Cytochrome P450 reaction-phenotyping: an industrial perspective

Positioning Enzyme- and Transporter-Based Precipitant Drug-Drug Interaction Studies in Drug Design

In vitro assessment of the potential of compounds to affect drug metabolizing enzymes and transporters and perpetrate drug-drug interactions (DDIs) is a common practice in drug research. For the development phase, regulators define an exhaustive list of enzymes and transporters to consider, but DDIs associated with many of these are minor and can be well-managed in the clinic; thus, progression of drug candidates that address unmet medical needs should not be curtailed due to this property. However, some enzymes and transporters are very important in drug disposition, so it is important to avoid/reduce inhibition or induction of these through drug design. Herein, simplified criteria and methodologies amenable to high-throughput screening are defined to enable drug design to address DDI risk. A strategy is proposed that focuses on the most important enzymes and transporters: namely, cytochrome P450 (CYP) 3A4, CYP2C9, and CYP2D6, organic anion transporting polypeptide (OATP) 1B1, and breast cancer resistant protein (BCRP).

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.

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Challenges and Opportunities for In Vitro-In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Underestimation of aldehyde oxidase (AO)-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45%-57% within twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fmAO In conclusion, the study provides the most robust system-specific empirical scaling factors to date as a pragmatic approach for the prediction of in vivo CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds

INTRODUCTION

Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recently been developed to address the gaps in the measurement of intrinsic clearance, identification of metabolites, and reaction phenotyping of low clearance compounds.

AREAS COVERED

The new methodologies of low clearance measurements are discussed, including the hepatocyte relay, HepatoPac®, HμREL®, and spheroid systems. In addition, metabolite formation rate determination and in vivo allometric scaling approaches are covered as alternative methods for low clearance measurements. With these new methods, measurement of ~ 20-fold lower limit of intrinsic clearance can be achieved. The advantages and limitations of each approach are highlighted.

EXPERT OPINION

Although several novel methods have been developed in recent years to address the challenges of low clearance, these assays tend to be time and labor intensive and costly. Future innovations focusing on developing systems with high enzymatic activities, ultra-sensitive universal quantifiable detectors, and artificial intelligence will further enhance our ability to explore the low clearance space.

Defining the Selectivity of Chemical Inhibitors Used for Cytochrome P450 Reaction Phenotyping: Overcoming Selectivity Limitations with a Six-Parameter Inhibition Curve-Fitting Approach

The utility of chemical inhibitors in cytochrome P450 (CYP) reaction phenotyping is highly dependent on their selectivity and potency for their target CYP isoforms. In the present study, seventeen inhibitors of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5 commonly used in reaction phenotyping were evaluated for their cross-enzyme selectivity in pooled human liver microsomes. The data were evaluated using a statistical desirability analysis to identify (1) inhibitors of superior selectivity for reaction phenotyping and (2) optimal concentrations for each. Among the inhibitors evaluated, α-naphthoflavone, furafylline, sulfaphenazole, tienilic acid, N-benzylnirvanol, and quinidine were most selective, such that their respective target enzymes were inhibited by ~95% without inhibiting any other CYP enzyme by more than 10%. Other commonly employed inhibitors, such as ketoconazole and montelukast, among others, were of insufficient selectivity to yield a concentration that could adequately inhibit their target enzymes without affecting other CYP enzymes. To overcome these shortcomings, an experimental design was developed wherein dose response data from a densely sampled multi-concentration inhibition curve are analyzed by a six-parameter inhibition curve function, allowing accounting of the inhibition of off-target CYP isoforms inhibition and more reliable determination of maximum targeted enzyme inhibition. The approach was exemplified using rosiglitazone N-demethylation, catalyzed by both CYP2C8 and 3A4, and was able to discern the off-target inhibition by ketoconazole and montelukast from the inhibition of the targeted enzyme. This methodology yields more accurate estimates of CYP contributions in reaction phenotyping. Significance Statement Isoform-selective chemical inhibitors are important tools for identifying and quantifying enzyme contributions as part of a CYP reaction phenotyping assessment for projecting drug-drug interactions. However, currently employed practices fail to adequately compensate for shortcomings in inhibitor selectivity and the resulting confounding impact on estimates of the CYP enzyme contribution to drug clearance. In this report, we describe a detailed IC50 study design with 6-parameter modeling approach that yields more accurate estimates of enzyme contribution.

Mitigated Oxidative Stress and Cognitive Impairments in Transient Global Ischemia using Niosomal Selegiline-NBP delivery

Stroke is the most common reason for adult disabilities and the second ground for death worldwide. Our previous study revealed that selegiline serves as an alternative candidate in transient hypoxia-ischemia. However, aggressive and restless behavior was observed in stroke-induced rats receiving 4 mg/kg selegiline. In comparison, 1 mg/kg selegiline could induce negligible therapeutic effects on mitochondrial dysfunction and histopathological changes. Therefore, we designed oral noisome-based selegiline attached to 4-(4-nitrobenzyl) pyridine to improve transient global ischemia by attenuating cognitive impairments, oxidative stress, and histopathological injury. The investigation was performed in transient hypoxia-ischemia-induced rats by oral administration of nanoformulation containing selegiline (0.25-1 mg/kg) for 4 weeks (3 times a week). Novel object recognition (NOR) was considered to evaluate their cognitive dysfunction. Oxidative stress parameters and brain histopathological assessments were determined following the scarification of rats. Outstandingly, our data demonstrated slower selegiline release from niosomes relative to free drug, which was also in a controlled manner. Our data confirmed significant improvement in cognitive behavior in the NOR test, an increase in glutathione level and total antioxidant power, a decline in MDA and protein carbonyl level, as well as a decreased number of dead cells in histopathological assessment after being exposed to (0.5-1 mg/kg) selegiline-NBP nanoformulation. These data manifested that the selegiline-NBP nanoformulation (0.5-1 mg/kg) could significantly reduce oxidative damage, cognitive dysfunction, and histopathological damage compared to transient hypoxia-ischemia rats, which is 20 times lower than the therapeutic dose in humans. Therefore, the proposed nanoformulation would be capable as an alternative candidate without side effects in stroke.

ZY12201, A Potent TGR5 Agonist: Identification of a Novel Pan CYP450 Inhibitor Tool Compound for In-Vitro Assessment

BACKGROUND

Identification of clinical drug-drug interaction (DDI) risk is an important aspect of drug discovery and development owing to poly-pharmacy in present-day clinical therapy. Drug metabolizing enzymes (DME) plays important role in the efficacy and safety of drug candidates. Hence evaluation of a New Chemical Entity (NCE) as a victim or perpetrator is very crucial for DDI risk mitigation. ZY12201 (2-((2-(4-(1H-imidazol-1-yl) phenoxy) ethyl) thio)-5-(2-(3, 4- dimethoxy phenyl) propane-2-yl)-1-(4-fluorophenyl)-1H-imidazole) is a novel and potent Takeda-G-protein-receptor-5 (TGR-5) agonist. ZY12201 was evaluated in-vitro to investigate the DDI liabilities.

OBJECTIVE

The key objective was to evaluate the CYP inhibition potential of ZY12201 for an opportunity to use it as a tool compound for pan CYP inhibition activities.

METHOD

In-vitro drug metabolizing enzymes (DME) inhibition potential of ZY12201 was evaluated against major CYP isoforms (1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4/5), aldehyde oxidase (AO), monoamine oxidase (MAO), and flavin-containing monooxygenase (FMO in human liver cytosol/mitochondrial preparation/ microsomes using probe substrates and Liquid Chromatography with tandem mass spectrometry (LC-MS-MS) method.

RESULTS

The study conducted on ZY12201 at 100 µM ZY12201 was found to reduce the metabolism of vanillin (AO probe substrate), tryptamine (MAO probe substrate), and benzydamine (FMO probe substrate) by 49.2%, 14.7%, and 34.9%, respectively. ZY12201 Ki values were 0.38, 0.25, 0.07, 0.01, 0.06, 0.02, 7.13, 0.03 and 0.003 μM for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4/5 (substrate: testosterone) and CYP3A4/5 (substrate: midazolam), respectively. Time-dependant CYP inhibition potential of ZY12201 was assessed against CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4/5 and no apparent IC50 shift was observed.

CONCLUSIONS

ZY12201, at 100 µM concentration showed low inhibition potential of AO, MAO, and FMO. ZY12201 was found as a potent inhibitor of CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A4/5 while moderately inhibits to CYP2E1. Inhibition of CYP1A2, CYP2B6, CYP2C19, and CYP2E1 by ZY12201 was competitive, while inhibition of CYP2C8, CYP2C9, CYP2D6, and CYP3A4/5 was of mixed-mode. ZY12201 is a non-time-dependent inhibitor of CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4/5. In summary, the reported Ki values unequivocally support that ZY12201 has a high potential to inhibit all major CYP isoforms. ZY12201 can be effectively used as a tool compound for in-vitro evaluation of CYP-based metabolic contribution to total drug clearance in the lead optimization stage of Drug Discovery Research.

INTERSYSTEM EXTRAPOLATION FACTORS (ISEF) ARE SUBSTRATE-DEPENDENT FOR CYP3A4: IMPACT ON CYTOCHROME P450 REACTION PHENOTYPING

The use of intersystem extrapolation factors (ISEF) is required for the quantitative scaling of drug metabolism data generated in individually expressed cytochrome P450 enzymes when estimating fractional contribution to metabolism by P450 enzymes in vivo (f_m,_CYP). For successful prediction of f_m, ISEF values must be universal across all substrates for any individual enzyme. In this study, ISEF values were generated for ten CYP3A4 selective substrates using a common source of recombinant heterologously expressed CYP3A4 and a pool of human liver microsomes. The resulting ISEF values for CYP3A4 were substrate-dependent and ranged 8-fold, with the highest value generated from intrinsic clearance of midazolam depletion (0.36) and the lowest from quinidine depletion (0.044). Application of these ISEF values for estimation of the fractional contribution of CYP3A4 and CYP2C19 to omeprazole clearance yielded values that ranged from 0.21-0.63 and 0.37-0.79, respectively, as compared to back-extrapolated in vivo f_m values of 0.27 (CYP3A4) and 0.85 (CYP2C19) from clinical pharmacokinetic data. For risperidone, estimated f_m values for CYP3A4 and CYP2D6 ranged from 0.87-0.98 and 0.02-0.13, respectively, as compared to in vivo values of 0.36 (CYP3A4) and 0.63-0.88 (CYP2D6), showing that the importance of CYP3A4 was over-estimated and the importance of CYP2D6 under-estimated. Overall, these findings suggest that ISEF values for CYP3A4 can vary with the marker substrate used to derive them, thereby reducing the effectiveness of the approach of using metabolism data from rCYP3A4 with ISEF values for the prediction of f_m values in vivo. Significance Statement Intersystem extrapolation factors (ISEF) are utilized for assigning fractional contributions of individual enzymes to drug clearance (f_m) from drug metabolism data generated in recombinant P450s. The present data shows that ISEF values for cytochrome P4503A4 vary with the substrate. This can lead to variable and erroneous prediction of f_m.

Reaction Phenotyping of Low-Turnover Compounds in Long-Term Hepatocyte Cultures Through Persistent Selective Inhibition of Cytochromes P450

Recognizing the challenges of determining the relative contribution of different drug metabolizing enzymes to the metabolism of slowly metabolized compounds, a cytochrome P450 reaction phenotyping (CRP) method using cocultured human hepatocytes (HEPATOPAC) has been established. In this study, the emphasis on the relative contribution of different cytochrome P450 (P450) isoforms was assessed by persistently inhibiting P450 isoforms over 7 days with human HEPATOPAC. P450 isoform-selective inhibition was achieved with the chemical inhibitors furafylline (CYP1A2), tienilic acid (CYP2C9), (+)-N-3-benzylnirvanol (CYP2C19), paroxetine (CYP2D6), azamulin (CYP3A), and a combination of 1-aminobenzotriazole and tienilic acid (broad spectrum inhibition of P450s). We executed this CRP method using HEPATOPAC by optimizing for the choice of P450 inhibitors, their selectivity, and the temporal effect of inhibitor concentrations on maintaining selectivity of inhibition. In general, the established CRP method using potent and selective chemical inhibitors allows to measure the relative contribution of P450s and to calculate the fraction of metabolism (f _m) of low-turnover compounds. Several low-turnover compounds were used to validate this CRP method by determining their hepatic intrinsic clearance and f _m, with comparison with literature values. We established the foundation of a robust CRP for low-turnover compound test system which can be expanded to include inhibition of other drug metabolizing enzymes. This generic CRP assay, using human long-term hepatocyte cultures, will be an essential tool in drug development for new chemical entities in the quantitative assessment of the risk as a victim of drug-drug interactions. SIGNIFICANCE STATEMENT: An ongoing trend is to develop drug candidates which have limited metabolic clearance. The current studies report a generic approach to conducting reaction phenotyping studies with human HEPATOPAC, focusing on P450 metabolism of low-turnover compounds. Potent and selective chemical inhibitors were used to assess the relative contribution of the major human P450s. Validation was achieved by confirming hepatic intrinsic clearance and fraction of metabolism for previously reported low-turnover compounds. This approach is adaptable for assessment of all drug metabolizing enzymes.

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization

Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed in vitro to in vivo extrapolation (IVIVE) that involves measuring drug metabolism in vitro, scaling-up this in vitro intrinsic clearance to a prediction of in vivo intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict in vivo clearance. This manuscript reviews common in vitro techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

Usage of In Vitro Metabolism Data for Drug-Drug Interaction in Physiologically Based Pharmacokinetic Analysis Submissions to the US Food and Drug Administration

The key parameters necessary to predict drug-drug interactions (DDIs) are intrinsic clearance (CL_int ) and fractional contribution of the metabolizing enzyme toward total metabolism (f_m ). Herein, we summarize the accumulated knowledge from 53 approved new drug applications submitted to the Office of Clinical Pharmacology, US Food and Drug Administration, from 2016 to 2018 that contained physiologically based pharmacokinetic (PBPK) models to understand how in vitro data are used in PBPK models to assess drug metabolism and predict DDIs. For evaluation of CL_int and f_m , 29 and 20 new drug applications were included for evaluation, respectively. For CL_int , 86.2% of the PBPK models used modified values based on in vivo data with modifications ranging from -82.5% to 2752.5%. For f_m , 45.0% of the models used modified values with modifications ranging from -28% to 178.6%. When values for CL_int were used from in vitro testing without modification, the model resulted in up to a 14.3-fold overprediction of the area under the concentration-time curve of the substrate. When values for f_m from in vitro testing were used directly, the model resulted in up to a 2.9-fold underprediction of its DDI magnitude with an inducer, and up to a 1.7-fold overprediction of its DDI magnitude with an inhibitor. Our analyses suggested that the in vitro system usually provides a reasonable estimation of f_m when the drug metabolism by a given CYP pathway is more than 70% of the total clearance. In vitro experiments provide important information about basic PK properties of new drugs and can serve as a starting point for building a PBPK model. However, key PBPK parameters such as CL_int and f_m still need to be optimized based on in vivo data.

Evaluation of Pharmacokinetic Drug-Drug Interactions: A Review of the Mechanisms, In Vitro and In Silico Approaches

Pharmacokinetic drug–drug interactions (DDIs) occur when a drug alters the absorption, transport, distribution, metabolism or excretion of a co-administered agent. The occurrence of pharmacokinetic DDIs may result in the increase or the decrease of drug concentrations, which can significantly affect the drug efficacy and safety in patients. Enzyme-mediated DDIs are of primary concern, while the transporter-mediated DDIs are less understood but also important. In this review, we presented an overview of the different mechanisms leading to DDIs, the in vitro experimental tools for capturing the factors affecting DDIs, and in silico methods for quantitative predictions of DDIs. We also emphasized the power and strategy of physiologically based pharmacokinetic (PBPK) models for the assessment of DDIs, which can integrate relevant in vitro data to simulate potential drug interaction in vivo. Lastly, we pointed out the future directions and challenges for the evaluation of pharmacokinetic DDIs.

Evidence-based strategies for the characterisation of human drug and chemical glucuronidation in vitro and UDP-glucuronosyltransferase reaction phenotyping

Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily contribute to the elimination of drugs from almost all therapeutic classes. Awareness of the importance of glucuronidation as a drug clearance mechanism along with increased knowledge of the enzymology of drug and chemical metabolism has stimulated interest in the development and application of approaches for the characterisation of human drug glucuronidation in vitro, in particular reaction phenotyping (the fractional contribution of the individual UGT enzymes responsible for the glucuronidation of a given drug), assessment of metabolic stability, and UGT enzyme inhibition by drugs and other xenobiotics. In turn, this has permitted the implementation of in vitro - in vivo extrapolation approaches for the prediction of drug metabolic clearance, intestinal availability, and drug-drug interaction liability, all of which are of considerable importance in pre-clinical drug development. Indeed, regulatory agencies (FDA and EMA) require UGT reaction phenotyping for new chemical entities if glucuronidation accounts for ≥25% of total metabolism. In vitro studies are most commonly performed with recombinant UGT enzymes and human liver microsomes (HLM) as the enzyme sources. Despite the widespread use of in vitro approaches for the characterisation of drug and chemical glucuronidation by HLM and recombinant enzymes, evidence-based guidelines relating to experimental approaches are lacking. Here we present evidence-based strategies for the characterisation of drug and chemical glucuronidation in vitro, and for UGT reaction phenotyping. We anticipate that the strategies will inform practice, encourage development of standardised experimental procedures where feasible, and guide ongoing research in the field.

Application of Azamulin to Determine the Contribution of CYP3A4/5 to Drug Metabolic Clearance Using Human Hepatocytes

Early determination of CYP3A4/5 contribution to the clearance of new chemical entities is critical to inform on the risk of drug-drug interactions with CYP3A inhibitors and inducers. Several in vitro approaches (recombinant P450 enzymes, correlation analysis, chemical and antibody inhibition in human liver microsomes) are available, but they are usually labor-intensive and/or suffer from specific limitations. In the present study, we have validated the use of azamulin as a specific CYP3A inhibitor in human hepatocytes. Azamulin (3 µM) was found to significantly inhibit CYP3A4/5 (>90%), whereas other P450 enzymes were not affected (less than 20% inhibition). Because human hepatocytes were used as a test system, the effect of azamulin on other key drug-metabolizing enzymes (aldehyde oxidase, carboxylesterase, UGT, flavin monooxygenase, and sulfotransferase) was also investigated. Apart from some UGTs showing minor inhibition (∼20%-30%), none of these non-P450 enzymes were inhibited by azamulin. Use of CYP3A5-genotyped human hepatocyte batches in combination with CYP3cide demonstrated that azamulin (at 3 µM) inhibits both CYP3A4 and CYP3A5 enzymes. Finally, 11 compounds with known in vivo CYP3A4/5 contribution have been evaluated in this human hepatocyte assay. Results showed that the effect of azamulin on the in vitro intrinsic clearance of these known CYP3A4/5 substrates was predictive of the in vivo CYP3A4/5 contribution. Overall, the study showed that human hepatocytes treated with azamulin provide a fast and accurate estimation of CYP3A4/5 contribution in metabolic clearance of new chemical entities. SIGNIFICANCE STATEMENT: Accurate estimation of CYP3A4/5 contribution in drug clearance is essential to anticipate risk of drug-drug interactions and select the appropriate candidate for clinical development. The present study validated the use of azamulin as selective CYP3A4/5 inhibitor in suspended human hepatocytes and demonstrated that this novel approach provides a direct and accurate determination of the contribution of CYP3A4/5 (fraction metabolized by CYP3A4/5) in the metabolic clearance of new chemical entities.

Evaluation of Erythromycin as a Tool to Assess CYP3A Contribution of Low Clearance Compounds in a Long-Term Hepatocyte Culture

Long-term hepatocyte culture systems such as HepatoPac are well suited to evaluate the metabolic turnover of low clearance (CL) drugs because of their sustained metabolic capacity and longer-term viability. Erythromycin (ERY), a moderate, mechanism-based inhibitor of CYP3A, was evaluated as a tool in the HepatoPac model to assess contribution of CYP3A to the clearance of drug candidates. ERY inhibited CYP3A activity by 58% and 80% at 3 and 10 μM, respectively, for up to 72 hours. At 30 µM, ERY inhibited midazolam hydroxylation by >85% for the entire 144-hour duration of the incubation. Alprazolam CL_int was inhibited 58% by 3 μM of ERY, 75% by 15 μM of ERY, 89% by 30 μM of ERY, and 94% by 60 μM of ERY. ERY (30 μM) did not markedly affect CL_int of substrates for several other major cytochrome P450 isoforms evaluated and did not markedly inhibit uridine diphosphoglucuronosyl transferase (UGT) isoforms 1A1, 1A3, 1A4, 1A6, 1A9, 2B7, or 2B15 as assessed using recombinant UGTs. ERY only mildly increased CYP3A4 gene expression by 2.1-fold (14% of rifampicin induction) at 120 µM, indicating that at effective concentrations for inhibition of CYP3A activity (30-60 µM), arylhydrocarbon receptor, constitutive androstane receptor, and pregnane-X-receptor activation are not likely to markedly increase levels of other drug-metabolizing enzymes or transporters. ERY at concentrations up to 60 µM was not toxic for up to 6 days of incubation. Use of ERY to selectively inhibit CYP3A in high-functioning, long-term hepatocyte models such as HepatoPac can be a valuable strategy to evaluate the contribution of CYP3A metabolism to the overall clearance of slowly metabolized drug candidates. SIGNIFICANCE STATEMENT: This work describes the use of erythromycin as a selective inhibitor of CYP3A to assess the contribution of CYP3A in the metabolism of compounds using long-term hepatocyte cultures.

Metabolite profiling and identification of enzymes responsible for the metabolism of mitragynine, the major alkaloid of Mitragyna speciosa (kratom)

1. Mitragynine is the major indole-based alkaloid of Mitragyna speciosa (kratom). Decoctions (teas) of the plant leaves have been used traditionally for cough, diarrhoea, pain, hypertension and for the treatment of opioid addiction. In the West, kratom has become increasingly utilized for mood elevation, pain treatment and as a means of self-treating opioid addiction. 2. Metabolic pathways of mitragynine were identified in human liver microsomes (HLM) and S9 fractions. A total of thirteen metabolites were identified, four oxidative metabolites and a metabolite formed by demethylation at the 9-methoxy group were the major metabolites of mitragynine. 3. The cytochrome P450 enzymes involved in the metabolism of mitragynine were identified using selective chemical inhibitors of HLM and recombinant cytochrome P450. The metabolism of mitragynine was predominantly carried out through the CYP3A4 with minor contributions by CYP2D6 and CYP2C9. The formation of five oxidative metabolites (Met2, Met4, Met6, Met8 and Met11) was catalyzed by the CYP3A4. 4. In summary, mitragynine was extensively metabolized in HLM primarily to O-demethylated and mono-oxidative metabolites. The CYP3A4 enzyme plays a predominant role in the metabolic clearance of mitragynine and also in the formation of 7-hydroxymitragynine (Met2), a known active minor alkaloid identified in the leaf material.

Decreasing the CYP2D6 contribution to metabolism of a CK1ε inhibitor

Our internal casein kinase 1ε lead inhibitor, compound 1 was partially cleared by the polymorphic cytochrome P450 2D6. CYP2D6 involvement in metabolism implies more extensive clinical trials. We therefore wanted to reduce the contribution to clearance by this enzyme. We utilized metabolism reports for compound 1 performed in recombinant CYP2D6 together with structure-metabolism variation in structures of closely related analogs in order to see if we could incorporate similar substitution patterns in our lead compound. In addition, we utilized a previously established docking method using a modified CYP2D6 crystal structure to see if the metabolism patterns in CYP2D6 could be reproduced to afford the metabolites in the metabolism reports as well as those for the compounds used in the structure-metabolism relationship. All three of these steps, the metabolism report, the establishment of structure-metabolism relationships and the docking, lead to compound 10 where CYP2D6 was not involved in the clearance pathways.

Protein Engineering of the Progesterone Hydroxylating P450-Monooxygenase CYP17A1 Alters Its Regioselectivity

The CYP171 enzyme is known to catalyse a key step in the steroidogenesis of mammals. The substrates progesterone and pregnenolone are first hydroxylated at the C17 position, and this is followed by cleavage of the C17-C20 bond to yield important precursors for glucosteroids and androgens. In this study, we focused on the reaction of the bovine CYP17A1 enzyme with progesterone as a substrate. On the basis of a created homology model, active-site residues were identified and systematically mutated to alanine. In whole-cell biotransformations, the importance of the N202, R239, G297 and E305 residues for substrate conversion was confirmed. Additionally, mutation of the L206, V366 and V483 residues enhanced the formation of the 16α-hydroxyprogesterone side product up to 40 % of the total product formation. Furthermore, residue L105 was found not to be involved in this side activity, which contradicts a previous study with the human enzyme.

Celecoxib is a substrate of CYP2D6: Impact on celecoxib metabolism in individuals with CYP2C9*3 variants

Celecoxib was characterized as a substrate of human cytochrome P450 (CYP) 2D6 in vitro. In recombinant CYP2D6, celecoxib hydroxylation showed atypical substrate inhibition kinetics with apparent K_m, K_i, and V_max of 67.2 μM, 12.6 μM, and 1.33 μM/min, respectively. In human liver microsomes (HLMs), a concentration-dependent inhibition of celecoxib hydroxylation by quinidine was observed after CYP2C9 and CYP3A4 were inhibited. In individual HLMs with variable CYP2D6 activities, a significant correlation was observed between celecoxib hydroxylation and CYP2D6-selective dextromethorphan O-demethylation when CYP2C9 and CYP3A4 activities were suppressed (r = 0.97, P < 0.0001). Molecular modeling showed two predominant docking modes of celecoxib with CYP2D6, resulting in either a substrate or an inhibitor. A second allosteric binding antechamber, which stabilized the inhibition mode, was revealed. Modeling results were consistent with the observed substrate inhibition kinetics. Using HLMs from individual donors, the relative contribution of CYP2D6 to celecoxib metabolism was found to be highly variable and dependent on CYP2C9 genotypes, ranging from no contribution in extensive metabolizers with CYP2C9*1*1 genotype to approximately 30% in slow metabolizers with allelic variants CYP2C9*1*3 and CYP2C9*3*3. These results demonstrate that celecoxib may become a potential victim of CYP2D6-associated drug-drug interactions, particularly in individuals with reduced CYP2C9 activity.

Identification of metabolites of MDR-1339, an inhibitor of β-amyloid protein aggregation, and kinetic characterization of the major metabolites in rats

We previously reported that MDR-1339, an inhibitor of β-amyloid protein aggregation, was likely to be eliminated by biotransformation in rats. The objective of this study was to determine the chemical identity of metabolites derived from this aggregate inhibitor and to characterize the kinetics of formation of these metabolites in rats. Using high performance liquid chromatography coupled with mass spectrometry with a hybrid triple quadrupole-linear ion trap, 7 metabolites and 1 potential metabolic intermediate were identified in RLM incubations containing MDR-1339. In addition to these, 3 glucuronide metabolites were detected in urine samples from rats receiving a 10 mg/kg oral dose of MDR-1339. When the kinetics of the formation of two major metabolites, M1 and M2, were analyzed assuming simple Michaelis-Menten kinetics, the V_max and K_m values were found to be 0.459 ± 0.0196 nmol/min/mg protein and 28.3 ± 3.07 μM for M1, and 0.101 ± 0.00537 nmol/min/mg protein and 14.7 ± 2.37 μM for M2, respectively. When chemically synthesized M1 and M2 were individually administered to rats intravenously at the dose of 5 mg/kg respectively, the volume of distribution and elimination clearance were determined to be 4590 ± 709 mL/kg and 68.4 ± 5.60 mL/min/kg for M1 and 15300 ± 8110 mL/kg and 98.0 ± 19.5 mL/min/kg for M2, respectively. When MDR-1339 was intravenously administered to rats at a dose of 5 mg/kg, the parent drug and M1 were readily detected for periods of up to 6 h after the administration, but M2 was observed only from 2 to 4 h. A standard moment analysis indicates that the formation clearance of M1 is 6.01 mL/min/kg, suggesting that 19.7% of the MDR-1339 dose was eliminated in rats. These observations indicate that the hepatic biotransformation of MDR-1339 results in the formation of at least 10 metabolites and that M1 is the major metabolite derived from this aggregation inhibitor in rats.

Direct and quantitative evaluation of the major human CYP contribution (fmCYP) to drug clearance using the in vitro Silensomes™ model

1. We have applied the concept of using MBIs to produce CYP-Silensomes to quantify the contribution of the major CYPs to drug metabolism (fmCYP). 2. The target CYPs were extensively and selectivity inhibited by the selected MBIs, while non-target CYPs were inhibited by less than 20% of the homologous control activities. Only CYP2D6-Silensomes exhibited a CYP2B6 inhibition that could be easily and efficiently encountered by subtracting the fm_CYP2B6 measured using CYP2B6-Silensomes to adjust the fm_CYP2D6. 3. To validate the use of a panel of 6 CYP-Silensomes, we showed that the fmCYP values of mono- and multi-CYP metabolised drugs were well predicted, with 70% within ± 15% accuracy. Moreover, the correlation with observed fmCYP values was higher than that for rhCYPs, which were run in parallel using the same drugs (<45% within ±15% accuracy). Moreover, the choice of the RAF substrate in rhCYP predictions was shown to affect the accuracy of the fmCYP measurement. 4. These results support the use of CYP1A2-, CYP2B6-, CYP2C8-, CYP2C9-, CYP2D6 and CYP3A4-Silensomes to accurately predict fmCYP values during the in vitro enzyme phenotyping assays in early, as well as in development, phases of drug development.

Estimation of fractions metabolized by hepatic CYP enzymes using a concept of inter-system extrapolation factors (ISEFs) - a comparison with the chemical inhibition method

BACKGROUND

For estimation of fractions metabolized (fm) by different hepatic recombinant human CYP enzymes (rhCYP), calculation of inter-system extrapolation factors (ISEFs) has been proposed.

METHODS

ISEF values for CYP1A2, CYP2C19 and CYP3A4/5 were measured. A CYP2C9 ISEF was taken from a previous report. Using a set of compounds, fractions metabolized by CYP enzymes (fm,CYP) values calculated with the ISEFs based on rhCYP data were compared with those from the chemical inhibition data. Oral pharmacokinetics (PK) profiles of midazolam were simulated using the physiologically based pharmacokinetics (PBPK) model with the CYP3A ISEF. For other CYPs, the in vitro fm,CYP values were compared with the reference fm,CYP data back-calculated with, e.g. modeling of test substrates by feeding clinical PK data.

RESULTS

In vitro-in vitro fm,CYP3A4 relationship between the results from rhCYP incubation and chemical inhibition was drawn as an exponential correlation with R2=0.974. A midazolam PBPK model with the CYP3A4/5 ISEFs simulated the PK profiles within twofold error compared to the clinical observations. In a limited number of cases, the in vitro methods could not show good performance in predicting fm,CYP1A2, fm,CYP2C9 and fm,CYP2C19 values as reference data.

CONCLUSIONS

The rhCYP data with the measured ISEFs provided reasonable calculation of fm,CYP3A4 values, showing slight over-estimation compared to chemical inhibition.

Systemic clearance and brain distribution of carbazole-based cyanine compounds as Alzheimer's disease drug candidates

SLM and SLOH, two analogues of carbazole-based cyanine compounds, have been shown to inhibit β-amyloid peptide aggregation in vitro and in Alzheimer’s disease model mice, which could be potentially developed into drugs for disease treatment. To pave the way for further pharmacokinetics-pharmacodynamics study, we set to investigate these compounds’ systemic clearance pathways and their brain exposure. We found that they generally exhibited relatively low plasma clearance which comprised of hepatic clearance and biliary clearance. Phase I oxidative metabolites for SLM and for SLOH upon microsomes incubation were identified, and the metabolism by CYP3A4 were found to be the major (>70%) hepatic clearance pathway, while the efflux by P-gp and BCRP located in the canalicular membrane of hepatocytes led to high biliary clearance. The permeation of SLM and SLOH through the brain endothelium was affected by the efflux transporters (P-gp and BCRP) and influx transporter (OATP2B1). The unbound interstitial fluid to plasma ratio (K_puu,brain) was 8.10 for SLOH and 11.0 for SLM, which favored brain entry and were several folds higher than that in wild-type mice. Taken together, these carbazole compounds displayed low plasma clearance and high brain permeability, which entitle further development.

Simultaneous detection of NADPH consumption and H2O2 production using the Ampliflu™ Red assay for screening of P450 activities and uncoupling

Cytochrome P450s belong to a large and diverse group of heme-containing enzymes. These monooxygenases catalyze the incorporation of a single atom of molecular oxygen into their substrate. In contrast to most other enzymes, the activity of P450 enzymes is not only dependent on substrate and cofactor availability and reaction conditions, but also depends on the coupling efficiency of the catalytic cycle itself. Through the electron transfer from NAD(P)H to the heme-center of the P450, the enzyme becomes activated and binds oxygen. The thereby generated iron-oxygen complex undergoes multiple reductive steps forming different activated oxygen species. These intermediates can decay easily, releasing the reactive oxygen species superoxide anion and hydrogen peroxide (H₂O₂), which can also be further reduced to water. This so-called uncoupling of the reaction cycle drains electrons from the system, which consequently does not lead to the desired product, but merely H₂O₂ formation with stoichiometric consumption of NAD(P)H. Hence, measuring NAD(P)H consumption only can lead to an overestimation of substrate conversion. To measure this uncoupling, we herein report a microtiter plate-based assay for the simultaneous quantification of hydrogen peroxide formation and NAD(P)H consumption using Ampliflu™ Red as reporter. This was exemplified for the P450 monooxygenase from Bacillus megaterium (P450 BM3) and five mutants, using different substrates. We demonstrate the applicability of the assay, which provides a versatile basis for a high-throughput preliminary screening of P450 enzyme libraries without the need for GC or HPLC analysis and clear indication of the extent of hydrogen peroxide uncoupling.

Improvement of the chemical inhibition phenotyping assay by cross-reactivity correction

BACKGROUND

The fraction of an absorbed drug metabolized by the different hepatic cytochrome P450 (CYP) enzymes, relative to total hepatic CYP metabolism (fmCYP), can be estimated by measuring the inhibitory effects of presumably selective CYP inhibitors on the intrinsic metabolic clearance of a drug using human liver microsomes. However, the chemical inhibition data are often affected by cross-reactivities of the chemical inhibitors used in this assay.

METHODS

To overcome this drawback, the cross-reactivities exhibited by six chemical inhibitors (furafylline, montelukast, sulfaphenazole, ticlopidine, quinidine and ketoconazole) were quantified using specific CYP enzyme marker reactions. The determined cross-reactivities were used to correct the in vitro fmCYPs of nine marketed drugs. The corrected values were compared with reference data obtained by physiologically based pharmacokinetics simulation using the software SimCYP.

RESULTS

Uncorrected in vitro fmCYPs of the nine drugs showed poor linear correlation with their reference data (R2=0.443). Correction by factoring in inhibitor cross-reactivities significantly improved the correlation (R2=0.736).

CONCLUSIONS

Correcting in vitro chemical inhibition results for cross-reactivities appear to offer a straightforward and easily adoptable approach to provide improved fmCYP data for a drug.

Impact of Probe Substrate Selection on Cytochrome P450 Reaction Phenotyping Using the Relative Activity Factor

Accurately assessing the contribution of cytochrome P450 (P450) isoforms to overall metabolic clearance is important for prediction of clinical drug-drug interactions (DDIs). The relative activity factor (RAF) approach in P450 reaction phenotyping assumes that the interaction between P450-selective probes and testing systems is the same as the interaction of drug candidate with those systems. To test this assumption, an intersystem clearance ratio (ICR) was created to evaluate the difference in values between RAF-scaled intrinsic clearance (CL_int) and measured CL_int in human liver microsomes (HLMs). The RAF value for CYP3A4 or CYP2C9 derived from a particular P450-selective probe reaction was applied to calculate RAF-scaled CL_int for other probe reactions of the same P450 isoform in a crossover manner and compared with the measured HLM CL_int When RAF derived from midazolam or nifedipine was used for CYP3A4, the ICR for testosterone 6β-hydroxylation was 31 and 25, respectively, suggesting significantly diverse interactions of CYP3A4 probes with the testing systems. Such ICR differences were less profound among probes for CYP2C9. In addition, these RAF values were applied to losartan and meloxicam, whose metabolism is mostly CYP2C9 mediated. Only using the RAF derived from testosterone for CYP3A4 produced the expected CYP2C9 contribution of 72%-87% and 47%-69% for metabolism of losartan and meloxicam, respectively. RAF derived from other CYP3A4 probes would have attributed predominantly to CYP3A4 and led to incorrect prediction of DDIs. Our study demonstrates a significant impact of probe substrate selection on P450 phenotyping using the RAF approach, and the ICR may provide a potential solution.

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions-an Industry Perspective

Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (fCL), estimation of fractional contribution of metabolizing enzyme toward metabolism (fm), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify fCL and fm, 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome.

Assessment of drug metabolism enzyme and transporter pharmacogenetics in drug discovery and early development: perspectives of the I-PWG

Genetic variants of drug metabolism enzymes and transporters can result in high pharmacokinetic and pharmacodynamic variability, unwanted characteristics of efficacious and safe drugs. Ideally, the contributions of these enzymes and transporters to drug disposition can be predicted from in vitro experiments and in silico modeling in discovery or early development, and then be utilized during clinical development. Recently, regulatory agencies have provided guidance on the preclinical investigation of pharmacogenetics, for application to clinical drug development. This white paper summarizes the results of an industry survey conducted by the Industry Pharmacogenomics Working Group on current practice and challenges with using in vitro systems and in silico models to understand pharmacogenetic causes of variability in drug disposition.

Software-aided cytochrome P450 reaction phenotyping and kinetic analysis in early drug discovery

RATIONALE

Cytochrome P450 (CYP450) reaction phenotyping (CRP) and kinetic studies are essential in early drug discovery to determine which metabolic enzymes react with new drug entities. A new semi-automated computer-assisted workflow for CRP is introduced in this work. This workflow provides not only information regarding parent disappearance, but also metabolite identification and relative metabolite formation rates for kinetic analysis.

METHODS

Time-course experiments based on incubating six probe substrates (dextromethorphan, imipramine, buspirone, midazolam, ethoxyresorufin and diclofenac) with recombinant human enzymes (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) and human liver microsomes (HLM) were performed. Liquid chromatography/high-resolution mass spectrometry (LC/HRMS) analysis was conducted with an internal standard to obtain high-resolution full-scan and MS/MS data. Data were analyzed using Mass-MetaSite software. A server application (WebMetabase) was used for data visualization and review.

RESULTS

CRP experiments were performed, and the data were analyzed using a software-aided approach. This automated-evaluation approach led to (1) the detection of the CYP450 enzymes responsible for both substrate depletion and metabolite formation, (2) the identification of specific biotransformations, (3) the elucidation of metabolite structures based on MS/MS fragment analysis, and (4) the determination of the initial relative formation rates of major metabolites by CYP450 enzymes.

CONCLUSIONS

This largely automated workflow enabled the efficient analysis of HRMS data, allowing rapid evaluation of the involvement of the main CYP450 enzymes in the metabolism of new molecules during drug discovery.

Content and activity of human liver microsomal protein and prediction of individual hepatic clearance in vivo

The lack of information concerning individual variation in content and activity of human liver microsomal protein is one of the most important obstacles for designing personalized medicines. We demonstrated that the mean value of microsomal protein per gram of liver (MPPGL) was 39.46 mg/g in 128 human livers and up to 19-fold individual variations existed. Meanwhile, the metabolic activities of 10 cytochrome P450 (CYPs) were detected in microsomes and liver tissues, respectively, which showed huge individual variations (200-fold). Compared with microsomes, the activities of liver tissues were much suitable to express the individual variations of CYP activities. Furthermore, individual variations in the in vivo clearance of tolbutamide were successfully predicted with the individual parameter values. In conclusion, we offer the values for MPPGL contents in normal liver tissues and build a new method to assess the in vitro CYP activities. In addition, large individual variations exist in predicted hepatic clearance of tolbutamide. These findings provide important physiological parameters for physiologically-based pharmacokinetics models and thus, establish a solid foundation for future development of personalized medicines.

A pilot study on the impact of known drug-drug interactions in cancer patients

Background

When a patient concomitantly uses two or more drugs, a drug-drug interaction (DDI) can possibly occur, potentially leading to an increased or decreased clinical effect of a given treatment. Cancer patients are at high risk of such interactions because they commonly receive multiple medications. Moreover, most cancer patients are elderly and require additional medications for comorbidities. Aim of this preliminary observational study was to evaluate the incidence of well known and established DDIs in a cohort of cancer outpatients undergoing multiple treatments.

Methods

Anamnestic and clinical data were collected for 64 adult patients in the ambulatory setting with malignant solid tumors who were receiving systemic anticancer treatment.

Patients also declared all drugs prescribed by other specialists or self-taken in the previous 2 weeks. DDIs were divided into two different groups: ‘neoplastic DDIs’ (NDDIs), involving antitumoral drugs, and ‘not neoplastic DDIs’ (nDDIs), involving all other classes of drugs. The severity of DDIs was classified as major, moderate and minor, according to the ‘Institute for Pharmacological Research Mario Negri’ definition.

Results

About 34 % of cancer outpatients within our cohort were prescribed/assumed interacting drug combinations. The most frequent major NDDIs involved the anticoagulant warfarin (33 % of total NDDIs) that, in association with tamoxifen, or capecitabine and paclitaxel, increased the risk of haemorrhage. About 60 % of nDDIs involved acetylsalicylic acid.

Conclusions

Overall, 16 % of DDIs were related to an A-level strength of recommendation to be avoided. The lack of effective communication among specialists and patients might have a role in determining therapeutic errors. Our pilot study, although limited by a small cohort size, highlights the urgent need of implementing the clinical management of cancer outpatients with new strategies to prevent or minimize potential harmful DDIs.

Strategies for individual phenotyping of linoleic and arachidonic acid metabolism using an oral glucose tolerance test

The ability to restore homeostasis upon environmental challenges has been proposed as a measure for health. Metabolic profiling of plasma samples during the challenge response phase should offer a profound view on the flexibility of a phenotype to cope with daily stressors. Current data modeling approaches, however, struggle to extract biological descriptors from time-resolved metabolite profiles that are able to discriminate between different phenotypes. Thus, for the case of oxylipin responses in plasma upon an oral glucose tolerance test we developed a modeling approach that incorporates a priori biological pathway knowledge. The degradation pathways of arachidonic and linoleic acids were modeled using a regression model based on a pseudo-steady-state approximated model, resulting in a parameter A that summarizes the relative enzymatic activity in these pathways. Analysis of the phenotypic parameters As suggests that different phenotypes can be discriminated according to preferred relative activity of the arachidonic and linoleic pathway. Correlation analysis shows that there is little or no competition between the arachidonic and linoleic acid pathways, although they share the same enzymes.

Reaction phenotyping: advances in the experimental strategies used to characterize the contribution of drug-metabolizing enzymes

During the process of drug discovery, the pharmaceutical industry is faced with numerous challenges. One challenge is the successful prediction of the major routes of human clearance of new medications. For compounds cleared by metabolism, accurate predictions help provide an early risk assessment of their potential to exhibit significant interpatient differences in pharmacokinetics via routes of metabolism catalyzed by functionally polymorphic enzymes and/or clinically significant metabolic drug-drug interactions. This review details the most recent and emerging in vitro strategies used by drug metabolism and pharmacokinetic scientists to better determine rates and routes of metabolic clearance and how to translate these parameters to estimate the amount these routes contribute to overall clearance, commonly referred to as fraction metabolized. The enzymes covered in this review include cytochrome P450s together with other enzymatic pathways whose involvement in metabolic clearance has become increasingly important as efforts to mitigate cytochrome P450 clearance are successful. Advances in the prediction of the fraction metabolized include newly developed methods to differentiate CYP3A4 from the polymorphic enzyme CYP3A5, scaling tools for UDP-glucuronosyltranferase, and estimation of fraction metabolized for substrates of aldehyde oxidase.