Keywords nonlinear mixed effect modelling, population pharmacokinetics, systematic review, valproic acid
AIMSPopulation pharmacokinetics is an essential tool that helps guide individualized dosing regimens. The aims of this systematic review are to provide knowledge concerning population pharmacokinetics of valproic acid (VPA) and to identify factors influencing VPA pharmacokinetic variability.
METHODSPubMed and Embase databases were systematically searched from inception to June, 2017. Relevant articles from reference lists were also included. All population pharmacokinetic studies of VPA conducted in humans and that employed a nonlinear mixed effect modelling approach were included in this review.
RESULTSTwenty-six studies were included in this review. Most studies characterized VPA pharmacokinetics as a one-compartment model. Three studies reported a two-compartment model. Body weight, dose and age were significant predictors for VPA volume of distribution (V d ). The estimated V d for one-compartment models ranged from 8.4 to 23.3 l. For two-compartment models, peripheral volumes of distribution ranged from 4.08 to 42.1 l. Frequently reported significant predictors for VPA clearance (CL VPA ) included body weight, VPA dose, concomitant medications, gender and age. The estimated CL VPA ranged from 0.206 to 1.154 l h À1 and the inter-individual variability ranged from 13.40 to 35.90%. Two studies reported population pharmacokinetics/pharmacodynamics of VPA in patients with epilepsy. Seventeen studies evaluated the performance of their final models.
CONCLUSIONSSignificant predictors influencing VPA pharmacokinetics as well as model methodologies are highlighted in this review. For clinical application, CL VPA could be predicted using body weight, VPA dose, concomitant medications, gender or age. For future research, there is a knowledge gap regarding population pharmacokinetics/pharmacodynamics of VPA in a population other than epileptic patients.British Journal of Clinical Pharmacology Br J Clin Pharmacol (2018) 84 816-834 816
A multiple dose, parallel group study was conducted to assess for a drug-drug interaction between the pyronaridine/artesunate (PA) combination antimalarial and ritonavir. Thirty-four healthy adults were randomized (1:1) to receive PA for 3 days or PA with ritonavir (100 mg twice daily for 17 days, PA administered on Days 8–10). Pharmacokinetic parameters for pyronaridine, artesunate, and its active metabolite dihydroartemisinin (DHA) were obtained after the last PA dose and for ritonavir on Days 1 and 10. Ritonavir coadministration did not markedly change pyronaridine pharmacokinetics but resulted in a 27% increase in artesunate area under the curve (AUC) and a 38% decrease in DHA AUC. Ritonavir exposure was increased 3.2-fold in the presence of PA. The only relevant safety observations were increases in liver enzymes, only reaching a clinically significant grade in the PA + ritonavir arm. It was concluded that coadministered ritonavir and PA interact to alter exposure to artesunate, DHA, and ritonavir itself.
Model methodologies in each study are summarized and discussed in this review. For future perspective, a population pharmacokinetic-pharmacodynamic study of lithium is recommended. Moreover, external validation of previously published models should be performed.
Aims: Polypharmacy is associated with multiple adverse health outcomes. The objective of this systematic review and meta-analysis was to explore the association between polypharmacy and depression. Methods and results: A systematic literature review was conducted by searching MEDLINE, Scopus, Science Direct, and CINAHL Complete to identify studies assessing the association between polypharmacy and depression published until November 2020. A meta-analysis was performed using random effect models. Heterogeneity was assessed using the I 2 -statistic. Nineteen studies were included in the meta-analysis. We found that an increase in the number of drugs was associated with an increased risk of depression (OR = 1.55 [95% CI: 1.01, 2.36; I 2 = 62%, n = 2]). Further, polypharmacy defined as the concurrent use of five or more medications was associated with an increased risk of depression (OR = 1.73 [95% CI: 1.39, 2.14], I 2 = 83%, n = 8). Conclusion: This meta-analysis revealed that polypharmacy, both discretely and categorically defined, was associated with an increased risk of depression.
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