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Research ArticleMetabolism, Transport, and Pharmacogenomics
Open Access

Quantitative Assessment of Population Variability in Hepatic Drug Metabolism Using a Perfused Three-Dimensional Human Liver Microphysiological System

N. Tsamandouras, T. Kostrzewski, C. L. Stokes, L. G. Griffith, D. J. Hughes and M. Cirit
Journal of Pharmacology and Experimental Therapeutics January 2017, 360 (1) 95-105; DOI: https://doi.org/10.1124/jpet.116.237495
N. Tsamandouras
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
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T. Kostrzewski
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
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C. L. Stokes
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
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L. G. Griffith
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
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D. J. Hughes
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
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M. Cirit
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
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    Fig. 1.

    Predose (measured at day 4) albumin, urea, and LDH levels stratified across different donors. Hu1601, Hu1604, Hu1624, Hu8150, and Hu8181 are lot numbers corresponding to five different donors. “Pooled” refers to the pool of hepatocytes from the five donors, and “All donors” refers to the data from all five donors merged together. Red lines correspond to the mean of the data, purple boxes extend the mean by ± 1 S.D., and pink boxes correspond to 95% confidence intervals around the mean. LDH levels are expressed in optical density (OD) units at 490 nm.

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    Fig. 2.

    Comparison between the predose (measured at day 4) and the postdose (measured at day 6 for diclofenac, propranolol, lidocaine, and ibuprofen and days 5 and 7 for phenacetin and prednisolone, respectively) albumin, urea, and LDH levels stratified across different treatments. Data from both the five donors and the pooled hepatocytes are shown. Red lines correspond to the mean of the data, purple boxes extend the mean by ± 1 S.D., and pink boxes correspond to 95% confidence intervals around the mean. Thin black lines connect the pre- and postdose levels in a given donor (or pool of donors) and well. Asterisks inside each subplot indicate significant differences between pre- and postdose levels (*P < 0.05, **P < 0.01, ***P < 0.001). LDH levels are expressed in optical density (OD) units at 490 nm.

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    Fig. 3.

    Volcano plot that illustrates the average fold-change in gene expression between the liver MPS (day 6) and freshly thawed hepatocytes along with the associated statistical significance. The log2 of the fold-change is plotted on the x-axis; thus, positive values indicate upregulation in the liver MPS compared with the freshly thawed hepatocytes, whereas negative values indicate downregulation. Genes outside the two black vertical lines are up- or downregulated more than 3-fold. On the y-axis, the –log10 of the P value is plotted; thus, the higher values indicate stronger statistical evidence of a significant difference in gene expression between the liver MPS and freshly thawed hepatocytes. The genes for which significant differences were detected after multiple testing correction are highlighted in red, and the respective gene names are reported.

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    Fig. 4.

    Drug depletion data available for the pharmacokinetic analysis. Hu1601, Hu1604, Hu1624, Hu8150, and Hu8181 are lot numbers corresponding to five different donors. “Pool” refers to the pool of hepatocytes from the five donors. The small numbers on the right of each concentration point (values of 1, 2, or 3) aim to distinguish different wells across the same donor (or pool of donors).

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    Fig. 5.

    Visual predictive checks of the developed mixed-effect models with regard to the observed individual-donor drug depletion data. Closed gray circles represent the observed concentrations in medium; highlighted with purple are the areas between the 5th and 95th percentiles of model simulations that take into account the different levels of variability (90% prediction intervals), whereas the red solid line represents their median (median prediction); the horizontal dashed black line represents the limit of quantification.

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    Fig. 6.

    Population PBPK model prediction of lidocaine arterial plasma concentrations during and after a constant-rate i.v. infusion (lidocaine HCl, 3 mg/kg for 3 minutes). The clinically observed data represented with closed gray circles were extracted from Tucker and Boas (1971) across five different subjects. The shaded area corresponds to the 95% population prediction intervals of the model, and the red line corresponds to the median model prediction. The insert plot magnifies the first 16 minutes for the purpose of clarity.

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    TABLE 1

    Parameter estimates from the modeling of the drug depletion data

    ParameterPropranololPrednisolonePhenacetinLidocaineIbuprofenDiclofenac
    Individual-donor data
     CLint(u)a3.88 (28.6%)0.81 (14.7%)8.91 (12.7%)4.38 (12.9%)5.02 (16.2%)17.80 (16.8%)
     IDVb66.8% (40.9%)29.3% (58.1%)24.1% (80.4%)28.5% (38.1%)32.6% (44.9%)36.2% (71.5%)
     IWVb32.9% (62.7%)21.5% (70.0%)26.1% (65.2%)11.3% (26.5%)30.7% (55.8%)6.0% (120.9%)
     RVb21.6% (56.6%)10.3% (25.8%)14.2% (69.8%)8.4% (34.0%)9.6% (29.3%)20.0% (26.2%)
    Pooled hepatocytes data
     CLint(u)a6.34 (5.9%)0.91 (4.0%)9.67 (17.4%)4.24 (3.6%)3.54 (33.3%)18.60 (14.4%)
     IWVb9.6% (50.4%)–c30.7% (41.5%)5.9% (43.7%)62.5% (40.0%)23.6% (54.4%)
     RVb19.7% (41.1%)11.4% (32.0%)9.5% (40.4%)6.9% (14.4%)7.5% (15.8%)16.3% (28.6%)
    Individual-donor/pooled hepatocytes
     CLint(u) ratiod0.61 (0.27, 0.97)0.89 (0.63, 1.16)0.92 (0.61, 1.47)1.03 (0.77, 1.31)1.42 (0.75, 4.20)0.96 (0.60, 1.48)
    • ↵a The typical unbound intrinsic clearance [CLint(u)] for each drug is reported in μl/min/106 cells.

    • ↵b Interdonor variability in unbound intrinsic clearance (IDV), interwell variability in unbound intrinsic clearance (IWV), and the residual variability in the observed data (RV) are reported in terms of CV%, which was calculated as Embedded Image, where “variance” is the estimate of ω2, π2, and σ2 for IDV, IWV, and RV, respectively (see Materials and Methods). Values in parentheses correspond to relative standard errors calculated as Embedded Image.

    • ↵c Interwell variability could not be estimated and was fixed to 0.

    • ↵d Ratio of CLint(u) determined in the individual donor data to the CLint(u) determined in the pooled hepatocytes data. Values in parentheses correspond to 95% confidence intervals of this ratio, calculated using Fieller’s theorem and assuming normality of the CLint(u) estimators. The average CLint(u) ratio across all compounds is 0.97.

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Journal of Pharmacology and Experimental Therapeutics: 360 (1)
Journal of Pharmacology and Experimental Therapeutics
Vol. 360, Issue 1
1 Jan 2017
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Research ArticleMetabolism, Transport, and Pharmacogenomics

Assessment of Variability in Drug Metabolism with Liver MPS

N. Tsamandouras, T. Kostrzewski, C. L. Stokes, L. G. Griffith, D. J. Hughes and M. Cirit
Journal of Pharmacology and Experimental Therapeutics January 1, 2017, 360 (1) 95-105; DOI: https://doi.org/10.1124/jpet.116.237495

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Research ArticleMetabolism, Transport, and Pharmacogenomics

Assessment of Variability in Drug Metabolism with Liver MPS

N. Tsamandouras, T. Kostrzewski, C. L. Stokes, L. G. Griffith, D. J. Hughes and M. Cirit
Journal of Pharmacology and Experimental Therapeutics January 1, 2017, 360 (1) 95-105; DOI: https://doi.org/10.1124/jpet.116.237495
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