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Figure 1.

Work flow of PKPD modeling.

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Figure 2.

Model structure of the PKPD model.

(A) Semi-PBPK model for the systemic kinetics of GL and GA in rat. (B) Semi-PBPK model for the systemic kinetics of GL and GA in human. (C)11β-HSD2 associated renin-angiotensin-aldosterone-electrolyte biological system PD model.

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Table 1.

Abbreviations of parameters of the physiologically based pharmacokinetic model for GL, GA and GAM.

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Table 2.

Physiological parameters in a 250 g rat and 70 kg human.

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Table 3.

Biochemical parameters for the physiologically based model for GL, GA and GAM in rat.

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Figure 3.

GL plasma concentration and accumulated biliary excretion after i.v. GL in rats with bile fistulas.

Plasma concentration-time profiles of GL at (A) 5–50 mg/kg [15], (C) 10 mg/kg [13], (D) 25 and 100 mg/kg [18], [19], [31]; accumulated biliary excretion of GL at (B) 5–50 mg/kg [15] and (C) 10 mg/kg [13]. Experimental data (fitset and testset) are shown as symbols; the lines represent the prediction of the GL model.

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Figure 4.

GA plasma and kidney concentration after i.v. GA and p.o. GA and GL in rats.

(A) Plasma concentration-time profiles of GA after i.v. 2–20 mg/kg GA in rats with bile fistulas [29]; (B) i.v. 60 mg/kg GA in rats with bile fistulas [18], i.v. 5.7 mg/kg GA in rats without bile fistulas and p.o. 5.7 mg/kg GA in rats [30]; (C) p.o. 10 [30] and 100 (experimental studies) mg/kg GL; (D) plasma and kidney exposure of GA after p.o. 200 mg/kg GL (experimental studies). Experimental data (fitset and testset) are shown as symbols; the lines represent the forecast of the GA model.

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Figure 5.

Plamsa concentration and accumulated biliary excretion of GAM.

Left, plasma concentration and accumulated biliary excretion of 3MGA after i.v. 5 mg/kg 3MGA in rats [5]; Right, accumulated biliary excretion of GAM after i.p. 25 mg/kg GA in rats [25]. Experimental data are shown as symbols; the lines represent the predictions of the GA model.

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Figure 6.

Plasma concentrations of GL and GA in human.

(A) GL plasma concentration after i.v. 40–120 mg GL in human [16]; (B) GA plasma concentration after p.o. administration of 130 mg/kg GA at (B, left) single dose and (B, right) multiple dose [10]; GA plasma concentration after p.o. (C, left) 225 mg GL and (C, right) 150 g licorice containing 225 mg GL [9]. Experimental data (fitset and testset) are shown as symbols; the lines represent the predictions of the human PBPK model.

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Table 4.

Biochemical parameters of the physiologically based model for GL, GA and GAM in human.

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Figure 7.

Time courses of urinary excretion of cortisol, cortisone and their ratio in different scenarios: (A) p.o. GA 130 mg/day for 5 days and withdrawn for another 5 days [10]; (B–D) p.o. GA 500 mg/day, 2 times/day for 7 days [34].

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Figure 8.

The effects of different levels of (A) angiotensin II [40] and (B) potassium [41] on aldosterone concentration.

Experimental data (fitset) are shown as symbols; the lines represent the predictions of the human PBPK model. i.f. in B stands for intravenous infusion.

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Table 5.

Optimized parameters in the PD model.

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Table 6.

Estimated urinary cortisol∶cortisone ratio for p.o. administration of GA at 510 mg/day administered 3 times/day for 2 days compared with the observed value.

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Table 7.

Estimated biomarkers of pseudoaldosteronism for p.o. administration of GA at 500 mg/day 2 times/day for one week compared with the observed value.

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Table 8.

Estimated biomarkers of pseudoaldosteronism for p.o. administration of GL at 0.7 g/day (9 subjects) or 1.4 g/day (5 subjects) for one to four weeks compared with observed values.

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Figure 9.

The simulated effect of three sensitivity factors on GA pharmacokinetics and potassium level.

Sensitivity factors: (A, B) sinusoidal transport function, (C, D) colonic transit time and (E) activity of 11β-HSD 2. The causal effect: (A, C) GA plasma concentration and (B, D, E) serum potassium level. GL was administered p.o. at 200 mg/day for one week. N stands for the normal value of the corresponding parameter.

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Figure 10.

The simulated probability distribution of the individual dose limit in 1000 virtual elderly people.

(A) The simulated dose data and fitted probability density by lognormal distribution; (B) The simulated dose data and fitted cumulative probability by log normal distribution; (C) The second derivative of the cumulative probability function and the critical value.

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Table 9.

Distribution of CLup, Kco, and kox,0 related physiological factors in simulation of the individual dose limit for 1000 subjects by the Monte Carlo method.

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