prediction accuracy compared with predictions based upon total K(i) 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.

CONCLUSION

DDI predictions based upon the use of K(i,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.

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 fm(CYP3A4 >or= 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 fm(CYP3A4) 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.

The utility of in vitro cytochrome P450 inhibition data in the prediction of drug-drug interactions

The accuracy of in vitro inhibition parameters in scaling to in vivo drug-drug interactions (DDI) was examined for over 40 drugs using seven human P450-selective marker activities in pooled human liver microsomes. These data were combined with other parameters (systemic C(max), estimated hepatic inlet C(max), fraction unbound, and fraction of the probe drug cleared by the inhibited enzyme) to predict increases in exposure to probe drugs, and the predictions were compared with in vivo DDI gathered from clinical studies reported in the scientific literature. For drugs that had been tested as precipitants of drug interactions for more than one P450 in vivo, the order of inhibitory potencies in vitro generally aligned with the magnitude of the in vivo interactions. With the exception of many drugs known to be mechanism-based inactivators, the use of in vitro IC(50), the fraction of the affected drug metabolized by the target enzyme [f(m(CYP))] and an estimate of free hepatic inlet C(max), was generally successful in identifying those drugs that cause at least a 2-fold increase in the exposure to P450 marker substrate drugs. For CYP3A, incorporation of inhibition of both hepatic and intestinal metabolism was needed for the prediction of DDI. Many CYP3A inhibitors showed a different inhibitory potency for three different CYP3A marker activities; however, these differences generally did not alter the conclusions regarding whether a drug would cause a CYP3A DDI in vivo. Overall, these findings support the conclusion that P450 in vitro inhibition data are valuable in designing clinical DDI study strategies and can be used to predict the magnitudes of DDI.

Prediction of metabolic clearance using cryopreserved human hepatocytes: kinetic characteristics for five benzodiazepines

Predictions of intrinsic clearance (CL(int)) from human liver microsomes often underestimate in vivo observations. In this study, a series of five benzodiazepines was used as prototypic CYP3A4 substrates to investigate the prediction of clearance from the less studied alternative in vitro system, cryopreserved human hepatocytes. Formation of the two major metabolites from midazolam, triazolam, diazepam, flunitrazepam, and alprazolam was measured in cryopreserved human hepatocytes from five donors; the kinetics were characterized and CL(int) values were determined and scaled to predict CL(int) in vivo. At least one of the two major pathways of metabolic clearance of each benzodiazepine was characterized by autoactivation in hepatocytes; the extent to which this occurred varied depending on substrate and liver (up to 8-fold). Heteroactivation by testosterone of these pathways was also observed (up to 6-fold). The maximum autoactivated clearance was used to predict in vivo CL(int) (1.6-138 ml/min/kg) which closely agreed with values previously obtained using human liver microsomes. Comparison with in vivo CL(int) indicates that cryopreserved human hepatocytes systematically underpredict CL(int). When three previous studies (documenting CL(int) for substrates of various enzymes in cryopreserved human hepatocytes using drug depletion-time profiles) were considered as well, the combined data show a consistent underprediction of 5.6-fold. Collectively it is demonstrated that the predicted hepatic intrinsic clearances from cryopreserved hepatocytes show an excellent rank order with in vivo findings but are systematically underpredicting the in vivo value.

Impact of parallel pathways of drug elimination and multiple cytochrome P450 involvement on drug-drug interactions: CYP2D6 paradigm

The success of in vitro derived Ki values for predicting drug-drug interactions in vivo has been mixed. For example, the use of hepatic input concentration of inhibitor has resolved the negative and positive interactions on the qualitative level, eliminating false negative predictions. However, several examples of false positives and a high incidence of over-predictions of true positive interactions indicated a need for incorporation of additional factors. The aim of this study was to investigate the effect of parallel elimination pathways as a possible reason for false positives and over-predictions. Simulation studies indicated that the degree of interaction (assessed by area under the plasma concentration-time curve ratio in the presence and absence of inhibitor) depends largely on the fraction of substrate metabolized by the particular P450 enzyme (fmCYPi) that is inhibited. The current analysis focused on CYP2D6 interactions due to the well documented genetic polymorphism and the ability to estimate fmCYP2D6 readily from in vivo data obtained in extensive and poor metabolizers. Based on either a phenotype study or an alternative regression analysis approach, the fmCYP2D6 values of 0.37 to 0.94 and 0.25 to 0.89, respectively, were obtained for nine substrates. Prediction of 44 drug-drug interaction studies was improved by the combination of parallel pathways of elimination and their susceptibility to inhibition. The overall success of predicting positive and negative interactions was increased from 54% to 84%, and the number of over-predictions was substantially reduced. It is concluded that incorporating parallel pathways provides a valuable step forward in making quantitative predictions of drug-drug interactions from in vitro data.

Substrate depletion approach for determining in vitro metabolic clearance: time dependencies in hepatocyte and microsomal incubations

The substrate depletion method is a popular approach used for the measurement of in vitro intrinsic clearance (CL(int)). However, the incubation conditions used in these studies can vary, the consequences of which have not been systematically explored. Initial substrate depletion incubations using rat microsomes and hepatocytes were performed for eight benzodiazepines: alprazolam, clobazam, clonazepam, chlordiazepoxide, diazepam, flunitrazepam, midazolam, and triazolam. Subsequent predictions of in vivo CL(int) (ranging from 3 to 200 ml/min) and hepatic clearance (CL(H)) (ranging from 0.3 to 15 ml/min) demonstrated that the general predictive ability of this approach was similar to that of the traditional metabolite formation method. A more detailed study of the substrate depletion profiles and CL(int) estimates indicated that the concentration of enzyme used is of particular importance. The metabolism of triazolam, clonazepam, and diazepam was monoexponential at all cell densities using hepatocytes; however, with microsomes, biphasic depletion was apparent, particularly at higher microsomal protein concentrations (2-5 mg/ml). Enzyme activity studies indicated that enzyme loss was more pronounced in the microsomal system (ranged from 8 to 65% activity after a 1-h incubation) compared with the hepatocyte system (approximately 100% activity after a 1-h incubation). For clonazepam (a low clearance substrate), these biphasic profiles could be explained by loss of enzyme activity. To ensure accurate predictions of in vivo CL(int) and CL(H) when using the substrate depletion approach, based on the results obtained for this class of drugs, it is recommended that low enzyme concentrations and short incubation times are used whenever possible.

Prediction of in vitro intrinsic clearance from hepatocytes: comparison of suspensions and monolayer cultures

Due to the time-dependent loss of cytochrome P450 (P450)-mediated metabolism in freshly isolated hepatocytes, several types of culture systems have been developed to extend their lifespan. The aim of this study was to evaluate the ability of monolayer cultures of rat hepatocytes to determine the in vitro CL(int) compared with suspensions of freshly isolated hepatocytes. Seven compounds were incubated in rat hepatocyte suspensions and monolayer cultures, and in vitro CL(int) was obtained via metabolite formation (12 pathways) or substrate depletion approaches. Only two compounds (tolbutamide and 7-ethoxycoumarin) gave comparable (within 2-fold) in vitro CL(int) in both suspensions and monolayer cultures. Although the overall rank order of compounds was the same in both models (covering a range of 3-4 orders of magnitude), the prediction of in vitro CL(int) for high-turnover compounds (seven pathways) was lower for monolayer cultures compared with suspensions, probably due to an uptake rate limitation leading to increases in K(M). In general, there was an average 50% loss of the P450 activity in monolayers based on a decrease in V(max) relative to suspensions. However, monolayer cultures gave a higher estimation of in vitro CL(int) for the low-turnover compound S-warfarin compared with fresh cell suspensions due to a decrease in the K(M) of the four individual metabolites. The use of hepatocyte monolayer cultures may offer the potential advantage of extending the lower end of the usable clearance range (below 0.1 microl/min/10(6) cells) for predicting in vivo CL(int).

CYP3A4 substrate selection and substitution in the prediction of potential drug-drug interactions

The complexity of in vitro kinetic phenomena observed for CYP3A4 substrates (homo- or heterotropic cooperativity) confounds the prediction of drug-drug interactions, and an evaluation of alternative and/or pragmatic approaches and substrates is needed. The current study focused on the utility of the three most commonly used CYP3A4 in vitro probes for the prediction of 26 reported in vivo interactions with azole inhibitors (increase in area under the curve ranged from 1.2 to 24, 50% in the range of potent inhibition). In addition to midazolam, testosterone, and nifedipine, quinidine was explored as a more "pragmatic" substrate due to its kinetic properties and specificity toward CYP3A4 in comparison with CYP3A5. Ki estimates obtained in human liver microsomes under standardized in vitro conditions for each of the four probes were used to determine the validity of substrate substitution in CYP3A4 drug-drug interaction prediction. Detailed inhibitor-related (microsomal binding, depletion over incubation time) and substrate-related factors (cooperativity, contribution of other metabolic pathways, or renal excretion) were incorporated in the assessment of the interaction potential. All four CYP3A4 probes predicted 69 to 81% of the interactions with azoles within 2-fold of the mean in vivo value. Comparison of simple and multisite mechanistic models and interaction prediction accuracy for each of the in vitro probes indicated that midazolam and quinidine in vitro data provided the best assessment of a potential interaction, with the lowest bias and the highest precision of the prediction. Further investigations with a wider range of inhibitors are required to substantiate these findings.

Prediction of Human Drug Clearance from in Vitro and Preclinical Data Using Physiologically Based and Empirical Approaches

PURPOSE

The aim of this study is to compare the accuracy of five methods for predicting in vivo intrinsic clearance (CL(int)) and seven for predicting hepatic clearance (CL(h)) in humans using in vitro microsomal data and/or preclinical animal data.

METHODS

The human CL(int) was predicted for 33 drugs by five methods that used either in vitro data with a physiologic scaling factor (SF), with an empirical SF, with the physiologic and drug-specific (the ratio of in vivo and in vitro CL(int) in rats) SFs, or rat CL(int) directly and with allometric scaling. Using the estimated CL(int), the CL(h) in humans was calculated according to the well-stirred liver model. The CL(h) was also predicted using additional two methods: using direct allometric scaling or drug-specific SF and allometry.

RESULTS

Using in vitro human microsomal data with a physiologic SF resulted in consistent underestimation of both CL(int) and CL(h). This bias was reduced by using either an empirical SF, a drug-specific SF, or allometry. However, for allometry, there was a substantial decrease in precision. For drug-specific SF, bias was less reduced, precision was similar to an empirical SF. Both CL(int) and CL(h) were best predicted using in vitro human microsomal data with empirical SF. Use of larger data set of 52 drugs with the well-stirred liver model resulted in a best-fit empirical SF that is 9-fold increase on the physiologic SF.

CONCLUSIONS

Overall, the empirical SF method and the drug-specific SF method appear to be the best methods; they show lower bias than the physiologic SF and better precision than allometric approaches. The use of in vitro human microsomal data with an empirical SF may be preferable, as it does not require extra information from a preclinical study.

Predictive Models of CYP3A4 Heteroactivation: In Vitro-in Vivo Scaling and Pharmacophore Modeling

Although activation of CYP3A4 is frequently observed in vitro, predictive computational-based models and methods for in vitro-in vivo scaling are scarce. It has been previously shown that in vitro CYP3A4 heteroactivation of carbamazepine (CBZ)-epoxide (ep) formation can be associated with the clinical drug interaction between felbatame and CBZ. The previously reported prediction methodology is applied here to an additional set of in vitro CYP3A4 heteroactivators, some exerting this effect at concentrations relevant in vivo. The antimalarial artemisinin potently increases CBZ-ep formation by a maximum of 500% at 300 microM. Testosterone and progesterone activates by a maximum of 1680 and 920%, respectively, at 150 microM, and quinidine causes a 130% increase at 300 microM. The predicted maximum in vivo decrease in steady-state concentration of carbamazepine (Css(CBZ)) at saturating effector concentrations is 85 to 90% for testosterone and progesterone, 75% for artemisinin, and 45% for quinidine. The corresponding predicted in vivo increase in Css(CBZ-ep) is 50, 60, 55, and 30% for artemisinin, testosterone, progesterone, and quinidine, respectively. At effector concentrations relevant in vivo, the Css(CBZ) change is predicted to </=20% for testosterone, artemisinin, and quinidine and </=10% for progesterone, with a concomitant Css(CBZ-ep) increase of 12% for testosterone and </=10% for progesterone, artemisinin, and quinidine. Structure-heteroactivation relationships were evaluated by generating a pharmacophore. The model includes two hydrogen bond acceptor features separated by hydrophobic features. Internal predictivity is high, and heteroactivation of an external test set correlate to observed in vitro heteroactivation.

CORRECTION TO "TISSUE DISTRIBUTION, STABILITY, AND PHARMACOKINETICS OF APO2 LIGAND/TUMOR NECROSIS FACTOR-RELATED APOPTOSIS-INDUCING LIGAND IN HUMAN COLON CARCINOMA COLO205 TUMOR-BEARING MICE"

Due to the time-dependent loss of cytochrome P450 (P450)-mediated metabolism in freshly isolated hepatocytes, several types of culture systems have been developed to extend their lifespan. The aim of this study was to evaluate the ability of monolayer cultures of rat hepatocytes to determine the in vitro CL(int) compared with suspensions of freshly isolated hepatocytes. Seven compounds were incubated in rat hepatocyte suspensions and monolayer cultures, and in vitro CL(int) was obtained via metabolite formation (12 pathways) or substrate depletion approaches. Only two compounds (tolbutamide and 7-ethoxycoumarin) gave comparable (within 2-fold) in vitro CL(int) in both suspensions and monolayer cultures. Although the overall rank order of compounds was the same in both models (covering a range of 3-4 orders of magnitude), the prediction of in vitro CL(int) for high-turnover compounds (seven pathways) was lower for monolayer cultures compared with suspensions, probably due to an uptake rate limitation leading to increases in K(M). In general, there was an average 50% loss of the P450 activity in monolayers based on a decrease in V(max) relative to suspensions. However, monolayer cultures gave a higher estimation of in vitro CL(int) for the low-turnover compound S-warfarin compared with fresh cell suspensions due to a decrease in the K(M) of the four individual metabolites. The use of hepatocyte monolayer cultures may offer the potential advantage of extending the lower end of the usable clearance range (below 0.1 microl/min/10(6) cells) for predicting in vivo CL(int).

UTILITY OF RECOMBINANT ENZYME KINETICS IN PREDICTION OF HUMAN CLEARANCE: IMPACT OF VARIABILITY, CYP3A5, AND CYP2C19 ON CYP3A4 PROBE SUBSTRATES

A systematic kinetic analysis of the metabolism of five benzodiazepines (low to high clearance compounds) was performed in CYP3A4, CYP3A5, and CYP2C19 baculovirus-expressed recombinant systems. The data obtained in the expression systems were scaled and compared with human liver microsomal predicted clearance and observed in vivo values, using either cytochrome P450 relative activity factors (RAFs) or the relative abundance approach. Interindividual variability, both in content (CYP3A4, CYP3A5) and activity (CYP3A4, CYP3A5, and CYP2C19), were incorporated in the clearance prediction by bootstrap analysis. These resampling Monte Carlo-based simulations were performed to justify any distribution assumptions in the generated range of the predicted clearance due to a limited sample size. This approach allowed extrapolation of the recombinant clearance data to specific population groups and investigation of the role of "minor" forms like CYP3A5 and CYP2C19 in comparison to the most prolific CYP3A4. The use of quinidine 3-hydroxylation and alprazolam 1'-hydroxylation as RAF markers for CYP3A4 and CYP3A5 activity, respectively, and the incorporation of variability improved the clearance prediction of the selected benzodiazepines (apart from flunitrazepam) to within 2-fold of the in vivo value. Clearance estimates from the immunoquantified protein levels were approximately 8-fold lower in comparison to the RAF approach. The differences observed in the benzodiazepine metabolite pathway ratios between CYP3A4 and CYP3A5, particularly for 1'- to 4-hydroxymidazolam and alprazolam, provided a useful measure of interindividual differences within the CYP3A family.

Progress towards prediction of human pharmacokinetic parameters from in vitro technologies

This review provides an academic view of the current status on using in vitro systems for the prediction of human in vivo drug clearance and inhibition interaction potential. It stresses that although in vitro technology continues to develop in an impressive way and expectations are high within the pharmaceutical industry, the potential of prediction process is yet to be fully realized. The principles of scaling and modeling in vitro parameters have a sound base and have been validated by using animal tissue. However, it is clear that the comparatively simple standard approach developed and validated in animal systems, results in a high incidence of underprediction for parameters describing clearance and inhibition interaction potential when applied to humans. There are several challenges to our ability to interpret the human in vitro data that can now be so readily generated, in particular, accommodating the unusual kinetic properties characteristic of CYP3A4 substrates, namely, positive and negative cooperativity, in the assessment of inhibition potential.

Database analyses for the prediction of in vivo drug-drug interactions from in vitro data

AIMS

In theory, the magnitude of an in vivo drug-drug interaction arising from the inhibition of metabolic clearance can be predicted using the ratio of inhibitor concentration ([I]) to inhibition constant (K(i)). The aim of this study was to construct a database for the prediction of drug-drug interactions from in vitro data and to evaluate the use of the various estimates for the inhibitor concentrations in the term [I]/K(i).

METHODS

One hundred and ninety-three in vivo drug-drug interaction studies involving inhibition of CYP3A4, CYP2D6 or CYP2C9 were collated from the literature together with in vitro K(i) values and pharmacokinetic parameters for inhibitors, to allow calculation of average/maximum systemic plasma concentration during the dosing interval and maximum hepatic input plasma concentration (both total and unbound concentration). The observed increase in AUC (decreased clearance) was plotted against the estimated [I]/K(i) ratio for qualitative zoning of the predictions.

RESULTS

The incidence of false negative predictions (AUC ratio > 2, [I]/K(i) < 1) was largest using the average unbound plasma concentration and smallest using the hepatic input total plasma concentration of inhibitor for each of the CYP enzymes. Excluding mechanism-based inhibition, the use of total hepatic input concentration resulted in essentially no false negative predictions, though several false positive predictions (AUC ratio < 2, [I]/K(i) > 1) were found. The incidence of true positive predictions (AUC ratio > 2, [I]/K(i) > 1) was also highest using the total hepatic input concentration.

CONCLUSIONS

The use of the total hepatic input concentration of inhibitor together with in vitro K(i) values was the most successful method for the categorization of putative CYP inhibitors and for identifying negative drug-drug interactions. However this approach should be considered as an initial discriminating screen, as it is empirical and requires subsequent mechanistic studies to provide a comprehensive evaluation of a positive result.

Comparison of the Use of Liver Models for Predicting Drug Clearance Using in Vitro Kinetic Data from Hepatic Microsomes and Isolated Hepatocytes

PURPOSE

To compare three liver models (well-stirred, parallel tube, and dispersion) for the prediction of in vivo intrinsic clearance (CL(int)), hepatic clearance (CLh). and hepatic availability (Fh) of a wide range of drugs in the rat using in vitro data from two in vitro sources.

METHODS

In vitro CL(int) was obtained from studies using isolated rat hepatocytes (35 drugs) or rat liver microsomes (52 drugs) and used to predict in vivo CL(int) using reported scaling factors, and subsequently CLh and Fh were predicted based on the three liver models. In addition, in vivo CL(int) values were calculated from the reported values of CLh based on each of the three models.

RESULTS

For all of the parameters, predictions from hepatocyte data were consistently more accurate than those from microsomal data. Comparison of in vitro and in vivo CL(int) values demonstrated that the dispersion model and the parallel tube model were comparable and more accurate (less bias, more precise) than the well-stirred model. For CLh and Fh prediction, the three models performed similarly.

CONCLUSIONS

Considering the statistics of the predictions for three liver models, the use of parallel tube model is recommended for the evaluation of in vitro CL(int) values both from microsomes and hepatocytes. However, for the prediction of the in vivo drug (hepatic) clearance from in vitro data, as there are minimal differences between the models, the use of the well-stirred liver model is recommended.

QUANTITATIVE PREDICTION OF THE IN VIVO INHIBITION OF DIAZEPAM METABOLISM BY OMEPRAZOLE USING RAT LIVER MICROSOMES AND HEPATOCYTES

The diazepam (DZ)-omeprazole (OMP) interaction has been selected as a prototype for an important drug-drug interaction involving cytochrome P450 inhibition. The availability of an in vivo K(i) value (unbound K(i), 21 microM) obtained from a series of steady-state inhibitor infusion studies allowed assessment of several in vitro-derived predictions of this inhibition interaction. Studies monitoring substrate depletion with time were used to obtain in vitro K(i) values that were evaluated against the more traditional metabolite formation approach using microsomes and hepatocytes. OMP inhibited the metabolism of DZ to its primary metabolites 4'-hydroxydiazepam, 3-hydroxydiazepam, and nordiazepam to different extents over a range of concentrations (0.3-150 microM), and a competitive inhibition model best fitted the data. The K(i) values observed using the substrate depletion approach (16 +/- 3 microM and 7 +/- 2 microM in microsomes and hepatocytes, respectively) were in good agreement with the overall weighted K(i) values obtained using the standard metabolite formation approach (12 +/- 2 microM and 16 +/- 5 microM in microsomes and hepatocytes, respectively). In vitro binding and cell uptake studies as well as human serum albumin studies in hepatocytes confirmed the importance of both intracellular and extracellular unbound concentrations of inhibitor when considering inhibition predictions. Both kinetic approaches and both in vitro systems predicted the in vivo interaction well and provide a good example of the ability of in vitro inhibition studies to quantitatively predict an in vivo drug-drug interaction successfully.

COMPARISON OF FRESH AND CRYOPRESERVED RAT HEPATOCYTE SUSPENSIONS FOR THE PREDICTION OF IN VITRO INTRINSIC CLEARANCE

Freshly isolated hepatocytes are currently regarded as the most superior in vitro model for use in prediction studies, in particular to provide estimates of in vivo intrinsic clearance (CL(int)). However, due to their loss of viability within 4 h and a decrease in cytochrome P450-dependent metabolism upon culture, newer cellular models are being developed. Cryopreserved hepatocytes have several potential advantages, but to date evaluation of the utility of this model for estimating in vitro CL(int) has been limited to the substrate depletion approach. We have incubated eight compounds with suspensions of freshly isolated and cryopreserved rat hepatocytes and obtained in vitro CL(int) via metabolite formation kinetics (for 14 pathways). A substantial range of in vitro CL(int) values (0.1-98 microl/min/10(6)cells) was obtained in both models, and the freshly isolated suspension data were in good agreement with the literature. Cryopreserved suspensions were able to give a comparable estimation (within 2-fold) of in vitro CL(int) to fresh cells for six pathways, namely tolbutamide, three diazepam metabolites, propranolol, and 7-hydroxylation of warfarin. A higher estimation of in vitro CL(int) was obtained for the three other metabolites of warfarin due to a decrease in the K(M) values. Lower estimations of in vitro CL(int) were observed for four compounds (six pathways), and this was particularly pronounced (4-16%) for pathways showing atypical Michaelis-Menten kinetic profiles (dextromethorphan, nordiazepam) but less so (25-45%) for pathways showing biphasic Michaelis-Menten kinetics (7-ethoxycoumarin and phenytoin).