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      Exposure–outcome analysis in depressed patients treated with paroxetine using population pharmacokinetics

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          This study investigated population pharmacokinetics of paroxetine, and then performed an integrated analysis of exposure and clinical outcome using population pharmacokinetic parameter estimates in depressed patients treated with paroxetine.

          Patients and methods

          A total of 271 therapeutic drug monitoring (TDM) data were retrospectively collected from 127 psychiatric outpatients. A population nonlinear mixed-effects modeling approach was used to describe serum concentrations of paroxetine. For 83 patients with major depressive disorder, the treatment response rate and the incidence of adverse drug reaction (ADR) were characterized by logistic regression using daily dose or area under the concentration–time curve (AUC) estimated from the final model as a potential exposure predictor.


          One compartment model was developed. The apparent clearance of paroxetine was affected by age as well as daily dose administered at steady-state. Overall treatment response rate was 72%, and the incidence of ADR was 30%. The logistic regression showed that exposure predictors were not associated with treatment response or ADR in the range of dose commonly used in routine practice. However, the incidence of ADR increased with the increase of daily dose or AUC for the patients with multiple concentrations.


          In depressed patients treated with paroxetine, TDM may be of limited value for individualization of treatment.

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          Most cited references 30

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          The UKU side effect rating scale. A new comprehensive rating scale for psychotropic drugs and a cross-sectional study of side effects in neuroleptic-treated patients.

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            Review and meta-analysis of antidepressant pharmacogenetic findings in major depressive disorder.

            This systematic review summarizes pharmacogenetic studies on antidepressant response and side effects. Out of the 17 genes we reviewed, 8 genes were entered into the meta-analysis (SLC6A4, HTR1A, HTR2A, TPH1, gene encoding the beta-3 subunit, brain-derived neurotrophic factor (BDNF), HTR3A and HTR3B). TPH1 218C/C genotype (7 studies, 754 subjects) was significantly associated with a better response (odds ratio, OR=1.62; P=0.005) with no heterogeneity between ethnicities. A better response was also observed in subjects with the Met variant within the BDNF 66Val/Met polymorphism (4 studies, 490 subjects; OR=1.63, P=0.02). Variable number of tandem repeats polymorphism within intron 2 (STin2) 12/12 genotype showed a trend toward a better response in Asians (STin2: 5 studies, 686 subjects; OR=3.89, P=0.03). As for side effects, pooled ORs of serotonin transporter gene promoter polymorphism (5-HTTLPR) l (9 studies, 2642 subjects) and HTR2A -1438G/G (7 studies, 801 subjects) were associated with a significant risk modulation (OR=0.64, P=0.0005) and (OR=1.91, P=0.0006), respectively. Interestingly, this significance became more robust when analyzed with side effect induced by selective serotonin reuptake inhibitors only (5-HTTLPR: P=0.0001, HTR2A: P<0.0001). No significant result could be observed for the other variants. These results were not corrected for multiple testing in each variant, phenotype and subcategory. This would have required a Bonferroni significance level of P<0.0023. Although some heterogeneity was present across studies, our finding suggests that 5-HTTLPR, STin2, HTR1A, HTR2A, TPH1 and BDNF may modulate antidepressant response.
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              Neurotransmitter receptor and transporter binding profile of antidepressants and their metabolites.

              Several new antidepressants that inhibit the serotonin (SERT) and norepinephrine transporters (NET) have been introduced into clinical practice the past several years. This report focuses on the further pharmacologic characterization of nefazodone and its metabolites within the serotonergic and noradrenergic systems, in comparison with other antidepressants. By use of radioligand binding assays, we measured the affinity (Ki) of 13 antidepressants and 6 metabolites for the rat and human SERT and NET. The Ki values for eight of the antidepressants and three metabolites were also determined for the rat 5-HT1A, 5-HT2A and muscarinic cholinergic receptors, the guinea pig histamine1 receptor and the human alpha-1 and alpha-2 receptors. These data are useful for predicting side effect profiles and the potential for pharmacodynamic drug-drug interactions of antidepressants. Of particular interest were the findings that paroxetine, generally thought of as a selective SERT antagonist, possesses moderately high affinity for the NET and that venlafaxine, which has been described as a "dual uptake inhibitor", possesses weak affinity for the NET. We observed significant correlations in SERT (r = 0.965) or NET (r = 0.983) affinity between rat and human transporters. Significant correlations were also observed between muscarinic cholinergic and NET affinity. There are several significant correlations between affinities for the 5-HT1A, 5-HT2A, histamine1, alpha-1 and alpha-2 receptors. These novel findings, not widely described previously, suggest that many of the individual drugs studied in these experiments possess some structural characteristic that determines affinity for several G protein-coupled, but not muscarinic, receptors.

                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                16 September 2015
                : 9
                : 5247-5254
                [1 ]Department of Clinical Pharmacology and Therapeutics, Samsung Medical Center, Seoul, Republic of Korea
                [2 ]Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea
                [3 ]Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
                [4 ]Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
                [5 ]Clinical Research Division, Toxicological Evaluation and Research Department, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Osong, Chungcheongbuk-do, Republic of Korea
                [6 ]Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
                Author notes
                Correspondence: Soo-Youn Lee, Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea, Tel +82 2 3410 1834, Fax +82 2 3410 2719, Email suddenbz@ 123456skku.edu
                Doh Kwan Kim, Department of Psychiatry, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea, Email paulkim@ 123456skku.edu
                © 2015 Kim et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License

                The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

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