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Aims: Pregnancy after kidney transplantation is realistic but immunosuppressants should be continued to prevent rejection. Tacrolimus is safe during pregnancy and is routinely dosed based on whole‐blood predose concentrations. However, maintaining these concentrations is complicated as physiological changes during pregnancy affect tacrolimus pharmacokinetics. The aim of this study was to describe tacrolimus pharmacokinetics throughout pregnancy and explain the changes by investigating covariates in a population pharmacokinetic model. Methods: Data of pregnant women using a twice‐daily tacrolimus formulation following kidney transplantation were retrospectively collected from 6 months before conception, throughout gestation and up to 6 months postpartum. Pharmacokinetic analysis was performed using nonlinear mixed effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. The final model was evaluated using goodness‐of‐fit plots, visual predictive checks and a bootstrap analysis. Results: A total of 260 whole‐blood tacrolimus predose concentrations from 14 pregnant kidney transplant recipients were included. Clearance increased during pregnancy from 34.5 to 41.7 L/h, by 15, 19 and 21% in the first, second and third trimester, respectively, compared to prior to pregnancy. This indicates a required increase in the tacrolimus dose by the same percentage to maintain the prepregnancy concentration. Haematocrit and gestational age were negatively correlated with tacrolimus clearance (P ≤ 0.01), explaining 18% of interindividual and 85% of interoccasion variability in oral clearance. Conclusions: Tacrolimus clearance increases during pregnancy, resulting in decreased exposure to tacrolimus, which is explained by gestational age and haematocrit. To maintain prepregnancy target whole‐blood tacrolimus predose concentrations during pregnancy, increasing the dose is required. [ABSTRACT FROM AUTHOR]

What is already known about this subject • Most antidepressants are metabolized by CYP2D6. The variant allele CYP2D6*4 is the main polymorphism resulting in reduced enzyme activity in Caucasians. • Reduced enzyme activity potentially leads to increased toxicity of antidepressants, but the relevance of genotyping for clinical practice is unclear. Most clinical studies suffer from small numbers of patients. What this study adds • This large population-based cohort study in 1198 elderly Dutch patients examines the influence of the CYP2D6* 4 polymorphism on intolerability of antidepressants. • The risk of switching to another antidepressant in tricyclic antidepressant users is higher in poor metabolizers (PMs), but not in SSRI users. PMs require a lower maintenance dose of antidepressants compared with extensive metabolizers (EMs). • Antidepressants were initiated in a relatively low dose, with gradual dose increments thereafter, reducing the risk of adverse drug reactions. Therefore, the question remains whether genotyping prior to the start of antidepressant therapy contributes substantially to the optimization of pharmacotherapy. Aims To study the effect of CYP2D6* 4 on antidepressant dose, switching and discontinuation of therapy. Methods The study consisted of all subjects in the Rotterdam Study, who received a first antidepressant prescription between April 1st 1991 and July 1st 2005 and for whom data on CYP2D6 genotype were available. Binary logistic regression was performed to study the association between CYP2D6* 4 and switching to any other antidepressant or discontinuation of therapy within 45 days. The difference in mean antidepressant dose was compared between CYP2D6 genotypes using t-tests and repeated measurements analyses. Results In users of tricyclic antidepressants (TCAs) the risk of switching to another antidepressant was significantly higher in poor metabolizers (PMs:* 4/* 4) compared with extensive metabolizers (EMs:* 1/* 1), with an adjusted OR of 5.77 (95% CI 1.59, 21.03; P = 0.01). In SSRI users there was no significant difference (OR 0.91; 95% CI 0.20, 4.15; P = 0.90). Heterozygous patients did not have an increased risk of switching in both TCA and SSRI users. The mean TCA dose was significantly lower in PMs than in EMs at the third and fourth prescription (difference 0.11 DDD, P = 0.03). In SSRI users the difference in mean dose between PMs and EMs was significant at the third prescription (0.17 DDD; P = 0.02). Conclusions The risk of switching to another antidepressant in TCA users is higher in PMs than in EMs. The maintenance doses of antidepressants were significantly lower in PMs. However, the question whether genotyping prior to the start of antidepressant therapy contributes substantially to the optimization of pharmacotherapy, requires further study. [ABSTRACT FROM AUTHOR]

Aims: Tacrolimus is a critical dose drug and to avoid under- and overexposure, therapeutic drug monitoring is standard practice. However, rejection and drug-related toxicity occur despite whole-blood tacrolimus pre-dose concentrations ([Tac] blood ) being on target. Monitoring tacrolimus concentrations at the target site (within peripheral blood mononuclear cells; [Tac] cells ) may better correlate with drug-efficacy. The aim of this study was to (1) investigate the relationship between [Tac] blood and [Tac] cells , (2) identify factors affecting the tacrolimus distribution in cells and whole-blood, and (3) study the relationship between [Tac] cells and clinical outcomes after kidney transplantation., Methods: A total of 175 renal transplant recipients were prospectively followed. [Tac] blood and [Tac] cells were determined at Months 3, 6 and 12 post-transplantation. Patients were genotyped for ABCB1 1199G>A and 3435C>T, CYP3A4 15389C>T, and CYP3A5 6986G>A. Data on rejection and tacrolimus-related nephrotoxicity and post-transplant diabetes mellitus were collected., Results: Correlations between [Tac] blood and [Tac] cells were moderate to poor (Spearman's r = 0.31; r = 0.41; r = 0.61 at Months 3, 6 and 12, respectively). The [Tac] cells /[Tac] blood ratio was stable over time in most patients (median intra-patient variability 39.0%; range 3.5%-173.2%). Age, albumin and haematocrit correlated with the [Tac] cells /[Tac] blood ratio. CYP3A5 and CYP3A4 genotype combined affected both dose-corrected [Tac] blood and [Tac] cells . ABCB1 was not significantly related to tacrolimus distribution. Neither [Tac] blood nor [Tac] cells correlated with clinical outcomes., Conclusions: The correlation between [Tac] blood and [Tac] cells is poor. Age, albumin and haematocrit correlate with the [Tac] cells /[Tac] blood ratio, whereas genetic variation in ABCB1, CYP3A4 and CYP3A5 do not. Neither [Tac] blood nor [Tac] cells correlated with clinical outcomes., (© 2020 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Aim: Risperidone is the most commonly prescribed antipsychotic drug to children and adolescents worldwide, but it is associated with serious side effects, including weight gain. This study assessed the relationship of risperidone and 9-hydroxyrisperidone trough concentrations, maximum concentrations and 24-hour area under the curves (AUCs) with body mass index (BMI) z-scores in children and adolescents with autism spectrum disorder (ASD) and behavioural problems. Secondary outcomes were metabolic, endocrine, extrapyramidal and cardiac side effects and effectiveness., Methods: Forty-two children and adolescents (32 males) aged 6-18 years were included in a 24-week prospective observational trial. Drug plasma concentrations, side effects and effectiveness were measured at several time points during follow-up. Relevant pharmacokinetic covariates, including medication adherence and CYP2D6, CYP3A4, CYP3A5 and P-glycoprotein (ABCB1) genotypes, were measured. Nonlinear mixed-effects modelling (NONMEM®) was used for a population pharmacokinetic analysis with 205 risperidone and 205 9-hydroxyrisperidone concentrations. Subsequently, model-based trough concentrations, maximum concentrations and 24-hour AUCs were analysed to predict outcomes using generalized and linear mixed-effects models., Results: A risperidone two-compartment model combined with a 9-hydroxyrisperidone one-compartment model best described the measured concentrations. Of all the pharmacokinetic parameters, higher risperidone sum trough concentrations best predicted higher BMI z-scores during follow-up (P < .001). Higher sum trough concentrations also predicted more sedation (P < .05), higher prolactin levels (P < .001) and more effectiveness measured with Aberrant Behavior Checklist irritability score (P < .01)., Conclusion: Our results indicate a therapeutic window exists, which suggests that therapeutic drug monitoring of risperidone might increase safety and effectiveness in children and adolescents with ASD and behavioural problems., (© 2020 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)