A semiphysiological population pharmacokinetic model of agomelatine and its metabolites in Chinese healthy volunteers

Feifan Xie, An Vermeulen, Pieter Colin, Zeneng Cheng, Feifan Xie, An Vermeulen, Pieter Colin, Zeneng Cheng

Abstract

Aims: Agomelatine is an antidepressant for major depressive disorders. It undergoes extensive first-pass hepatic metabolism and displays irregular absorption profiles and large interindividual variability (IIV) and interoccasion variability of pharmacokinetics. The objective of this study was to characterize the complex pharmacokinetics of agomelatine and its metabolites in healthy subjects.

Methods: Plasma concentration-time data of agomelatine and its metabolites were collected from a 4-period, cross-over bioequivalence study, in which 44 healthy subjects received 25 mg agomelatine tablets orally. Nonlinear mixed effects modelling was used to characterize the pharmacokinetics and variability of agomelatine and its metabolites. Deterministic simulations were carried out to investigate the influence of pathological changes due to liver disease on agomelatine pharmacokinetics.

Results: A semiphysiological pharmacokinetic model with parallel first-order absorption and a well-stirred liver compartment adequately described the data. The estimated IIV and interoccasion variability of the intrinsic clearance of agomelatine were 130.8% and 28.5%, respectively. The IIV of the intrinsic clearance turned out to be the main cause of the variability of area under the curve-based agomelatine exposure. Simulations demonstrated that a reduction in intrinsic clearance or liver blood flow, and an increase in free drug fraction had a rather modest influence on agomelatine exposures (range: -50 to 200%). Portosystemic shunting, however, substantially elevated agomelatine exposure by 12.6-109.1-fold.

Conclusions: A semiphysiological pharmacokinetic model incorporating first-pass hepatic extraction was developed for agomelatine and its main metabolites. The portosystemic shunting associated with liver disease might lead to significant alterations of agomelatine pharmacokinetics, and lead to substantially increased exposure.

Keywords: agomelatine; first-pass; metabolite; pharmacokinetics; semiphysiological.

Conflict of interest statement

A.V. is an 80% employee of Johnson and Johnson and owns J&J stock/stock options. She is also a visiting Professor at Ghent University. The other authors have no competing interests to declare.

© 2019 The British Pharmacological Society.

Figures

Figure 1
Figure 1
Schematic representation of the semiphysiological pharmacokinetic model for agomelatine and its metabolites. F1, the fraction of dose absorbed via gut depot 1; K13, first‐order absorption rate constant through gut depot 1; K23, first‐order absorption rate constant through gut depot 2; ALAG1, absorption lag time of gut depot 1; ALAG2, absorption lag time of gut depot 2; QH, liver blood flow; CLH, hepatic plasma clearance; EH, hepatic extraction ratio; FH, fraction of absorbed drug escaping hepatic first‐pass; PBR, plasma to blood drug concentration ratio of agomelatine; FM3OH, the fraction of agomelatine converted to 3‐hydroxy‐agomelatine; FM7DM, the fraction of agomelatine converted to 7‐desmethyl‐agomelatine; CL3OH, clearance of 3‐hydroxy‐agomelatine; CL7DM, clearance of 7‐desmethyl‐agomelatine; Q7DM, compartmental clearance between the central and peripheral compartment of 7‐desmethyl‐agomelatine; QAGM, compartmental clearance between the central and peripheral compartment of agomelatine
Figure 2
Figure 2
Goodness‐of‐fit plots of the final population pharmacokinetics model for agomelatine and its metabolites. Top panels: observed concentrations vs individual predictions of agomelatine A, 3‐hydroxy‐agomelatine B, and 7‐desmethyl‐agomelatine C; Middle panels: conditional weighted residuals (CWRES) vs time after dose of agomelatine D, 3‐hydroxy‐agomelatine E, and 7‐desmethyl‐agomelatine F; Bottom panels: CWRES vs population predicted concentrations of agomelatine G, 3‐hydroxy‐agomelatine H, and 7‐desmethyl‐agomelatine I
Figure 3
Figure 3
Representative plasma concentrations and individual predictions of agomelatine and its metabolites on different occasions. The dots are observed concentrations, and the solid lines are individual predictions
Figure 4
Figure 4
Visual predictive check plots for the final population pharmacokinetics model of agomelatine A, and D, 3‐hydroxy‐agomelatine B, and 7‐desmethyl‐agomelatine C, and E. The upper panels represent simulation‐based 90% prediction intervals (grey shaded areas) of the continuous data. The black solid line represents the median of the observations, and the black dashed line represents the median of the model predictions. The horizontal dashed lines indicate the lower limit of quantification (LLOQ) of agomelatine (0.046 ng/mL), 3‐hydroxy‐agomelatine (0.460 ng/mL), and 7‐desmethyl‐agomelatine (0.137 ng/mL). The lower panels display simulation based 90% confidence intervals (grey shaded areas) around the median (dashed black lines) for the fraction of below LLOQ observations. The observed fraction samples below LLOQ are represented with solid black lines
Figure 5
Figure 5
Typical concentration–time profiles of agomelatine for healthy status and for liver disease. Top left panel: the impact of reductions in intrinsic clearance (CLint) on agomelatine pharmacokinetics profile. Top right panel: the impact of increases in free plasma agomelatine fraction (fu) on agomelatine pharmacokinetics profile. Bottom left panel: the impact of decreases in hepatic blood flow (QH) on agomelatine pharmacokinetics profile. Bottom right panel: the impact of extents of shunted fraction (fshunt) of hepatic blood flow on agomelatine pharmacokinetics profile

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