Journal List > Transl Clin Pharmacol > v.23(2) > 1082614

Lee, Lim, Seong, Park, Gwon, Han, Lee, Kim, Yoon, and Yoo: Population pharmacokinetic analysis of the multiple peaks phenomenon in sumatriptan

Abstract

The objective of this study was to develop a population pharmacokinetic (PK) model for sumatriptan, which frequently shows an atypical absorption profile with multiple peaks. Sumatriptan, a selective agonist for the vascular serotonin (5-HT1) receptor that causes vasoconstriction of the cerebral arteries, is used for the acute treatment of migraine attack with or without aura. Despite its relatively high between-subject variability, few reports have addressed PK modeling of sumatriptan. Plasma data obtained after a single 50-mg oral dose of sumatriptan in 26 healthy Korean male subjects were used. Blood samples were collected 0 (predose), 0.25, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 4, 6, 8, 10, and 12 h after dosing. Plasma sumatriptan concentrations were analyzed using UPLC/MS/MS. Population PK analysis was performed using plasma concentration data for sumatriptan with NON-MEM (ver. 7.2). A total of 364 concentrations of sumatriptan were captured by a one-compartment model with first-order elimination, and a combined transit compartment model and first-order absorption with lag time was successful in describing the PK with multiple peaks in the absorption phase of sumatriptan. The creatinine clearance as a covariate significantly (P < 0.01) influenced the absorption fraction (f). The final model was validated through a visual predictive check and bootstrapping with no serious model misspecification.

References

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Figure 1.
Individual plasma concentration versus time plots of sumatriptan. The bold red line is the median value.
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Figure 2.
The scheme of the final PK model of sumatriptan. ka1, absorption rate constant from the depot; ka2, absorption rate constant from the final transit compartment to the central compartment; ktr, identical transfer rate constant of the transit compartment model; f, fraction of the dose absorbed through the absorption compartment; n, number of transit compartments placed before the central compartment; an, the drug amount in the nth compartment; CL, clearance.
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Figure 3.
Final model diagnosis plot produced using the final pharmacokinetic model. (A) Observations (DV) vs. population predictions (PRED) (B) DV vs. individual predictions (IPRED) (C) Conditional weighted residuals (CWRES) vs. PRED and (D) CWRES vs. time (TIME).
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Figure 4.
Visual predictive check plot of the final model 0 and 12 h after a single oral administration of 50 mg sumatriptan. A total of 1,000 datasets were simulated using the final PK parameter estimates. Circles represent the observed sumatriptan plasma concentrations: the 90% confidence interval of the simulated concentrations (gray area), and observed concentration (solid line) of the 5th, median, and 95th percentiles.
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Figure 5.
PK curves from representative individuals showing multiple peaks. Circle, observed value; solid red line, individual predicted value.
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Table 1.
Demographic characteristics of subjects
Variable Distributiona
Age (years) 23.9 (22–28)
Sex (male/female) 26 / 0
Weight (kg) 66.7 (51–84)
Height (cm) 174.2 (166.2–184.8)

a Mean (range) is presented for continuous variables and number of subjects for categorical variables.

Table 2.
PK model development process
Model Model tested Objective function value
M1 Two-compartment model with first-order absorption followed by zero-order absorption with lag time 1169.47
M2 Two-compartment model with zero-order absorption followed by first-order absorption with lag time 1175.19
M3 M1 with nonlinear elimination by the Michaelis-Menten equation 1144.67
M4 M2 with nonlinear elimination by the Michaelis-Menten equation 1172.26
M5 One-compartment model with a combined transit compartment model and first-order absorption 1078.99
M6 M5 with CrCL as a covariate for f 1071.57
M7 M5 with nonlinear elimination by the Michaelis-Menten equation 1068.82
Table 3.
Final parameter estimates and bootstrap results
Parameter (unit) Definition Estimate (%RSE) BSV (CV%) (%RSE) Bootstrap 95% CI Shrinkage of BSV (%)
CL/F (L/h) Apparent oral clearance 418 (4) 18.5 (25.9) 383 – 455 6.41
V/F (L) Apparent volume of distribution 56.9 (35.4) 70.9 (28.9) 17.2 – 93.7 2.16
ka1 (h−1) Absorption rate constant of first-order absorption 0.62 (9.13) 0.53 – 0.75
ka2 (h−1) Absorption rate constant from the final transit compartment to the central compartment 0.29 (6.89) 24.6 (39.3) 0.25 – 0.33 14.2
MTT (h) Mean transit time 1.94 (9.89) 35.6 (29.6) 1.54 – 2.30 7.1
n Number of transit compartments 11 (23.2) 6.47 – 25.4
ALAG1 (h) Lag time for ka1 0.24 (1.32) 0.23 – 0.25
f Fraction of the dose absorbed by transit compartment model 0.56 (6.18) 14.4 (40.7) 0.49 – 0.67 18.6
f,CrCL CrCL as a covariate for f –0.985 (34.6)
Proportional error 0.21 (7.3) 0.17 – 0.24
Additive error 0.3 (15.2) 0.17 – 0.37

BSV, Between-Subject Variability; -, Not estimated.

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