Inhibition-based metabolic drug-drug interactions: predictions from in vitro data

Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic

Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

Predicting the Effect of Renal Function on Systemic Clearance: Is a simple scaling method sufficient?

PURPOSE

To employ a simple scaling method to predict systemic or oral clearance for drugs that are primarily renally cleared knowing the fraction eliminated in urine (f_e) and a patient's renal function relative to healthy controls (S_GFR).

METHODS

Observations evaluating drug clearance as a function of creatinine clearance for renally cleared drugs (f_e >0.3) were obtained from literature sources. The analysis comprised of 82 unique drugs from 124 studies including 31 drugs with replicate studies. A simple scaler for renal function was employed and compared to the linear regression of available data. For drugs in which replicate studies were available, the ability of the linear regression (Cl vs Cl_CR) from one pharmacokinetic study was used to predict observations from an assigned replicate and compared to the scaling approach.

RESULTS

For patients categorized as severe kidney disease (Cl_CR fixed at 20 ml/min), the scalar tended to over predict some observations, but 92% of the predictions were within 50 - 200% of the observed data. For drugs with available replicates, the scalar was as good or better in predicting the influence of Cl_CR on systemic clearance from a separate study when comparing against the linear regression approach.

CONCLUSION

A scaling approach to account for alterations in drug clearance appears to have its advantages and represents a simple and generalizable method for guiding dose adjustments in patients with decreased renal function for drugs that are renally cleared (f_e >0.3). In addition to its use in clinical practice, validation of this approach may have implications in facilitating more efficient drug development processes for designing dose-adjusted pharmacokinetic studies in patients with renal disease.

In vitro inhibitory effects of glucosamine, chondroitin and diacerein on human hepatic CYP2D6

OBJECTIVES

Glucosamine, chondroitin and diacerein are natural compounds commonly used in treating osteoarthritis. Their concomitant intake may trigger drug-natural product interactions. Cytochrome P450 (CYP) has been implicated in such interactions. Cytochrome P450 2D6 (CYP2D6) is a major hepatic CYP involved in metabolism of 25% of the clinical drugs. This study aimed to investigate the inhibitory effect of these antiarthritic compounds on CYP2D6.

METHODS

CYP2D6 was heterologously expressed in Escherichia coli. CYP2D6-antiarthritic compound interactions were studied using in vitro enzyme kinetics assay and molecular docking.

RESULTS

The high-performance liquid chromatography (HPLC)-based dextromethorphan O-demethylase assay was established as CYP2D6 marker. All glucosamines and chondroitins weakly inhibited CYP2D6 (IC₅₀ values >300 µM). Diacerein exhibited moderate inhibition with IC₅₀ and K _i values of 34.99 and 38.27 µM, respectively. Its major metabolite, rhein displayed stronger inhibition potencies (IC₅₀=26.22 μM and K _i =32.27 μM). Both compounds exhibited mixed-mode of inhibition. In silico molecular dockings further supported data from the in vitro study. From in vitro-in vivo extrapolation, rhein presented an area under the plasma concentration-time curve (AUC) ratio of 1.5, indicating low potential to cause in vivo inhibition.

CONCLUSIONS

Glucosamine, chondroitin and diacerein unlikely cause clinical interaction with the drug substrates of CYP2D6. Rhein, exhibits only low potential to cause in vivo inhibition.

In vitro inhibitory effects of glucosamine, chondroitin and diacerein on human hepatic CYP2D6

OBJECTIVES

Glucosamine, chondroitin and diacerein are natural compounds commonly used in treating osteoarthritis. Their concomitant intake may trigger drug-natural product interactions. Cytochrome P450 (CYP) has been implicated in such interactions. Cytochrome P450 2D6 (CYP2D6) is a major hepatic CYP involved in metabolism of 25% of the clinical drugs. This study aimed to investigate the inhibitory effect of these antiarthritic compounds on CYP2D6.

METHODS

CYP2D6 was heterologously expressed in Escherichia coli. CYP2D6-antiarthritic compound interactions were studied using in vitro enzyme kinetics assay and molecular docking.

RESULTS

The high-performance liquid chromatography (HPLC)-based dextromethorphan O-demethylase assay was established as CYP2D6 marker. All glucosamines and chondroitins weakly inhibited CYP2D6 (IC50 values >300 µM). Diacerein exhibited moderate inhibition with IC50 and K i values of 34.99 and 38.27 µM, respectively. Its major metabolite, rhein displayed stronger inhibition potencies (IC50=26.22 μM and K i =32.27 μM). Both compounds exhibited mixed-mode of inhibition. In silico molecular dockings further supported data from the in vitro study. From in vitro-in vivo extrapolation, rhein presented an area under the plasma concentration-time curve (AUC) ratio of 1.5, indicating low potential to cause in vivo inhibition.

CONCLUSIONS

Glucosamine, chondroitin and diacerein unlikely cause clinical interaction with the drug substrates of CYP2D6. Rhein, exhibits only low potential to cause in vivo inhibition.

Cytochrome P450 2C9-natural antiarthritic interactions: Evaluation of inhibition magnitude and prediction from in vitro data

Many dietary supplements are promoted to patients with osteoarthritis (OA) including the three naturally derived compounds, glucosamine, chondroitin and diacerein. Despite their wide spread use, research on interaction of these antiarthritic compounds with human hepatic cytochrome P450 (CYP) enzymes is limited. This study aimed to examine the modulatory effects of these compounds on CYP2C9, a major CYP isoform, using in vitro biochemical assay and in silico models. Utilizing valsartan hydroxylase assay as probe, all forms of glucosamine and chondroitin exhibited IC₅₀ values beyond 1000 μM, indicating very weak potential in inhibiting CYP2C9. In silico docking postulated no interaction with CYP2C9 for chondroitin and weak bonding for glucosamine. On the other hand, diacerein exhibited mixed-type inhibition with IC₅₀ value of 32.23 μM and K_i value of 30.80 μM, indicating moderately weak inhibition. Diacerein's main metabolite, rhein, demonstrated the same mode of inhibition as diacerein but stronger potency, with IC₅₀ of 6.08 μM and K_i of 1.16 μM. The docking of both compounds acquired lower CDOCKER interaction energy values, with interactions dominated by hydrogen and hydrophobic bondings. The ranking with respect to inhibition potency for the investigated compounds was generally the same in both in vitro enzyme assay and in silico modeling with order of potency being diacerein/rhein > various glucosamine/chondroitin forms. In vitro-in vivo extrapolation of inhibition kinetics (using 1 + [I]/K_i ratio) demonstrated negligible potential of diacerein to cause interaction in vivo, whereas rhein was predicted to cause in vivo interaction, suggesting potential interaction risk with the CYP2C9 drug substrates.

Simulation of Metabolic Drug-Drug Interactions Perpetrated by Fluvoxamine Using Hybridized Two-Compartment Hepatic Drug-Pool-Based Tube Modeling and Estimation of In Vivo Inhibition Constants

Co-administration of fluvoxamine (FLV) (perpetrator) and ramelteon (victim, high-clearance CYP1A2 substrate) reportedly showed a 130-fold increase in the area under blood-ramelteon-levels curve (AUCR), which is unpredictable by any method assuming the traditional well-stirred hepatic extraction (Eh ) model. Thus, in order to predict this drug interaction (DDI), a mathematical method that allows simulation of dynamic changes in blood victim levels in response to metabolic inhibition by a perpetrator, without the use of any specialized tools, was derived using hybridized two-compartment hepatic drug-pool-based tube modeling. Using this method, the ramelteon-victimized DDI could be simulated in comparison with other victim DDIs, assuming a consistent FLV dosing regimen. Despite large differences in AUCRs, CYP1A2 or CYP2C19 substrate-victimized DDIs resulted in equivalent inhibition constants (Ki , around 3 nM) and net enzymatic inhibitory activities calculated by eliminating hepatic availability increases for victims. Thus, the unusually large ramelteon DDI could be attributed to the Eh of ramelteon itself. This DDI risk could also be accurately predicted from Ki s estimated in the other CYP1A2 or CYP2C19-substrate interactions. Meanwhile, dynamic changes in blood perpetrator levels were demonstrated to have a small effect on DDI, thus suggesting the usefulness of a tube-based static method for DDI prediction.

Novel pre-clinical methodologies for pharmacokinetic drug-drug interaction studies: spotlight on "humanized" animal models

Poly-therapy is common due to co-occurrence of several ailments in patients, leading to the elevated possibility of drug-drug interactions (DDI). Pharmacokinetic DDI often accounts for severe adverse drug reactions in patients resulting in withdrawal of drug from the market. Hence, the prediction of DDI is necessary at pre-clinical stage of drug development. Several human tissue and cell line-based in vitro systems are routinely used for screening metabolic and transporter pathways of investigational drugs and for predicting their clinical DDI potentials. However, ample constraints are associated with the in vitro systems and sometimes in vitro-in vivo extrapolation (IVIVE) fail to assess the risk of DDI in clinic. In vitro-in vivo correlation model in animals combined with human in vitro studies may be helpful in better prediction of clinical outcome. Native animal models vary remarkably from humans in drug metabolizing enzymes and transporters, hence, the interpretation of results from animal DDI studies is difficult. With the advent of modern molecular biology and engineering tools, novel pre-clinical animal models, namely, knockout rat/mouse, transgenic rat/mouse with humanized drug metabolizing enzymes and/or transporters and chimeric rat/mouse with humanized liver are developed. These models nearly simulate human-like drug metabolism and help to validate the in vivo relevance of the in vitro human DDI data. This review briefly discusses the application of such novel pre-clinical models for screening various type of DDI along with their advantages and limitations.

Selective inhibition of cytochrome P450 2D6 by Sarpogrelate and its active metabolite, M-1, in human liver microsomes

The present study was performed to evaluate the in vitro inhibitory potential of sarpogrelate and its active metabolite, M-1, on the activities of nine human cytochrome (CYP) isoforms. Using a cocktail assay, the effects of sarpogrelate on nine CYP isoforms and M-1 were measured by specific marker reactions in human liver microsomes. Sarpogrelate potently and selectively inhibited CYP2D6-mediated dextromethorphan O-demethylation with an IC50 (Ki) value of 3.05 μM (1.24 μM), in a competitive manner. M-1 also markedly inhibited CYP2D6 activity; its inhibitory effect with an IC50 (Ki) value of 0.201 μM (0.120 μM) was more potent than that of sarpogrelate, and was similarly potent as quinidine (Ki, 0.129 μM), a well-known typical CYP2D6 inhibitor. In addition, sarpogrelate and M-1 strongly inhibited both CYP2D6-catalyzed bufuralol 1'-hydroxylation and metoprolol α-hydroxylation activities. However, sarpogrelate and M-1 showed no apparent inhibition of the other following eight CYPs: CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2E1, or CYP3A4/5. Upon 30-minute preincubation of human liver microsomes with sarpogrelate or M-1 in the presence of NADPH, no obvious shift in IC50 was observed in terms of inhibition of the nine CYP activities, suggesting that sarpogrelate and M-1 are not time-dependent inactivators. Sarpogrelate strongly inhibited the activity of CYP2D6 at clinically relevant concentrations in human liver microsomes. These observations suggest that sarpogrelate could have an effect on the metabolic clearance of drugs possessing CYP2D6-catalyzed metabolism as a major clearance pathway, thereby eliciting pharmacokinetic drug-drug interactions.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME

This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

In vitro approaches to investigate cytochrome P450 activities: update on current status and their applicability

INTRODUCTION

Cytochromes P450 (CYPs) play a central role in the Phase I metabolism of drugs and other xenobiotics. It is estimated that CYPs can metabolize up to two-thirds of drugs present in humans. Over the past two decades, there have been numerous advances in in vitro methodologies to characterize drug metabolism and interaction involving CYPs.

AREAS COVERED

This review focuses on the use of in vitro methodologies to examine CYPs' role in drug metabolism and interaction. There is an emphasis on their current development, applicability, advantages and limitations as well as the use of in silico approaches in complementing and supporting in vitro data. The article also highlights the challenges in extrapolating in vitro data to in vivo situations.

EXPERT OPINION

Advances in in vitro methodologies have been made such that data can be used for in vivo prediction with comfortable degree of confidence. Improved assay designs and analytical techniques have permitted development of miniaturized assay format and automated system with improved sensitivity and throughput capacity. High-quality experimental designs and scientifically rigorous assessment/validation protocols remain crucial in developing reliable and robust in vitro models. With continued progress made in the field, in vitro methodologies will continually be employed in evaluating CYP activities in pharmaceutical industries and laboratories.

Lack of a Clinically Significant Effect of Zonisamide on Phenytoin Steady-State Pharmacokinetics in Patients With Epilepsy

This study was designed to measure the effect of the addition of zonisamide on phenytoin pharmacokinetics under steady-state conditions in patients with epilepsy. Nineteen patients stabilized under phenytoin monotherapy were included in a 3-center, open-label, 1-way drug interaction trial. Zonisamide was gradually increased to 400 mg/day, taken twice daily. Three pharmacokinetic profiles were performed: on days -7 and -1, to assess pharmacokinetic parameters of oral phenytoin administered alone, and on day 35, after 14 days of zonisamide treatment, to evaluate the effect of zonisamide on phenytoin pharmacokinetics and to characterize zonisamide pharmacokinetics in the presence of phenytoin. Fourteen patients completed the study; the coadministration of zonisamide and phenytoin was safe and well tolerated. Zonisamide did not significantly affect the mean C(min), C(max), AUC(0-12), and CL/F of phenytoin measured before and after zonisamide administration. The pharmacokinetic measures of zonisamide in the presence of phenytoin were consistent with previous reports of induction of zonisamide metabolism by phenytoin.

Methods for the quantitative evaluation and prediction of CYP enzyme induction using human in vitro systems

IMPORTANCE OF THE FIELD

For successful drug development, it is important to investigate the potency of candidate drugs causing drug-drug interactions (DDI) during the early stages of development. The most common mechanisms of DDIs are the inhibition and induction of CYP enzymes. Therefore, it is important to develop co.mpounds with lower potencies for CYP enzyme induction.

AREAS COVERED IN THIS REVIEW

The aim of the present paper is to present an overview of the current knowledge of CYP induction mechanisms, particularly focusing on the transcriptional gene activation mediated by pregnane X receptor, aryl hydrocarbon receptor and constitutive androstane receptor. The adoptable options of in vitro assay methods for evaluating CYP induction are also summarized. Finally, we introduce a method for the quantitative prediction of CYP3A4 induction considering the turnover of CYP3A4 mRNA and protein in hepatocytes based on the data obtained from a reporter gene assay.

WHAT THE READER WILL GAIN

In order to predict in vivo CYP enzyme induction quantitatively based on in vitro information, an understanding of the physiological induction mechanisms and the features of each in vitro assay system is essential. We also present the estimation method of in vivo CYP induction potency of each compound based on the in vitro data which are routinely obtained but not necessarily utilized maximally in pharmaceutical companies.

TAKE HOME MESSAGE

It is desirable to select compounds with lower potencies for the inductive effect. For this purpose, an accurate prioritization procedure to evaluate the induction potency of each compound in a quantitative manner considering the pharmacologically effective concentration of each compound is necessary.

Impact of nonlinear midazolam pharmacokinetics on the magnitude of the midazolam-ketoconazole interaction in rats

Numerous groups have described the rat as an in vivo model for the assessment and prediction of drug-drug interactions (DDIs) in humans involving the inhibition of cytochrome P450 3A forms. Even for a well-established substrate-inhibitor pair like midazolam-ketoconazole, however, the magnitude of the DDI in rats (e.g. 1.5- to 5-fold) does not relate to what is observed clinically (e.g. 5- to 16-fold). Because nonlinear substrate pharmacokinetics (PK) may result in a weaker interaction, it was hypothesized that the lower magnitude of interaction observed in rats was due to the saturation of metabolic pathway(s) of midazolam at the doses used (10-20 mg/kg). Therefore, the inhibitory effects of ketoconazole were reevaluated at lower oral (1 and 5 mg/kg) and intravenous (IV) (1 mg/kg) doses of midazolam. In support of the hypothesis, oral exposure at 5 mg/kg dose of midazolam was 18-fold higher compared to that at 1 mg/kg. Furthermore, when the interaction was investigated at the lower midazolam dose (1 mg/kg), ketoconazole increased the IV and oral exposure of midazolam by 7-fold and 11-fold, respectively. A weaker DDI (1.5- to 1.8-fold) was observed at the higher oral midazolam dose. Collectively, these results suggest that the lower reported interaction in rats is likely due to saturation of midazolam clearance at the doses used. Therefore, when the rat is used as a DDI model to screen and differentiate compounds, or predict CYP3A inhibition in humans, it is important to use low doses of midazolam and ensure linear PK.

Optimizing pediatric dosing: a developmental pharmacologic approach

Many physiologic differences between children and adults can result in age-related differences in pharmacokinetics. Understanding the effects of age on bioavailability, volume of distribution, protein binding, hepatic metabolic isoenzymes, and renal elimination can provide insight into optimizing doses for pediatric patients. We performed a search of English-language literature using the MEDLINE database regarding age and pharmacokinetics (1979-July 2008). We then evaluated the literature with an emphasis on drugs with one primary elimination pathway, such as renal clearance or a pathway involving a single metabolic isoenzyme. Our mechanistic-based analysis revealed that children need weight-corrected doses that are substantially higher than adult doses for drugs that are metabolically eliminated solely by the specific cytochrome P450 (CYP) isoenzymes CYP1A2, CYP2C9, and CYP3A4. In contrast, weight-corrected doses for drugs eliminated by renal excretion or metabolism involving CYP2C19, CYP2D6, N-acetyltransferase 2, or uridine diphosphate glucuronosyltransferases are similar in children and adults. In children, bioavailability of drugs with high first-pass metabolism is decreased for drugs metabolized by CYP1A2, CYP2C9, and CYP3A4. Limited data suggest that by age 5 years, bioavailability of drugs affected by efflux transporters should be equivalent to that of adults. Using a pharmacokinetics-based approach, rational predictions can be made for the effects of age on drugs that undergo similar pathways of elimination, even when specific pharmacokinetic data are limited or unavailable.

Studying cytochrome P450 kinetics in drug metabolism

BACKGROUND

Determination of cytochrome P450 enzyme-mediated kinetics in vitro can be useful for predicting drug dosing and clearance in humans. Expressed P450s, human liver microsomes, human hepatocytes (both fresh and cryopreserved), and human liver slices are used to estimate K(m) and V(max) values for determination of intrinsic clearance of the drug for scale-up to predict in vivo clearance.

OBJECTIVE

To describe the advantages and disadvantages of the various in vitro systems used to estimate kinetic parameters for disposition of drugs and the various kinetic profiles that can be observed.

METHODS

A review of the literature was conducted to evaluate the utility of the various in vitro preparations, the methods for determining kinetic parameters and the types of kinetic profiles that may be observed.

RESULTS/CONCLUSIONS

The choice of in vitro system for determining kinetic parameters will depend on the objective of the studies, as each system has advantages and disadvantages. Kinetic parameter determinations must be carefully assessed to assure that the correct kinetic model is applied and the most accurate kinetic parameters are determined.

A comprehensive in vitro and in silico analysis of antibiotics that activate pregnane X receptor and induce CYP3A4 in liver and intestine

We have investigated several in silico and in vitro methods to improve our ability to predict potential drug interactions of antibiotics. Our focus was to identify those antibiotics that activate pregnane X receptor (PXR) and induce CYP3A4 in human hepatocytes and intestinal cells. Human PXR activation was screened using reporter assays in HepG2 cells, kinetic measurements of PXR activation were made in DPX-2 cells, and induction of CYP3A4 expression and activity was verified by quantitative polymerase chain reaction, immunoblotting, and testosterone 6beta-hydroxylation in primary human hepatocytes and LS180 cells. We found that in HepG2 cells CYP3A4 transcription was activated strongly (> 10-fold) by rifampin and troleandomycin; moderately (> or = 7-fold) by dicloxacillin, tetracycline, clindamycin, griseofulvin, and (> or = 4-fold) erythromycin; and weakly (> 2.4-fold) by nafcillin, cefaclor, sulfisoxazole, and (> 2-fold) cefadroxil and penicillin V. Similar although not identical results were obtained in DPX-2 cells. CYP3A4 mRNA and protein expression were induced by these antibiotics to differing extents in both liver and intestinal cells. CYP3A4 activity was significantly increased by rifampin (9.7-fold), nafcillin and dicloxacillin (5.9-fold), and weakly induced (2-fold) by tetracycline, sufisoxazole, troleandomycin, and clindamycin. Multiple pharmacophore models and docking indicated a good fit for dicloxacillin and nafcillin in PXR. These results suggest that in vitro and in silico methods can help to prioritize and identify antibiotics that are most likely to reduce exposures of medications (such as oral contraceptive agents) which interact with enzymes and transporters regulated by PXR. In summary, nafcillin, dicloxacillin, cephradine, tetracycline, sulfixoxazole, erythromycin, clindamycin, and griseofulvin exhibit a clear propensity to induce CYP3A4 and warrant further clinical investigation.

Integrated in vitro analysis for the in vivo prediction of cytochrome P450-mediated drug-drug interactions

Unbound IC(50) (IC(50,u)) values of 15 drugs were determined in eight recombinantly expressed human cytochromes P450 (P450s) and human hepatocytes, and the data were used to simulate clinical area under the plasma concentration-time curve changes (deltaAUC) on coadministration with prototypic CYP2D6 substrates. Significant differences in IC(50,u) values between enzyme sources were observed for quinidine (0.02 microM in recombinant CYP2D6 versus 0.5 microM in hepatocytes) and propafenone (0.02 versus 4.1 microM). The relative contribution of individual P450s toward the oxidative metabolism of clinical probes desipramine, imipramine, tolterodine, propranolol, and metoprolol was estimated via determinations of intrinsic clearance using recombinant P450s (rP450s). Simulated deltaAUC were compared with those observed in vivo via the ratios of unbound inhibitor concentration at the entrance to the liver to inhibition constants determined against rP450s ([I](in,u)/K(i)) and incorporating parallel substrate elimination pathways. For this dataset, there were 20% false negatives (observed deltaAUC >or= 2, predicted deltaAUC < 2), 77% correct predictions, and 3% false positives. Thus, the [I](in,u)/K(i) approach appears relatively successful at estimating the degree of clinical interactions and can be incorporated into drug discovery strategies. Using a Simcyp ADME (absorption, metabolism, distribution, elimination) simulator (Simcyp Ltd., Sheffield, UK), there were 3% false negatives, 94% correct simulations, and 3% false positives. False-negative predictions were rationalized as a result of mechanism-based inhibition, production of inhibitory metabolites, and/or hepatic uptake. Integrating inhibition and reaction phenotyping data from automated rP450 screens have shown applicability to predict the occurrence and degree of in vivo drug-drug interactions, and such data may identify the clinical consequences for candidate drugs as both "perpetrators" and "victims" of P450-mediated interactions.

Tolfenamic acid is a potent CYP1A2 inhibitor in vitro but does not interact in vivo: correction for protein binding is needed for data interpretation

OBJECTIVE

Our aim was to correlate the in vitro and in vivo CYP1A2 inhibition potential of tolfenamic acid, an NSAID highly (99.7%) bound to plasma proteins, to study the significance of protein binding of inhibitor in metabolic drug interactions.

METHODS

The effect of tolfenamic acid on CYP1A2 (phenacetin O-deethylation) was studied using human liver microsomes, with and without albumin (0-10 mg/ml). In a randomized, crossover study, 10 volunteers took 200 mg tolfenamic acid or placebo t.i.d. for 3 days. On day 2, a caffeine test was performed. On day 3, each ingested 4 mg of the CYP1A2 substrate tizanidine. Plasma tizanidine, its metabolites (M) and tolfenamic acid, and pharmacodynamic variables were measured.

RESULTS

Tolfenamic acid strongly inhibited phenacetin-O-deethylation in vitro (IC(50) 1.8 microM without albumin). Albumin decreased its inhibitory effect in a concentration-dependent manner; the IC(50) exceeded 100 microM with 10 mg/ml of albumin. Tolfenamic acid had no effect on the area under the concentration-time curve (AUC(0-oo)), peak concentration, time of peak concentration or half-life of tizanidine or M-3; only the AUC(0-oo) of secondary metabolite M-4 was slightly decreased (13%, P = 0.004). The caffeine test and the pharmacodynamic effects of tizanidine were unchanged.

CONCLUSIONS

Tolfenamic acid potently inhibits CYP1A2 in vitro when studied without albumin, but not in vivo. This apparent discrepancy is due to the high protein binding of tolfenamic acid. To avoid overestimation of the interaction potential, the inhibitory effect of highly albumin-bound compounds should also be studied in vitro with albumin, or their exact unbound plasma concentration should be used in predictions.

An Interaction Study Between the New Antiepileptic and CNS Drug Carisbamate (RWJ-333369) and Lamotrigine and Valproic Acid

PURPOSE

To characterize possible pharmacokinetic interactions between the new antiepileptic drug carisbamate (RWJ-333369) and valproic acid (VPA) or lamotrigine (LTG) following multiple dosing in healthy subjects.

METHODS

Two open-label, sequential-design studies were conducted in 24 healthy adults. In Study 1, subjects received carisbamate alone (5 days 250 mg q12h; 5 days 500 mg q12h), then VPA alone (7 days 300 mg q12h; 7 days 500 mg q12h), and then a combination of VPA (500 mg q12h) and carisbamate (5 days 250 mg q12h; 5 days 500 mg q12h). In Study 2, subjects received carisbamate alone as in Study 1, then LTG alone (14 days 25 mg q12h; 14 days 50 mg q12h), and then combination of LTG (50 mg q12h) and carisbamate (3 days 250 mg q12h; 14 days 500 mg q12h).

RESULTS

Coadministration of VPA or LTG had minimal effect on carisbamate mean C(max) and AUC(ss) values. Mean VPA-C(max) and AUC(ss) values were approximately 15% lower when given concomitantly with carisbamate. However, the 90% confidence intervals (CIs) for the C(max) and AUC(ss) ratio with/without carisbamate were within the 80-125% equivalence range, C(max) 82-89%; AUC(ss) 81-88%. Mean LTG C(max) and AUC(ss) values were approximately 20% lower when given concomitantly with carisbamate. The 90% CIs with and without carisbamate for LTG C(max) and AUC(ss) were 79-86% and 75-81%, respectively. This modest change is not considered clinically significant.

CONCLUSIONS

There were no clinically significant interactions between carisbamate and VPA or LTG. Concomitant administration of carisbamate with VPA or LTG was generally safe and well tolerated.

A test for measuring the effects of enzyme inactivation

In the single-enzyme, single-substrate reaction with non-mechanism-based enzyme inactivation, the formation of the product and inactivation of the enzyme occur independently. For this reaction, we show that the steady-state hypothesis is applicable even when degradation of the enzyme occurs. An equation for the rate of product formation has been derived and it shows Michaelis-Menten kinetics with an apparent Michaelis-Menten constant K(M)(app)=K(M)+K(delta) where K(delta) is the enzyme inactivation constant. Use of a Lineweaver-Burk plot yields values for K(M)(app), which can be used to estimate K(delta) and, consequently, the degree of enzyme inactivation in a particular experiment. We employ this methodology to estimate the inactivation constant for the arsenate reductase catalyzed production of arsenite with appreciable enzyme inactivation.

Methods for Predicting Human Drug Metabolism

Drug metabolism information is a necessary component of drug discovery and development. The key issues in drug metabolism include identifying: the enzyme(s) involved, the site(s) of metabolism, the resulting metabolite(s), and the rate of metabolism. Methods for predicting human drug metabolism from in vitro and computational methodologies and determining relationships between the structure and metabolic activity of molecules are also critically important for understanding potential drug interactions and toxicity. There are numerous experimental and computational approaches that have been developed in order to predict human metabolism which have their own limitations. It is apparent that few of the computational tools for metabolism prediction alone provide the major integrated functions needed to assist in drug discovery. Similarly the different in vitro methods for human drug metabolism themselves have implicit limitations. The utilization of these methods for pharmaceutical and other applications as well as their integration is discussed as it is likely that hybrid methods will provide the most success.

Quantitative prediction of in vivo inhibitory interactions involving glucuronidated drugs from in vitro data: the effect of fluconazole on zidovudine glucuronidation

AIMS

Using the fluconazole-zidovudine (AZT) interaction as a model, to determine whether inhibition of UDP-glucuronosyltransferase (UGT) catalysed drug metabolism in vivo could be predicted quantitatively from in vitro kinetic data generated in the presence and absence bovine serum albumin (BSA).

METHODS

Kinetic constants for AZT glucuronidation were generated using human liver microsomes (HLM) and recombinant UGT2B7, the principal enzyme responsible for AZT glucuronidation, as the enzyme sources with and without fluconazole. K(i) values were used to estimate the decrease in AZT clearance in vivo.

RESULTS

Addition of BSA (2%) to incubations decreased the K(m) values for AZT glucuronidation by 85-90% for the HLM (923 +/- 357 to 91 +/- 9 microm) and UGT2B7 (478-70 microm) catalysed reactions, with little effect on V(max). Fluconazole, which was shown to be a selective inhibitor of UGT2B7, competitively inhibited AZT glucuronidation by HLM and UGT2B7. Like the K(m), BSA caused an 87% reduction in the K(i) for fluconazole inhibition of AZT glucuronidation by HLM (1133 +/- 403 to 145 +/- 36 microm) and UGT2B7 (529 to 73 microm). K(i) values determined for fluconazole using HLM and UGT2B7 in the presence (but not absence) of BSA predicted an interaction in vivo. The predicted magnitude of the interaction ranged from 41% to 217% of the reported AUC increase in patients, depending on the value of the in vivo fluconazole concentration employed in calculations.

CONCLUSIONS

K(i) values determined under certain experimental conditions may quantitatively predict inhibition of UGT catalysed drug glucuronidation in vivo.

Uptake and intracellular binding of lipophilic amine drugs by isolated rat hepatocytes and implications for prediction of in vivo metabolic clearance

The hepatic uptake of imipramine and propranolol was investigated after incubation with isolated rat hepatocytes over a wide concentration range (0.04-400 microM). The cell-to-medium concentration ratio (K(p)) was concentration-dependent and could be described using a two-site binding model incorporating a high affinity/low capacity site and a linear component for a site which was apparently not saturated. Maximum (at 0.04 microM) and minimum K(p) values (at 400 microM) were 360 and 280, and 110 and 70 for imipramine and propranolol, respectively. During these incubations, metabolism was inhibited using aminobenzotriazole (an irreversible inhibitor of cytochrome P450). Pretreatment of cells either by freeze-thawing or with saponin (which permeabilizes the plasma membrane) eliminated the saturable process. The saturable uptake process of imipramine was also inhibited by 18 other lipophilic amine drugs (including propranolol). This uptake component may involve membrane transporter(s), whereas the nonsaturable component probably represents partition into the phospholipid component of membranes. Propranolol was further investigated to determine the impact of high K(p) values on hepatocellular clearance. The area under the curve for propranolol concentrations in the total incubate (medium including the cells) from the depletiontime profile was substantially greater than the corresponding area under the curve for the drug concentration in the extracellular medium, and this difference approximated the nonsaturable uptake component. It is concluded that the clearance of propranolol in isolated hepatocytes is not rate-limited by hepatic uptake and is directly proportional to unbound drug concentration, being independent of the higher K(p) value.

The pharmacokinetics and interactions of new antiepileptic drugs: an overview

In the past decade 10 new antiepileptic drugs (AEDs)have been introduced: felbamate, gabapentin, lamotrigine, levetiracetem, oxcarbazepine, pregabalin, tiagabine, topiramate, vigabatrin,and zonisamide. The pharmacokinetics (PK) of these new AEDs as well as their potential for drug interactions are reviewed in this article. In general, new AEDs have better PK profiles and are less involved in drug interactions than the 4 established AEDs: phenobarbital,phenytoin, carbamazepine, and valproic acid. However, in spite of the large therapeutic arsenal of old and new AEDs, about 30% of epileptic patients are still not seizure-free, and thus, there is a substantial need to develop new AEDs.

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.

Stochastic prediction of CYP3A-mediated inhibition of midazolam clearance by ketoconazole

Conventional methods to forecast CYP3A-mediated drug-drug interactions have not employed stochastic approaches that integrate pharmacokinetic (PK) variability and relevant covariates to predict inhibition in terms of probability and uncertainty. Empirical approaches to predict the extent of inhibition may not account for nonlinear or non-steady-state conditions, such as first-pass effects or accumulation of inhibitor concentration with multiple dosing. A physiologically based PK model was developed to predict the inhibition of CYP3A by ketoconazole (KTZ), using midazolam (MDZ) as the substrate. The model integrated PK models of MDZ and KTZ, in vitro inhibition kinetics of KTZ, and the variability and uncertainty associated with these parameters. This model predicted the time- and dose-dependent inhibitory effect of KTZ on MDZ oral clearance. The predictive performance of the model was validated using the results of five published KTZ-MDZ studies. The model improves the accuracy of predicting the inhibitory effect of increasing KTZ dosing on MDZ PK by incorporating a saturable KTZ efflux from the site of enzyme inhibition in the liver. The results of simulations using the model supported the KTZ dose of 400 mg once daily as the optimal regimen to achieve maximum inhibition by KTZ. Sensitivity analyses revealed that the most influential variable on the prediction of inhibition was the fractional clearance of MDZ mediated by CYP3A. The model may be used prospectively to improve the quantitative prediction of CYP3A inhibition and aid the optimization of study designs for CYP3A-mediated drug-drug interaction studies in drug development.

Identification of enzymes involved in phase I metabolism of ciclesonide by human liver microsomes

Ciclesonide, a novel inhaled corticosteroid, is currently being developed for the treatment of asthma. Here, the enzymes catalysing the human hepatic metabolism of ciclesonide were investigated. When incubated with human liver microsomes (HLM), [14C]ciclesonide was first metabolised to the active metabolite M1 (des-isobutyryl-ciclesonide, des-CIC) and to at least two additional metabolites, M2 and M3. M3 comprises a 'family' of structurally similar metabolites that are inactive. 16-Hydroxyprednisolone was also formed in microsomal incubations of [14C]des-CIC, but at approximately one-tenth the amount of both M2 and M3. bis-p-Nitrophenylphosphate and SKF 525-A respectively inhibited des-CIC formation from [14C]ciclesonide by 82% and 49% and M2/M3 formation by 82-84% and 87-89%. Regression analysis showed significant negative correlations (r = -0.96, -0.79 and -0.71, respectively) of M2 formation with CYP3A4/5, CYP2B6 and CYP2C8 activities; M3 formation significantly correlated with CYP4A9/11 (r = 0.47). Troleandomycin and diethyldithiocarbamate inhibited M2 and M3 formation by 85% and 45%, respectively. Sulphaphenazole and quinidine had no inhibitory effects. CYP3A4 Supersomes catalysed notable formation of both M2 and M3 from [14C]des-CIC; CYP2C8 and CYP2D6, but not CYP4A11 formed smaller amounts. It is concluded that the human hepatic metabolism of ciclesonide is primarily catalysed by one or more esterases and, subsequently, by CYP3A4.

Pregnancy-induced changes in pharmacokinetics: a mechanistic-based approach

Observational studies have documented that women take a variety of medications during pregnancy. It is well known that pregnancy can induce changes in the plasma concentrations of some drugs. The use of mechanistic-based approaches to drug interactions has significantly increased our ability to predict clinically significant drug interactions and improve clinical care. This same method can also be used to improve our understanding regarding the effect of pregnancy on pharmacokinetics of drugs. Limited studies suggest bioavailability of drugs is not altered during pregnancy. Increased plasma volume and protein binding changes can alter the apparent volume of distribution (Vd) of drugs. Through changes in Vd and clearance, pregnancy can cause increases or decreases in the terminal elimination half-life of drugs. Depending on whether a drug is excreted unchanged by the kidneys or which metabolic isoenzyme is involved in the metabolism of a drug can determine whether or not a change in dosage is needed during pregnancy. The renal excretion of unchanged drugs is increased during pregnancy. The metabolism of drugs catalysed by select cytochrome P450 (CYP) isoenzymes (i.e. CYP3A4, CYP2D6 and CYP2C9) and uridine diphosphate glucuronosyltransferase (UGT) isoenzymes (i.e. UGT1A4 and UGT2B7) are increased during pregnancy. Dosages of drugs predominantly metabolised by these isoenzymes or excreted by the kidneys unchanged may need to be increased during pregnancy in order to avoid loss of efficacy. In contrast, CYP1A2 and CYP2C19 activity is decreased during pregnancy, suggesting that dosage reductions may be needed to minimise potential toxicity of their substrates. There are limitations to the available data. This analysis is based primarily on observational studies, many including small numbers of women. For some isoenzymes, the effect of pregnancy on only one drug has been evaluated. The full-time course of pharmacokinetic changes during pregnancy is often not studied. The effect of pregnancy on transport proteins is unknown. Drugs eliminated by non-CYP or non-UGT pathways or multiple pathways will need to be evaluated individually. In conclusion, by evaluating the pharmacokinetic data of a variety of drugs during pregnancy and using a mechanistic-based approach, we can start to predict the effect of pregnancy for a large number of clinically used drugs. However, because of the limitations, more clinical, evidence-based studies are needed to fully elucidate the effects of pregnancy on the pharmacokinetics of drugs.

Predicting in vivo drug interactions from in vitro drug discovery data

In vitro screening for drugs that inhibit cytochrome P450 enzymes is well established as a means for predicting potential metabolism-mediated drug interactions in vivo. Given that these predictions are based on enzyme kinetic parameters observed from in vitro experiments, the miscalculation of the inhibitory potency of a compound can lead to an inaccurate prediction of an in vivo drug interaction, potentially precluding a safe drug from advancing in development or allowing a potent inhibitor to 'slip' into the patient population. Here, we describe the principles underlying the generation of in vitro drug metabolism data and highlight commonly encountered uncertainties and sources of bias and error that can affect extrapolation of drug-drug interaction information to the clinical setting.

Principles: mechanisms and modeling of synergism in cellular responses

Cells can be considered as integrators of simultaneous stimuli, in which cross-talk between transduction pathways can eventually produce responses that are significantly different from simply additive responses. Synergism represents an efficient means of increasing the amplitude of cellular responses induced by low levels of stimulation. Recently, several kinetic and physicochemical models have been developed to describe and predict synergistic responses. In this article, the mechanisms that control the magnitude and timing of cellular synergism are discussed. We suggest that the analysis of theoretical models could enable a general prediction of synergism despite the presence of signal-specific synergistic responses. In addition, application of the proposed concepts should aid understanding of the wide occurrence of synergism induced by interacting transduction pathways in multi-drug clinical treatment.

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.

In vitro inhibition of UDP glucuronosyltransferases by atazanavir and other HIV protease inhibitors and the relationship of this property to in vivo bilirubin glucuronidation

Several human immunodeficiency virus (HIV) protease inhibitors, including atazanavir, indinavir, lopinavir, nelfinavir, ritonavir, and saquinavir, were tested for their potential to inhibit uridine 5'-diphospho-glucuronosyltransferase (UGT) activity. Experiments were performed with human cDNA-expressed enzymes (UGT1A1, 1A3, 1A4, 1A6, 1A9, and 2B7) as well as human liver microsomes. All of the protease inhibitors tested were inhibitors of UGT1A1, UGT1A3, and UGT1A4 with IC(50) values that ranged from 2 to 87 microM. The IC50 values found for all compounds for UGT1A6, 1A9, and 2B7 were >100 microM. The inhibition (IC50) of UGT1A1 was similar when tested against the human cDNA-expressed enzyme or human liver microsomes for atazanavir, indinavir, and saquinavir (2.4, 87, and 7.3 microM versus 2.5, 68, and 5.0 microM, respectively). By analysis of the double-reciprocal plots of bilirubin glucuronidation activities at different bilirubin concentrations in the presence of fixed concentrations of inhibitors, the UGT1A1 inhibition by atazanavir and indinavir was demonstrated to follow a linear mixed-type inhibition mechanism (Ki = 1.9 and 47.9 microM, respectively). These results suggest that a direct inhibition of UGT1A1-mediated bilirubin glucuronidation may provide a mechanism for the reversible hyperbilirubinemia associated with administration of atazanavir as well as indinavir. In vitro-in vivo scaling with [I]/Ki predicts that atazanavir and indinavir are more likely to induce hyperbilirubinemia than other HIV protease inhibitors studied when a free Cmax drug concentration was used. Our current study provides a unique example of in vitro-in vivo correlation for an endogenous UGT-mediated metabolic pathway.

Selective inhibition of human cytochrome P4502C8 by montelukast

The leukotriene receptor antagonist montelukast was examined for its inhibition of the human drug-metabolizing enzyme cytochrome P4502C8 (CYP2C8). Montelukast was demonstrated to be a potent inhibitor of CYP2C8-catalyzed amodiaquine N-deethylase, rosiglitazone N-demethylase, and paclitaxel 6alpha-hydroxylase in human liver microsomes. Inhibition was also observed when the reaction was catalyzed by recombinant heterologously expressed CYP2C8. The mechanism of inhibition was competitive, with K(i) values ranging from 0.0092 to 0.15 microM. Inhibition potency was highly dependent on the microsomal protein concentration. Increasing the microsomal protein concentration by 80-fold yielded a 100-fold decrease in inhibition potency. Preincubation of montelukast with human liver microsomes and NADPH did not alter the inhibition potency, suggesting that montelukast is not a mechanism-based inactivator. Montelukast was a selective inhibitor for human CYP2C8; inhibition of other human cytochrome P450 enzymes was substantially less. These in vitro data support the use of montelukast as a selective CYP2C8 inhibitor that could be used to determine the contribution of this enzyme to drug metabolism reactions. These data also raise the possibility that montelukast could have an effect on the metabolic clearance of drugs possessing CYP2C8-catalyzed metabolism as a major clearance pathway, thereby eliciting pharmacokinetic drug-drug interactions.

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.

VALIDATED ASSAYS FOR HUMAN CYTOCHROME P450 ACTIVITIES

The measurement of the effect of new chemical entities on human cytochrome P450 marker activities using in vitro experimentation represents an important experimental approach in drug development. In vitro drug interaction data can be used in guiding the design of clinical drug interaction studies, or, when no effect is observed in vitro, the data can be used in place of an in vivo study to claim that no interaction will occur in vivo. To make such a claim, it must be assured that the in vitro experiments are performed with absolute confidence in the methods used and data obtained. To meet this need, 12 semiautomated assays for human P450 marker substrate activities have been developed and validated using approaches described in the GLP (good laboratory practices) as per the code of U.S. Federal Regulations. The assays that were validated are: phenacetin O-deethylase (CYP1A2), coumarin 7-hydroxylase (CYP2A6), bupropion hydroxylase (CYP2B6), amodiaquine N-deethylase (CYP2C8), diclofenac 4'-hydroxylase and tolbutamide methylhydroxylase (CYP2C9), (S)-mephenytoin 4'-hydroxylase (CYP2C19), dextromethorphan O-demethylase (CYP2D6), chlorzoxazone 6-hydroxylase (CYP2E1), felodipine dehydrogenase, testosterone 6 beta-hydroxylase, and midazolam 1'-hydroxylase (CYP3A4 and CYP3A5). High-pressure liquid chromatography-tandem mass spectrometry, using stable isotope-labeled internal standards, has been applied as the analytical method. This analytical approach, through its high sensitivity and selectivity, has permitted the use of very low incubation concentrations of microsomal protein (0.01-0.2 mg/ml). Analytical assay accuracy and precision values were excellent. Enzyme kinetic and inhibition parameters obtained using these methods demonstrated high precision and were within the range of values previously reported in the scientific literature. These methods should prove useful in the routine assessments of the potential for new drug candidates to elicit pharmacokinetic drug interactions via inhibition of cytochrome P450 activities.

Potent inhibition of human liver aldehyde oxidase by raloxifene

The selective estrogen receptor modulator, raloxifene, has been demonstrated as a potent uncompetitive inhibitor of human liver aldehyde oxidase-catalyzed oxidation of phthalazine, vanillin, and nicotine-Delta1'(5')-iminium ion, with K(i) values of 0.87 to 1.4 nM. Inhibition was not time-dependent. Raloxifene has also been shown to be a noncompetitive inhibitor of an aldehyde oxidase-catalyzed reduction reaction of a hydroxamic acid-containing compound, with a K(i) of 51 nM. However, raloxifene had only small effects on xanthine oxidase, an enzyme related to aldehyde oxidase. In addition, several other compounds of the same therapeutic class as raloxifene were examined for their potential to inhibit aldehyde oxidase. However, none were as potent as raloxifene, since IC(50) values were orders of magnitude higher and ranged from 0.29 to 57 micro M. In an examination of analogs of raloxifene, it was shown that the bisphenol structure with a hydrophobic group on the 3-position of the benzthiophene ring system was the most important element that imparts inhibitory potency. The relevance of these data to the mechanistic understanding of aldehyde oxidase catalysis, as well as to the potential for raloxifene to cause drug interactions with agents for which aldehyde oxidase-mediated metabolism is important, such as zaleplon or famciclovir, is discussed.

In vitro drug interactions of cytochrome p450: an evaluation of fluorogenic to conventional substrates

Clinically observed drug interactions with cytochrome p450 (p450) enzymes have increased the need to assess drug interactions of new chemical entities early in the discovery process. To meet this need, fluorogenic substrates have been commercialized. However, only limited evaluations of their utility and comparisons to drug probes have been reported. This study examines the correlation between IC50 values obtained with fluorogenic and conventional drug probes for structurally diverse inhibitors of the five major human p450 isoforms. In general, correlations are weak, with significant numbers of compounds being missed as inhibitors by either probe. For p450s 1A2, 2C9, and 2C19, correlation coefficients were above 0.6 with slopes that ranged from 1.5 to 4.2. However, for p450s 1A2 and 2C9, about 20% of compounds were not included because an IC50 value could not be determined with one of the two probes. CYP 2C19 had the highest correlation (correlation coefficient 0.84), with a slope of 2.0 and less than 5% of compounds excluded. CYP 2D6 showed a good correlation for IC50 values less than 10 microM. However, at higher IC50 values, a high degree of scatter was observed. CYP 3A4 had the weakest correlation, and a large number of compounds were excluded with the fluorogenic probe. Overall, the study shows the care needed when selecting fluorogenic probes and the caution needed when results with fluorogenic probes are used to drive structure-activity relationships with respect to drug interactions.

Comparison of in vitro and in vivo inhibition potencies of fluvoxamine toward CYP2C19

A previous study suggested that fluvoxamine inhibition potency toward CYP1A2 is 10 times greater in vivo than in vitro. The present study was designed to determine whether the same gap exists for CYP2C19, another isozyme inhibited by fluvoxamine. In vitro studies examined the effect of nonspecific binding on the determination of inhibition constant (K(i)) values of fluvoxamine toward CYP2C19 in human liver microsomes and in a cDNA-expressed microsomal (Supersomes) system using (S)-mephenytoin as a CYP2C19 probe. K(i) values based on total added fluvoxamine concentration (K(i,total)) and unbound fluvoxamine concentration (K(i,ub)) were calculated, and interindividual variability in K(i) values was examined in six nonfatty livers. K(i,total) values varied with microsomal protein concentration, whereas the corresponding K(i,ub) values were within a narrow range (70-80 nM). In vivo inhibition constants (K(i)iv) were obtained from a study of the disposition of a single oral dose (100 mg) of the CYP2C19 probe (S)-mephenytoin in 12 healthy volunteers receiving fluvoxamine at 0, 37.5, 62.6, and 87.5 mg/day to steady state. In this population, the ratio of (S)-4-hydroxy-mephenytoin formation clearances (uninhibited/inhibited) was positively correlated with fluvoxamine average steady-state concentration with an intercept of 0.85 (r(2) = 0.88, p < 0.001). The mean (+/-S.D.) values of K(i)iv based on total and unbound plasma concentrations were 13.5 +/- 5.6 and 1.9 +/- 1.1 nM, respectively. Comparison of in vitro and in vivo K(i) values, based on unbound fluvoxamine concentrations, suggests that fluvoxamine inhibition potency is roughly 40 times greater in vivo than in vitro.

Assessment of the contributions of CYP3A4 and CYP3A5 in the metabolism of the antipsychotic agent haloperidol to its potentially neurotoxic pyridinium metabolite and effect of antidepressants on the bioactivation pathway

As a plausible explanation for the large interindividual variability in the pharmacokinetics of the neuroleptic agent haloperidol, the contributions of CYP3A isozymes (CYP3A4 and the polymorphic CYP3A5) predominantly involved in haloperidol bioactivation to the neurotoxic pyridinium species 4-(4-Chlorophenyl)-1-[4-(4-fluorophenyl)-4-oxobutyl]-pyridinium (HPP(+)) were assessed in human liver microsomes and heterologously expressed enzymes. Based on recent reports on drug-drug interactions between haloperidol and antidepressants including selective serotonin reuptake inhibitors, the inhibitory effects of antidepressants on the CYP3A4/5-mediated haloperidol bioactivation were also evaluated. HPP(+) formation followed Michaelis-Menten kinetics in microsomes, recombinant CYP3A4, and CYP3A5 with K(m) values of 24.4 +/- 8.9 microM, 18.3 +/- 4.9 microM, and 200.2 +/- 47.6 microM, respectively, and V(max) values of 157.6 +/- 13.2 pmol/min/mg of protein, 10.4 +/- 0.6 pmol/min/pmol P450, and 5.16 +/- 0.6 pmol/min/pmol P450, respectively. The similarity in K(m) values between human liver microsomal and recombinant CYP3A4 incubations suggests that polymorphic CYP3A5 may not be an important genetic contributor to the interindividual variability in CYP3A-mediated haloperidol clearance pathways. Besides HPP(+), a novel 4-fluorophenyl-ring-hydroxylated metabolite of haloperidol in microsomes/CYP3A enzymes was also detected. Its formation was consistent with previous reports on the detection of O-sulfate and -glucuronide conjugates of a fluorophenyl ring-hydroxylated metabolite of haloperidol in human urine. Finally, all antidepressants except buspirone inhibited the CYP3A4/5-catalyzed oxidation of haloperidol to HPP(+) in a concentration-dependent manner. Based on the estimated IC(50) values for inhibition of HPP(+) formation in microsomes, the antidepressants were ranked in the following order: fluoxetine, nefazodone, norfluoxetine, trazodone, and fluvoxamine. These inhibition results suggest that clinically observed drug-drug interactions between haloperidol and antidepressants may arise via the attenuation of CYP3A4/5-mediated 4-(4-chlorophenyl)-1-[4-(4-fluorophenyl)-4-oxobutyl]-4-piperidinol biotransformation pathways.