Projections of Drug-Drug Interactions Caused by Time-Dependent Inhibitors of Cytochrome P450 1A2, 2B6, 2C8, 2C9, 2C19, and 2D6 Using In Vitro Data in Static and Dynamic Models.

In vitro time-dependent inhibition (TDI) kinetic parameters for cytochrome P450 (CYP) 1A2, 2B6, 2C8, 2C9, 2C19, and 2D6, were determined in pooled human liver microsomes for 19 drugs (and 2 metabolites) for which clinical drug-drug interactions (DDI) are known. In vitro TDI data were incorporated into the projection of the magnitude of DDIs using mechanistic static models and Simcyp®. Results suggest that for the mechanistic static model, use of estimated average unbound exit concentration of the inhibitor from the liver resulted in a successful prediction of observed magnitude of clinical DDIs and was similar to Simcyp®. Overall, predictions of DDI magnitude (i.e., fold increase in AUC of a CYP-specific marker substrate) were within 2-fold of actual values. Geometric mean-fold errors were 1.7 and 1.6 for static and dynamic models, respectively. Projections of DDI from both models were also highly correlated to each other (r2 = 0.92). This investigation demonstrates that DDI can be reliably predicted from in vitro TDI data generated in HLM for several CYP enzymes. Simple mechanistic static model equations as well as more complex dynamic PBPK models can be employed in this process. Significance Statement Cytochrome P450 time-dependent inhibitors (TDI) can cause drug-drug interactions (DDI). An ability to reliably assess the potential for a new drug candidate to cause DDI is essential during drug development. In this report, TDI data for 19 drugs (and 2 metabolites) were measured and used in static and dynamic models to reliably project the magnitude of DDI resulting from inhibition of CYP1A2, 2B6, 2C8, 2C9, 2C19, and 2D6.

Physiologically Based Pharmacokinetic Modeling of the Drug-Drug Interaction Between CYP3A4 Substrate Glasdegib and Moderate CYP3A4 Inducers in Lieu of a Clinical Study.

Glasdegib (DAURISMO) is a hedgehog pathway inhibitor approved for the treatment of acute myeloid leukemia (AML). Cytochrome P450 3A4 (CYP3A4) has been identified as a major metabolism and clearance pathway for glasdegib. The role of CYP3A4 in the clearance of glasdegib has been confirmed with clinical drug-drug interaction (DDI) studies following the coadministration of glasdegib with the strong CYP3A4 inhibitor ketoconazole and the strong inducer rifampin. To evaluate potential drug interactions with CYP3A4 modulators, the coadministration of glasdegib with a moderate CYP3A4 inducer, efavirenz, was evaluated using physiologically based pharmacokinetic (PBPK) modeling using the Simcyp simulator. The glasdegib compound file was developed using measured physicochemical properties, data from human intravenous and oral pharmacokinetics, absorption, distribution, metabolism, and excretion studies, and in vitro reaction phenotyping results. The modeling assumptions, model parameters, and assignments of fractional CYP3A4 metabolism were verified using results from clinical pharmacokinetics (PK) and DDI studies with ketoconazole and rifampin. The verified glasdegib and efavirenz compound files, the latter of which was available in the Simcyp simulator, were used to estimate the potential impact of efavirenz on the PK of glasdegib. PBPK modeling predicted a glasdegib area under the concentration-time curve ratio of 0.45 and maximum plasma concentration ratio of 0.75 following coadministration with efavirenz. The PBPK results, in lieu of a formal clinical study, informed the drug label, with the recommendation to double the clinical dose of glasdegib when administered in conjunction with a moderate CYP3A4 inducer, followed by a resumption of the original dose 7 days post-discontinuation.

An improved method for cytochrome p450 reaction phenotyping using a sequential qualitative-then-quantitative approach.

Cytochrome P450 reaction phenotyping to determine the fraction of metabolism values (fm) for individual enzymes is a standard study in the evaluation of a new drug. However, there are technical challenges in these studies caused by shortcomings in the selectivity of P450 inhibitors and unreliable scaling procedures for recombinant P450 (rCYP) data. In this investigation, a two-step "qualitative-then-quantitative" approach to P450 reaction phenotyping is described. In the first step, each rCYP is tested qualitatively for potential to generate metabolites. In the second step, selective inhibitors for the P450s identified in step1 are tested for their effects on metabolism using full inhibition curves. Forty-eight drugs were evaluated in step 1 and there were no examples of missing an enzyme important to in vivo clearance. Five drugs (escitalopram, fluvastatin, pioglitazone, propranolol, and risperidone) were selected for full phenotyping in step2 to determine fm values, with findings compared to fm values estimated from single inhibitor concentration data and rCYP with intersystem-extrapolation-factor corrections. The two-step approach yielded fm values for major drug clearing enzymes that are close to those estimated from clinical data: escitalopram and CYP2C19 (0.42 vs 0.36-0.82), fluvastatin and CYP2C9 (0.76 vs 0.76), pioglitazone and CYP2C8 (0.72 vs 0.73), propranolol and CYP2D6 (0.68 vs 0.37-0.56) and risperidone and CYP2D6 (0.60 vs 0.66-0.88). Reaction phenotyping data generated in this fashion should offer better input to physiologically-based pharmacokinetic models for prediction of DDI and impact of genetic polymorphisms on drug clearance. The qualitative-then-quantitative approach is proposed as a replacement to standard reaction phenotyping strategies. Significance Statement P450 reaction phenotyping is important for projecting drug-drug interactions and interpatient variability in drug exposure. However, currently recommended practices can frequently fail to provide reliable estimates of the fractional contributions of specific P450 enzymes (fm) to drug clearance. In this report, we describe a two-step qualitative-then-quantitative reaction phenotyping approach that yields more accurate estimates of fm.

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.

Investigation of CYP3A induction by PF-05251749 in early clinical development: comparison of linear slope physiologically based pharmacokinetic prediction and biomarker response.

PF-05251749 is a dual inhibitor of casein kinase 1 δ/ε under clinical development to treat disruption of circadian rhythm in Alzheimer's and Parkinson's diseases. In vitro, PF-05251749 (0.3-100 µM) induced CYP3A in cryopreserved human hepatocytes, demonstrating non-saturable, dose-dependent CYP3A mRNA increases, with induction slopes in the range 0.036-0.39 µM-1 . In a multiple-dose study (B8001002) in healthy participants, CYP3A activity was explored by measuring changes in 4ß-hydroxycholesterol/cholesterol ratio. Following repeated oral administration of PF-05251749, up to 400 mg q.d., no significant changes were observed in 4ß-hydroxycholesterol/cholesterol ratio; this ratio increased significantly (~1.5-fold) following administration of PF-05251749 at 750 mg q.d., suggesting potential CYP3A induction at this dose. Physiologically based pharmacokinetic (PBPK) models were developed to characterize the observed clinical pharmacokinetics (PK) of PF-05251749 at 400 and 750 mg q.d.; the PBPK induction model was calibrated using the in vitro linear fit induction slope, with rifampin as reference compound (Indmax  = 8, EC50  = 0.32 µM). Clinical trial simulation following co-administration of PF-05251749, 400 mg q.d. with oral midazolam 2 mg, predicted no significant drug interaction risk. PBPK model predicted weak drug interaction following co-administration of PF-05251749, 750 mg q.d. with midazolam 2 mg. In conclusion, good agreement was obtained between CYP3A drug interaction risk predicted using linear-slope PBPK model and exploratory biomarker trends. This agreement between two orthogonal approaches enabled assessment of drug interaction risks of PF-05251749 in early clinical development, in the absence of a clinical drug-drug interaction study.

The Pharmacokinetics, Metabolism, and Clearance Mechanisms of Abrocitinib, a Selective Janus Kinase Inhibitor, in Humans.

Abrocitinib is an oral once-daily Janus kinase 1 selective inhibitor being developed for the treatment of moderate-to-severe atopic dermatitis. This study examined the disposition of abrocitinib in male participants following oral and intravenous administration using accelerator mass spectroscopy methodology to estimate pharmacokinetic parameters and characterize metabolite (M) profiles. The results indicated abrocitinib had a systemic clearance of 64.2 L/h, a steady-state volume of distribution of 100 L, extent of absorption >90%, time to maximum plasma concentration of ∼0.5 hours, and absolute oral bioavailability of 60%. The half-life of both abrocitinib and total radioactivity was similar, with no indication of metabolite accumulation. Abrocitinib was the main circulating drug species in plasma (∼26%), with 3 major monohydroxylated metabolites (M1, M2, and M4) at >10%. Oxidative metabolism was the primary route of elimination for abrocitinib, with the greatest disposition of radioactivity shown in the urine (∼85%). In vitro phenotyping indicated abrocitinib cytochrome P450 fraction of metabolism assignments of 0.53 for CYP2C19, 0.30 for CYP2C9, 0.11 for CYP3A4, and ∼0.06 for CYP2B6. The principal systemic metabolites M1, M2, and M4 were primarily cleared renally. Abrocitinib, M1, and M2 showed pharmacology with similar Janus kinase 1 selectivity, whereas M4 was inactive. SIGNIFICANCE STATEMENT: This study provides a detailed understanding of the disposition and metabolism of abrocitinib, a Janus kinase inhibitor for atopic dermatitis, in humans, as well as characterization of clearance pathways and pharmacokinetics of abrocitinib and its metabolites.

Static and Dynamic Projections of Drug-Drug Interactions Caused by Cytochrome P450 3A Time-Dependent Inhibitors Measured in Human Liver Microsomes and Hepatocytes.

Cytochrome P450 3A (CYP3A) is a frequent target for time-dependent inhibition (TDI) that can give rise to drug-drug interactions (DDI). Yet many drugs that exhibit in vitro TDI for CYP3A do not result in DDI. There were 23 drugs with published clinical DDI evaluated for CYP3A TDI in human liver microsomes (HLM) and hepatocytes (HHEP), and these data were used in static and dynamic models for projecting DDI caused by inactivation of CYP3A in both liver and intestine. TDI parameters measured in HHEP, particularly the maximal rate of enzyme inactivation, were generally lower than those measured in HLM. In static models, the use of estimated average unbound organ exit concentrations offered the most accurate projections of DDI with geometric mean fold errors of 2.0 and 1.7 for HLM and HHEP, respectively. Use of maximum organ entry concentrations yielded marked overestimates of DDI. When evaluated in a binary fashion (i.e., projection of DDI of 1.25-fold or greater), data from HLM offered the greatest sensitivity (100%) and specificity (67%) and yielded no missed DDI when average unbound organ exit concentrations were used. In dynamic physiologically based pharmacokinetic modeling, accurate projections of DDI were obtained with geometric mean fold errors of 1.7 and 1.6 for HLM and HHEP, respectively. Sensitivity and specificity were 100% and 67% when using TDI data generated in HLM and Simcyp modeling. Overall, DDI caused by CYP3A-mediated TDI can be reliably projected using dynamic or static models. For static models, average organ unbound exit concentrations should be used as input values otherwise DDI will be markedly overestimated. SIGNIFICANCE STATEMENT: CYP3A time-dependent inhibitors (TDI) are important in the design and development of new drugs. The prevalence of CYP3A TDI is high among newly synthesized drug candidates, and understanding the potential need for running clinical drug-drug interaction (DDI) studies is essential during drug development. Ability to reliably predict DDI caused by CYP3A TDI has been difficult to achieve. We report a thorough evaluation of CYP3A TDI and demonstrate that DDI can be predicted when using appropriate models and input parameters generated in human liver microsomes or hepatocytes.

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.

Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Guidelines on Model Fitting and Recommendations on Time Course for In Vitro Cytochrome P450 Induction Studies Including Impact on Drug Interaction Risk Assessment.

Translational and ADME Sciences Leadership Group Induction Working Group (IWG) presents an analysis on the time course for cytochrome P450 induction in primary human hepatocytes. Induction of CYP1A2, CYP2B6, and CYP3A4 was evaluated by seven IWG laboratories after incubation with prototypical inducers (omeprazole, phenobarbital, rifampicin, or efavirenz) for 6-72 hours. The effect of incubation duration and model-fitting approaches on induction parameters (Emax and EC50) and drug-drug interaction (DDI) risk assessment was determined. Despite variability in induction response across hepatocyte donors, the following recommendations are proposed: 1) 48 hours should be the primary time point for in vitro assessment of induction based on mRNA level or activity, with no further benefit from 72 hours; 2) when using mRNA, 24-hour incubations provide reliable assessment of induction and DDI risk; 3) if validated using prototypical inducers (>10-fold induction), 12-hour incubations may provide an estimate of induction potential, including characterization as negative if <2-fold induction of mRNA and no concentration dependence; 4) atypical dose-response ("bell-shaped") curves can be addressed by removing points outside an established confidence interval and %CV; 5) when maximum fold induction is well defined, the choice of nonlinear regression model has limited impact on estimated induction parameters; 6) when the maximum fold induction is not well defined, conservative DDI risk assessment can be obtained using sigmoidal three-parameter fit or constraining logistic three- or four-parameter fits to the maximum observed fold induction; 7) preliminary data suggest initial slope of the fold induction curve can be used to estimate Emax/EC50 and for induction risk assessment. SIGNIFICANCE STATEMENT: Regulatory agencies provide inconsistent guidance on the optimum length of time to evaluate cytochrome P450 induction in human hepatocytes, with EMA recommending 72 hours and FDA suggesting 48-72 hours. The Induction Working Group analyzed a large data set generated by seven member companies and determined that induction response and drug-drug risk assessment determined after 48-hour incubations were representative of 72-hour incubations. Additional recommendations are provided on model-fitting techniques for induction parameter estimation and addressing atypical concentration-response curves.

Physiologically-Based Pharmacokinetic Modeling of the Drug-Drug Interaction of the UGT Substrate Ertugliflozin Following Co-Administration with the UGT Inhibitor Mefenamic Acid.

The sodium-glucose cotransporter 2 inhibitor ertugliflozin is metabolized by the uridine 5'-diphospho-glucuronosyltransferase (UGT) isozymes UGT1A9 and UGT2B4/2B7. This analysis evaluated the drug-drug interaction (DDI) following co-administration of ertugliflozin with the UGT inhibitor mefenamic acid (MFA) using physiologically-based pharmacokinetic (PBPK) modeling. The ertugliflozin modeling assumptions and parameters were verified using clinical data from single-dose and multiple-dose studies of ertugliflozin in healthy volunteers, and the PBPK fraction metabolized assignments were consistent with human absorption, distribution, metabolism, and excretion results. The model for MFA was developed using clinical data, and in vivo UGT inhibitory constant values were estimated using the results from a clinical DDI study with MFA and dapagliflozin, a UGT1A9 and UGT2B4/2B7 substrate in the same chemical class as ertugliflozin. Using the verified compound files, PBPK modeling predicted an ertugliflozin ratio of area under the plasma concentration-time curves (AUCR ) of 1.51 when co-administered with MFA. ClinicalTrials.gov identifier: NCT00989079.

In Vitro Characterization of Ertugliflozin Metabolism by UDP-Glucuronosyltransferase and Cytochrome P450 Enzymes.

Ertugliflozin is primarily cleared through UDP-glucurosyltransferase (UGT)-mediated metabolism (86%) with minor oxidative clearance (12%). In vitro phenotyping involved enzyme kinetic characterization of UGTs or cytochrome P450 enzymes catalyzing formation of the major 3-O-ß-glucuronide (M5c) and minor 2-O-ß-glucuronide (M5a), monohydroxylated ertugliflozin (M1 and M3), and des-ethyl ertugliflozin (M2) metabolites in human liver microsomes (HLMs). Fractional clearance (fCL) from HLM intrinsic clearance (CLint) indicated a major role for glucuronidation (fCL 0.96; CLint 37 µl/min per milligram) versus oxidative metabolism (fCL 0.04; CLint 1.64 µl/min per milligram). Substrate concentration at half-maximal velocity (Km), maximal rate of metabolism (Vmax), and CLint for M5c and M5a formation were 10.8 µM, 375 pmol/min per milligram, and 34.7 µl/min per milligram and 41.7 µM, 94.9 pmol/min per milligram, and 2.28 µl/min per milligram, respectively. Inhibition of HLM CLint with 10 µM digoxin or tranilast (UGT1A9) and 3 µM 16ß-phenyllongifolol (UGT2B7/UGT2B4) resulted in fraction metabolism (fm) estimates of 0.81 and 0.19 for UGT1A9 and UGT2B7/UGT2B4, respectively. Relative activity factor scaling of recombinant enzyme kinetics provided comparable fm for UGT1A9 (0.86) and UGT2B7 (0.14). Km and Vmax for M1, M2, and M3 formation ranged 73.0-93.0 µM and 24.3-116 pmol/min per milligram, respectively, and was inhibited by ketoconazole (M1, M2, and M3) and montelukast (M2). In summary, ertugliflozin metabolism in HLMs was primarily mediated by UGT1A9 (78%) with minor contributions from UGT2B7/UGT2B4 (18%), CYP3A4 (3.4%), CYP3A5 (0.4%), and CYP2C8 (0.16%). Considering higher ertugliflozin oxidative metabolism (fCL 0.12) obtained from human mass balance, human systemic clearance is expected to be mediated by UGT1A9 (70%), UGT2B7/UGT2B4 (16%), CYP3A4 (10%), CYP3A5 (1.2%), CYP2C8 (0.5%), and renal elimination (2%). SIGNIFICANCE STATEMENT: This manuscript describes the use of orthogonal approaches (i.e., enzyme kinetics, chemical inhibitors, and recombinant enzymes) to characterize the fraction of ertugliflozin metabolism through various UDP-glucuronosyltransferase (UGT) and cytochrome P450 (CYP) enzyme-mediated pathways. Phenotyping approaches routinely used to characterize CYP hepatic fractional metabolism (fm) to estimate specific enzymes contributing to overall systemic clearance were similarly applied for UGT-mediated metabolism. Defining the in vitro metabolic disposition and fm for ertugliflozin allows risk assessment when considering potential victim-based drug-drug interactions perpetrated by coadministered drugs.

Cytochrome P450 3A Time-Dependent Inhibition Assays Are Too Sensitive for Identification of Drugs Causing Clinically Significant Drug-Drug Interactions: A Comparison of Human Liver Microsomes and Hepatocytes and Definition of Boundaries for Inactivation Rate Constants.

Time-dependent inhibition (TDI) of CYP3A is an important mechanism underlying numerous drug-drug interactions (DDIs), and assays to measure this are done to support early drug research efforts. However, measuring TDI of CYP3A in human liver microsomes (HLMs) frequently yields overestimations of clinical DDIs and thus can lead to the erroneous elimination of many viable drug candidates from further development. In this investigation, 50 drugs were evaluated for TDI in HLMs and suspended human hepatocytes (HHEPs) to define appropriate boundary lines for the TDI parameter rate constant for inhibition (kobs) at a concentration of 30 µM. In HLMs, a kobs value of 0.002 minute-1 was statistically distinguishable from control; however, many drugs show kobs greater than this but do not cause DDI. A boundary line defined by the drug with the lowest kobs that causes a DDI (diltiazem) was established at 0.01 minute-1 Even with this boundary, of the 33 drugs above this value, only 61% cause a DDI (true positive rate). A corresponding analysis was done using HHEPs; kobs of 0.0015 minute-1 was statistically distinguishable from control, and the boundary was established at 0.006 minute-1 Values of kobs in HHEPs were almost always lower than those in HLMs. These findings offer a practical guide to the use of TDI data for CYP3A in early drug-discovery research. SIGNIFICANCE STATEMENT: Time-dependent inhibition of CYP3A is responsible for many drug interactions. In vitro assays are employed in early drug research to identify and remove CYP3A time-dependent inhibitors from further consideration. This analysis demonstrates suitable boundaries for inactivation rates to better delineate drug candidates for their potential to cause clinically significant drug interactions.

Physiologically Based Pharmacokinetic Modeling Suggests Limited Drug-Drug Interaction for Fesoterodine When Coadministered With Mirabegron.

5-Hydroxymethyl tolterodine (5-HMT; the active fesoterodine metabolite) is metabolized via the cytochrome P450 (CYP) 2D6 and CYP3A pathways. Mirabegron is a moderate CYP2D6 inhibitor and weak CYP3A inhibitor. Potential drug-drug interactions (DDIs) following coadministration of these 2 overactive bladder treatments were estimated using physiologically based pharmacokinetic models, developed and verified by comparing predicted and observed pharmacokinetic profiles from clinical studies. Models predicted and verified mirabegron and desipramine (CYP2D6 substrate) and 5-HMT and ketoconazole (strong CYP3A inhibitor) DDIs. Mirabegron model-predicted mean steady-state AUC and Cmax were within 11% of clinical observations. The predicted versus observed geometric mean ratio (GMR) of AUCinf for CYP2D6 substrates desipramine and metoprolol coadministered with mirabegron 100 or 160 mg once daily were 3.47 versus 3.41 and 2.97 versus 3.29, respectively, indicating that the mirabegron model can be used to predict clinical CYP2D6 inhibition. 5-HMT fractional clearance by CYP3A and CYP2D6 was verified from clinical DDI studies with a potent CYP3A4 inhibitor (ketoconazole) and inducer (rifampicin) in CYP2D6 extensive and poor metabolizers and with a moderate CYP3A inhibitor (fluconazole) in healthy volunteers. 5-HMT AUCinf and Cmax GMRs for fesoterodine DDIs were all predicted within 1.26-fold of clinical observation, providing verification for the fesoterodine substrate model. The predicted changes in 5-HMT AUCinf and Cmax ratios for 8 mg fesoterodine when coadministered with 50 mg mirabegron were 1.22-fold and 1.17-fold, respectively, relative to 8 mg fesoterodine given alone. This modest increase in 5-HMT exposures by approximately 20% is considered clinically insignificant and would not require fesoterodine dose adjustment when coadministered with mirabegron within approved daily-dose ranges.

6-Chloro-5-[4-(1-Hydroxycyclobutyl)Phenyl]-1H-Indole-3-Carboxylic Acid is a Highly Selective Substrate for Glucuronidation by UGT1A1, Relative to ß-Estradiol.

6-Chloro-5-[4-(1-hydroxycyclobutyl)phenyl]-1H-indole-3-carboxylic acid (PF-06409577) is a direct activator of the human ß1-containing adenosine monophosphate-activated protein kinase (ΑMPK) isoforms. The clearance mechanism of PF-06409577 in animals and humans involves uridine diphosphoglucuronosyl transferase (UGT)-mediated glucuronidation to an acyl glucuronide metabolite of PF-06409577 [(2S,3S,4S,5R,6S)-6-((6-chloro-5-(4-(1-hydroxycyclobutyl)phenyl)-1H-indole-3-carbonyl)oxy)-3,4,5-trihydroxytetrahydro-2H-pyran-2-carboxylic acid (M1)], which retains selective activation of human ß1-containing AMPK isoforms. This paper describes a detailed characterization of the human UGT isoform(s) responsible for glucuronidation of PF-06409577 to M1. Studies using a panel of 13 human recombinant UGT (hrUGT) enzymes indicated that PF-06409577 was converted to M1 in a highly selective fashion by UGT1A1, which was further verified in human liver microsomes treated with specific chemical inhibitors, and in different UGT1A1 expressers. Conversion of PF-06409577 to M1 by UGT1A1 occurred in a relatively selective fashion, compared with ß-estradiol (ES), a conventional probe substrate of UGT1A1. The Michaelis-Menten constant (K M) and V max values describing the formation of M1 from PF-06409577 in hrUGT1A1 and microsomal preparations from human intestine, liver, and kidney ranged from 131 to 212 µM (K M) and 107-3834 pmol/min per milligram (V max) in the presence of 2% bovine serum albumin. Relative activity factors (RAF) were determined for UGT1A1 using PF-06409577 and ES to enable estimation of intrinsic clearance from various tissues. RAF values from PF-06409577 and ES were generally comparable with the exception of intestinal microsomes, where ES overestimated the RAF of UGT1A1 due to glucuronidation by intestinal UGT1A8 and UGT1A10. Our results suggest the potential utility of PF-06409477 as a selective probe UGT1A1 substrate for UGT reaction phenotyping and inhibition studies in preclinical discovery/development.

Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidances from Regulatory Agencies: Focus on CYP3A4 mRNA In Vitro Response Thresholds, Variability, and Clinical Relevance.

The Innovation and Quality Induction Working Group presents an assessment of best practice for data interpretation of in vitro induction, specifically, response thresholds, variability, application of controls, and translation to clinical risk assessment with focus on CYP3A4 mRNA. Single concentration control data and Emax/EC50 data for prototypical CYP3A4 inducers were compiled from many human hepatocyte donors in different laboratories. Clinical CYP3A induction and in vitro data were gathered for 51 compounds, 16 of which were proprietary. A large degree of variability was observed in both the clinical and in vitro induction responses; however, analysis confirmed in vitro data are able to predict clinical induction risk. Following extensive examination of this large data set, the following recommendations are proposed. a) Cytochrome P450 induction should continue to be evaluated in three separate human donors in vitro. b) In light of empirically divergent responses in rifampicin control and most test inducers, normalization of data to percent positive control appears to be of limited benefit. c) With concentration dependence, 2-fold induction is an acceptable threshold for positive identification of in vitro CYP3A4 mRNA induction. d) To reduce the risk of false positives, in the absence of a concentration-dependent response, induction ≥ 2-fold should be observed in more than one donor to classify a compound as an in vitro inducer. e) If qualifying a compound as negative for CYP3A4 mRNA induction, the magnitude of maximal rifampicin response in that donor should be ≥ 10-fold. f) Inclusion of a negative control adds no value beyond that of the vehicle control.

Data Generated by Quantitative Liquid Chromatography-Mass Spectrometry Proteomics Are Only the Start and Not the Endpoint: Optimization of Quantitative Concatemer-Based Measurement of Hepatic Uridine-5'-Diphosphate-Glucuronosyltransferase Enzymes with Reference to Catalytic Activity.

Quantitative proteomic methods require optimization at several stages, including sample preparation, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and data analysis, with the final analysis stage being less widely appreciated by end-users. Previously reported measurement of eight uridine-5'-diphospho-glucuronosyltransferases (UGT) generated by two laboratories [using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT)] reflected significant disparity between proteomic methods. Initial analysis of QconCAT data showed lack of correlation with catalytic activity for several UGTs (1A4, 1A6, 1A9, 2B15) and moderate correlations for UGTs 1A1, 1A3, and 2B7 (Rs = 0.40-0.79, P < 0.05; R2 = 0.30); good correlations were demonstrated between cytochrome P450 activities and abundances measured in the same experiments. Consequently, a systematic review of data analysis, starting from unprocessed LC-MS/MS data, was undertaken, with the aim of improving accuracy, defined by correlation against activity. Three main criteria were found to be important: choice of monitored peptides and fragments, correction for isotope-label incorporation, and abundance normalization using fractional protein mass. Upon optimization, abundance-activity correlations improved significantly for six UGTs (Rs = 0.53-0.87, P < 0.01; R2 = 0.48-0.73); UGT1A9 showed moderate correlation (Rs = 0.47, P = 0.02; R2 = 0.34). No spurious abundance-activity relationships were identified. However, methods remained suboptimal for UGT1A3 and UGT1A9; here hydrophobicity of standard peptides is believed to be limiting. This commentary provides a detailed data analysis strategy and indicates, using examples, the significance of systematic data processing following acquisition. The proposed strategy offers significant improvement on existing guidelines applicable to clinically relevant proteins quantified using QconCAT.

Biosynthesis and Identification of Metabolites of Maraviroc and Their Use in Experiments to Delineate the Relative Contributions of Cytochrome P4503A4 versus 3A5.

Maraviroc (MVC) is a CCR5 coreceptor antagonist indicated in combination with other antiretroviral agents for the treatment of CCR5-tropic human immunodefinciency virus-1 infection. In this study, the metabolism of MVC was investigated in human liver microsomes to delineate the relative roles of CYP3A4 and CYP3A5. MVC is metabolized to five hydroxylated metabolites, all of which were biosynthesized and identified using mass and NMR spectroscopy. The sites of metabolism were the 2- and 3-positions of the 4,4-difluorocyclohexyl moiety and the methyl of the triazole moiety. Absolute configurations were ultimately ascertained by comparison to authentic standards. The biosynthesized metabolites were used for quantitative in vitro experiments in liver microsomes using cyp3cide, a selective inactivator of CYP3A4. (1S,2S)-2-OH-MVC was the main metabolite representing approximately half of the total metabolism, and CYP3A5 contributed approximately 40% to that pathway in microsomes from CYP3A5*1/*1 donors. The other four metabolites were almost exclusively metabolized by CYP3A4. (1S,2S)-2-hydroxylation also correlated to T-5 N-oxidation, a CYP3A5-specific activity. These data are consistent with clinical pharmacokinetic data wherein CYP3A5 extensive metabolizer subjects showed a modestly lower exposure to MVC.

Establishing Transcriptional Signatures to Differentiate PXR-, CAR-, and AhR-Mediated Regulation of Drug Metabolism and Transport Genes in Cryopreserved Human Hepatocytes.

The potential for drug-drug interactions (DDIs) arising from transcriptional regulation of drug-disposition genes via activation of nuclear receptors (NRs), such as pregnane X receptor (PXR), constitutive androstane receptor (CAR), and aryl hydrocarbon receptor (AhR), remains largely unexplored, as highlighted in a recent guidance document from the European Medicines Agency. The goal of this research was to establish PXR-/CAR-/AhR-specific drug-metabolizing enzyme (DME) and transporter gene expression signatures in sandwich-cultured cryopreserved human hepatocytes using selective activators of PXR (rifampin), CAR (CITCO), and AhR (omeprazole). Dose response for ligand-induced changes to 38 major human DMEs and critical hepatobiliary transporters were assessed using a custom gene expression array card. We identified novel differentially expressed drug-disposition genes for PXR (↑ABCB1/MDR1, CYP2C9, CYP2C19, and EPHX1, ↓ABCB11), CAR [↑sulfotransferase (SULT) 1E1, uridine glucuronosyl transferase (UGT) 2B4], and AhR (↑SLC10A1/NTCP, SLCO1B1/OATP1B1], and coregulated genes (CYP1A1, CYP2B6, CYP2C8, CYP3A4, UGT1A1, UGT1A4). Subsequently, DME gene expression signatures were generated for known CYP3A4 inducers PF-06282999 and pazopanib. The former produced an induction signature almost identical to that of rifampin, suggesting activation of the PXR pathway, whereas the latter produced an expression signature distinct from those of PXR, CAR, or AhR, suggesting involvement of an alternate pathway(s). These results demonstrate that involvement of PXR/CAR/AhR can be identified via expression changes of signature DME/transporter genes. Inclusion of such signature genes could serve to simultaneously identify potential inducers and inhibitors, and the NRs involved in the transcriptional regulation, thus providing a more holistic and mechanism-based assessment of DDI risk for DMEs and transporters beyond conventional cytochrome P450 isoforms.

Induction of human cytochrome P450 3A4 by the irreversible myeloperoxidase inactivator PF-06282999 is mediated by the pregnane X receptor.

1. 2-(6-(5-Chloro-2-methoxyphenyl)-4-oxo-2-thioxo-3,4-dihydropyrimidin-1(2H)-yl) acetamide (PF-06282999) is a member of the thiouracil class of irreversible inactivators of human myeloperoxidase enzyme and a candidate for the treatment of cardiovascular disease. PF-06282999 is an inducer of CYP3A4 mRNA and midazolam-1'-hydroxylase activity in human hepatocytes, which is consistent with PF-06282999-dose dependent decreases in mean maximal plasma concentrations (Cmax) and area under the plasma concentration time curve (AUC) of midazolam in humans following 14-day treatment with PF-06282999. 2. In the present study, the biochemical mechanism(s) of CYP3A4 induction by PF-06282999 was studied. Incubations in reporter cells indicated that PF-06282999 selectively activated human pregnane X receptor (PXR). Treatment of human HepaRG cells with PF-06282999 led to ∼14-fold induction in CYP3A4 mRNA and 5-fold increase in midazolam-1'-hydroxylase activity, which was nullified in PXR-knock out HepaRG cells. TaqMan® gene expression analysis of human hepatocytes treated with PF-06282999 and the prototypical PXR agonist rifampin demonstrated increases in mRNA for CYP3A4 and related CYPs that are regulated by PXR. 3. Docking studies using a published human PXR crystal structure provided insights into the molecular basis for PXR activation by PF-06282999. Implementation of PXR transactivation assays in a follow-on discovery campaign should aid in the identification of back-up compounds devoid of PXR activation and CYP3A4 induction liability.

Quantitative Characterization of Major Hepatic UDP-Glucuronosyltransferase Enzymes in Human Liver Microsomes: Comparison of Two Proteomic Methods and Correlation with Catalytic Activity.

Quantitative characterization of UDP-glucuronosyltransferase (UGT) enzymes is valuable in glucuronidation reaction phenotyping, predicting metabolic clearance and drug-drug interactions using extrapolation exercises based on pharmacokinetic modeling. Different quantitative proteomic workflows have been employed to quantify UGT enzymes in various systems, with reports indicating large variability in expression, which cannot be explained by interindividual variability alone. To evaluate the effect of methodological differences on end-point UGT abundance quantification, eight UGT enzymes were quantified in 24 matched liver microsomal samples by two laboratories using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT) standard, and measurements were assessed against catalytic activity in seven enzymes (n = 59). There was little agreement between individual abundance levels reported by the two methods; only UGT1A1 showed strong correlation [Spearman rank order correlation (Rs) = 0.73, P < 0.0001; R2 = 0.30; n = 24]. SIL-based abundance measurements correlated well with enzyme activities, with correlations ranging from moderate for UGTs 1A6, 1A9, and 2B15 (Rs = 0.52-0.59, P < 0.0001; R2 = 0.34-0.58; n = 59) to strong correlations for UGTs 1A1, 1A3, 1A4, and 2B7 (Rs = 0.79-0.90, P < 0.0001; R2 = 0.69-0.79). QconCAT-based data revealed generally poor correlation with activity, whereas moderate correlations were shown for UGTs 1A1, 1A3, and 2B7. Spurious abundance-activity correlations were identified in the cases of UGT1A4/2B4 and UGT2B7/2B15, which could be explained by correlations of protein expression between these enzymes. Consistent correlation of UGT abundance with catalytic activity, demonstrated by the SIL-based dataset, suggests that quantitative proteomic data should be validated against catalytic activity whenever possible. In addition, metabolic reaction phenotyping exercises should consider spurious abundance-activity correlations to avoid misleading conclusions.