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Research ArticleArticle

An Investigation into the Prediction of the Plasma Concentration-Time Profile and Its Interindividual Variability for a Range of Flavin-Containing Monooxygenase Substrates Using a Physiologically Based Pharmacokinetic Modeling Approach

Venkatesh Pilla Reddy, Barry C. Jones, Nicola Colclough, Abhishek Srivastava, Joanne Wilson and Danxi Li
Drug Metabolism and Disposition September 2018, 46 (9) 1259-1267; DOI: https://doi.org/10.1124/dmd.118.080648
Venkatesh Pilla Reddy
Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)
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Barry C. Jones
Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)
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Nicola Colclough
Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)
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Abhishek Srivastava
Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)
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Joanne Wilson
Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)
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Danxi Li
Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)
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  • Fig. 1.
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    Fig. 1.

    Mean simulated using hepatocyte CLint data (solid line) and observed (data points) concentrations of FMO substrates after administration of a single dose to humans for nine FMO substrates. The gray lines around the solid black line represent simulated individual trials matched to a clinical study. Lower and upper gray lines represent the 90% confidence interval of the respective simulations.

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    Fig. 2.

    Forest plot showing the PBPK modeling performance of FMO substrates. Predictions are expressed as ratios of predicted over observed AUC. The dashed line represents the identity (predicted/observed ratio), the gray shaded represents the 0.5–2.0 ratio window, and the blue shaded area represents the 0.67- to 1.50-fold ratio. Mean AUC using hepatocytes (blue squares); mean AUC using HLM (red circles); mean AUC using rFMO with no scaling (green triangles), with error bars represented as percentile range (fifth and 95th percentiles).

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    Fig. 3.

    Determination of rFMO scalar for itopride and its application to tozasertib as an example. (A–C) Model fit without rFMO scalar, with rFMO tissue scalar, and with rFMO ISEF scalar for itopride, respectively. (D–F) Tozasertib model without rFMO scalar, with rFMO tissue scalar, and with rFMO ISEF scalar, respectively.

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    Fig. 4.

    Correlations for the PBPK model–predicted clearance using human hepatocytes, HLM, and rFMO with ISEF scalar and tissue-specific scalar.

Tables

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    TABLE 1

    Clinical data used for PBPK model verification

    DrugAge RangeNumber of SubjectsMale/Female NumbersDose (Route)Dosage Regimen/PK DurationCommentsReference
    yr
    Benzydamine41–5166/05 mg (i.v.)Single/48 hoursCaucasian healthy volunteersHumphries et al. (2015)
    Benzydamine18–51126/650 mg (oral)Single/48 hoursCaucasian healthy volunteersHumphries et al. (2015)
    Itopride—66/050 mg (oral)Single/24 hoursJapanese healthy volunteersYoon et al. (2014)
    Itopride24–3155/0150 mg (oral)Single/24 hoursJapanese healthy volunteersKatagiri et al. (2006)
    Tozasertib22–802714/134, 8, 16, 32, 45, 64, and 96 mg/m2 (i.v.)Single, 24-hour infusionOncology patientsTraynor et al. (2011)
    Tamoxifen29–71294/2520 mg (oral)Multiple, PK at SSOncology patientsAstraZeneca internal dataa
    Tamoxifen41–64240/2430 mg (oral)SingleHealthy volunteersFuchs et al. (1996)
    Moclobemide21–301212/0150 mg (i.v.), 20 minute infusionSingleHealthy volunteersRaaflaub et al. (1984)
    Moclobemide21–301212/0100 mg (oral)SingleHealthy volunteersSchoerlin et al. (1987)
    Imipramine23–6488/0100 mg (oral)SingleCaucasian healthy volunteersAlbers et al. (2000)
    Imipramine22–37115/650 mg (i.v.) and 100 mg (oral)SingleCaucasian healthy volunteersBrøsen and Gram (1988)
    Clozapine21–301818/0100 mg (oral); twice dailySingleAsian healthy volunteersTassaneeyakul et al. (2005)
    Clozapine30–3222/0200 and 600 mg (oral)Multiple, PK at SSCaucasian schizophrenic patientsTakano et al. (2006)
    Olanzapine28–501010/010 mg, oralSingleSchizophrenic patientsElshafeey et al. (2009)
    Olanzapine19–412424/010 mg (oral)SingleHealthy volunteersChiu et al. (2004)
    Ranitidine21–2366/020 mg (i.v.) and 100 mg (oral)SingleHealthy volunteersMcNeil et al. (1981)
    Ranitidine19–321212/0100–400 mg (oral)Single and multipleHealthy volunteersGarg et al. (1985)
    • SS, steady-state. —, data not available or not reported.

    • ↵a Clinical trial NCT02093351: To assess safety and effect of olaparib on the pharmacokinetics of anastrozole, letrozole, and tamoxifen, and their effect on olaparib, in patients with advanced solid cancer (2017).

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    TABLE 2

    PBPK model input parameters

    ParameterDescriptionUnitParameter Value
    BenzydamineItoprideTozasertibTamoxifenMoclobemideImipramineClozapineOlanzapineRanitidine
    Physicochemical dataa 309.4358.4464.6371.5268.7280.4326.8312.4314.4
     MWMolecule weightg/mol
     log P/log DOctanol: buffer partition coefficient4.24/2.342.12/0.724.3/3.366.8/4.622.17/1.655.03/2.513.5/2.963.5/2.150.67/−0.78
     pKa/typeDissociation constant9.3/base8.8/base8.3/base8.8/base6/base9.4/base7.75/base7.2/base8.2/2.7 diprotic base
     BPBlood-to-plasma partition ratio0.760.720.940.890.840.930.8250.730.90
     FuFraction unbound in plasma0.1460.2620.08730.000350.6380.2610.09250.3270.912
    Absorption
     KaAbsorption rate constant1/h1.214, lag time of 0.4 hours—0.391.1212.2.21.360.38
     Fu,gutUnbound fraction of drug in gut enterocytes. Either default of 1 or predicted value used10.1921111111
     Pcaco-2Caco-2 permeability× 10−6 cm/sMech-eff model——Mech-eff model64.4Mech-eff modelPSA/HBDPSA/HBDPSA/HBD
     Peff,manHuman jejunum permeability× 10−4 cm/s8.715—4.096.958.567.877.830.94
    Distribution
     VssDistribution volume at steady-state after IV or predicted using Method 2l/kg0.9666.35.615.73.5917.11.65.11.50
     VssDistribution modell/kgMinimal PBPK modelFull PBPKFull PBPKFull PBPKFull PBPKMinimal PBPKMinimal PBPKMinimal PBPKFull PBPK
    Elimination
     CLint-HLMHuman liver microsomal protein in vitro intrinsic clearanceµl/min/mg protein181861431418<3<3
     CLint- HepatocytesHepatocytes in vitro intrinsic clearanceµl/min per 106 cells91129439520.6
     Fm (% FMO) Fraction metabolized contribution%539638283821232326
     CLint - rFMOFMO in-vitro intrinsic clearance and remaining metabolic CL was accounted via major metabolizing enzyme via HLM in enzyme kinetics or via rCYP if P450 contribution knownµl/min/pmol protein or µl/min/mg protein for HLMFMO1 = 0.44,FMO3 = 0.29,FMO5 = 0.001,CYP2D6 = 8.5FMO1 = 0.79,FMO3 = 0.118,FMO5 = 0.0.052,CYP3A4 = 0.87FMO1 = 0.24,FMO3 = 0.48,FMO5 = 0,CYP3A4 = 39FMO1 = 0.083,FMO3 = 0,FMO5 = 0,CYP3A4 = 3.6FMO1 = 0.018,FMO3 = 0.031,FMO5 = 0.003,CYP3A4 = 2.9FMO1 = 0.163,FMO3 = 0.013, FMO5 = 0.001,CYP1A2 = 0.058,2C19 = 2.36,2D6 = 47,3A4 = 0.021,Additional HLM CL = 1.52FMO1 = 0.031,FMO3 = 0,FMO5 = 0,CYP3A4 = 11.1FMO1 = 0.04,FMO3 = 0.006,FMO5 = 0,CYP3A4 = 2.31FMO1 = 0.011,FMO3 = 0.003,FMO5 = 0.028,CYP3A4 = 2.22
     Systemic  clearanceSystemic absolute CL or oral CLl/h9.66b88c87b8c63.7b54c32c26c7.56b
     Renal  clearanceRenal CLl/h0.241.5——————24.6
     Fu,micUnfound fraction in microsomes0.351.050.180.020.980.310.300.730.97
     Fu,incUnfound fraction in hepatocytes0.740.880.210.0030.870.650.330.860.98
    • HBD, hydrogen bond donor; PSA, polar surface area; rCYP, recombinant cytochrome P450; Vss, volume of distribution at steady state. —, data not available or not reported.

    • ↵a Source: AstraZeneca experimental data (Jones et al., 2017).

    • ↵b From intravenous study using references shown in Table 3 for a respective drug.

    • ↵c From oral study using references shown in Table 3 for a respective drug.

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    TABLE 3

    Observed mean PK parameters for FMO substrates using hepatocyte data

    DrugDosing RegimenDoseObserved AUC (S.D.)Observed Cmax (S.D.)Observed CL (S.D.)Predicted AUC with Hep (S.D)Predicted Cmaxa with Heps (S.D)Predicted CL (S.D.)Reference for the Observed Data
    mgng⋅h/mlng/mll/hng⋅h/mlng/mll/h
    BenzydamineIntravenous5540 (112)68 (19)9.6594 (191)74 (18)8.89 (3.2)Baldock et al. (1991)
    BenzydamineOral504994 (1190)546 (177)9.84245 (1748)398 (126)9.4 (3.2)Baldock et al. (1991)
    ItoprideOral50750 (123)280 (49)NR1440 (424)353 (61)37.6 (11)http://www.meppo.com/pdf/drugs/2845-GANATON-1415104080.pdf
    ItoprideOral1502170 (349)930 (50)55–881940 (442)b1061 (184)81 (18)Katagiri et al. (2006)
    TozasertibIV421277,673 (18,560)3547 (1113)a53.6 (17.6)85,135 (20,883)3480 (797)47 (11)Traynor et al. (2011)
    TamoxifenOral (multiple doses)202336 (699)134.8 (35.5)7.68 (2.2)1938 (488)94 (22)11 (4) AstraZeneca internal datac
    TamoxifenOral303370 (701)63.6 (11.1)NR2379 (580)58 (15)14 (4)Fuchs et al. (1996)
    MoclobemideIntravenous1503807210039.4 (5.9)4180 (738)3825 (376)36(6)Raaflaub et al. (1984)
    MoclobemideOral100157082363.71859 (459)531 (138)57 (18)Schoerlin et al. (1987)
    ImipramineIntravenous128 (12–22)(0.35–0.60)39.5 (33.6–63)16 (4)0.9 (0.3)65 (13)Nguyen et al. (2016)
    ImipramineOral100985 (662)63.2 (40)126 (88)1663 (614)46 (17)69 (28)Albers et al. (2000)
    ClozapineOral1003994 (2144)185 (132)31.81 (16)5465 (2097)493 (179)21 (9)Tassaneeyakul et al. (2005)
    OlanzapineOral10823 (480);AUC0–120 h21.4 (14)13 (4.6)623 (197)20 (6)18 (7)Chiu et al. (2004)
    RanitidineIntravenous20488 (40)61543 (3.7)470 (99)891 (108)49 (14)McNeil et al. (1981)
    RanitidineOral1001726 (418)342 (122)NR1551 (388)280 (48)68 (17)McNeil et al. (1981)
    • heps, hepatocytes; NR, not reported. —, data not available or not reported.

    • ↵a Cmax = concentration at the end of infusion.

    • ↵b AUC0–4 h to match the reported AUC.

    • ↵c Clinical trial NCT02093351: To assess safety and effect of olaparib on the pharmacokinetics of anastrozole, letrozole, and tamoxifen, and their effect on olaparib, in patients with advanced solid cancer (2017).

Additional Files

  • Figures
  • Tables
  • Data Supplement

    • Supplemental Data -

      Supplementary Table 1 - Human in vitro data for FMO substrates (Jones et al., 2017)

      Supplementary Table 2 - Options used to define the elimination within PBPK platform (Simcyp V16)

      Supplementary Figure 1 - Forest plot showing the physiologically based pharmacokinetic modeling performance of FMO substrates using rFMO data with and without scalar (tissue specific or ISEF) in the model

      Supplementary Table 3 - Simulated mean (SD) PK parameters for FMO substrates using HLM or rFMO with ISEF or tissue specific scalar data

      Supplementary Table 4 - Paediatrics simulations for Itopride using rFMO data

      Supplementary Table 5 - Mass Spectrometer parameters for FMO substrates

      Supplementary Text

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Drug Metabolism and Disposition: 46 (9)
Drug Metabolism and Disposition
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1 Sep 2018
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Research ArticleArticle

PBPK Modeling of FMO Substrates

Venkatesh Pilla Reddy, Barry C. Jones, Nicola Colclough, Abhishek Srivastava, Joanne Wilson and Danxi Li
Drug Metabolism and Disposition September 1, 2018, 46 (9) 1259-1267; DOI: https://doi.org/10.1124/dmd.118.080648

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Research ArticleArticle

PBPK Modeling of FMO Substrates

Venkatesh Pilla Reddy, Barry C. Jones, Nicola Colclough, Abhishek Srivastava, Joanne Wilson and Danxi Li
Drug Metabolism and Disposition September 1, 2018, 46 (9) 1259-1267; DOI: https://doi.org/10.1124/dmd.118.080648
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