Assessing Pharmacokinetic Correlates of Escitalopram-Related Adverse Drug Reactions.

BACKGROUND: To assess the pharmacokinetic correlates of reported adverse drug reactions (ADRs) under antidepressant treatment with escitalopram (ESC) using a large therapeutic drug monitoring database. METHODS: A large naturalistic sample of inpatients and outpatients prescribed ESC was analyzed. ADRs were classified using the Udvalg for Kliniske Undersogelser side effect rating scale. We compared ESC-treated patients with (n = 35) and without ADRs (n = 273) using ESC plasma concentrations as the primary outcome. We also compared ADR rates in the 2 groups based on 2 cut-off ESC levels reflecting the recommended upper thresholds of the therapeutic reference range of 80 ng/mL, suggested by the consensus therapeutic drug monitoring guidelines, and 40 ng/mL, based on recent meta-analysis data. The effects of age, sex, smoking, daily ESC dose, plasma concentrations, and concentrations corrected for daily dose were included in a binary logistic regression model to predict ADRs. RESULTS: No differences in clinical, demographic, or pharmacokinetic parameters were observed between patients with and without ADRs ( P > 0.05). Patients with ESC-related ADRs were more frequently diagnosed with psychotic disorders than those without (25% vs. 7.1%, P = 0.004). None of the variables was associated with ADR risk. Overall, ADR rates were not significantly different in patients above versus below thresholds of ESC concentrations (ESC concentrations >40 [n = 59] vs. ≤40 ng/mL [n = 249] and >80 [n = 8] vs. ≤80 ng/mL [n = 300]; P = 0.56 and P = 1.0, respectively). CONCLUSIONS: No distinct pharmacokinetic patterns underlying ESC-associated ADRs were observed. Further studies with more specific assessments of ADRs in larger cohorts are required to better identify potential underlying patterns.

Clozapine once- versus multiple-daily dosing: a two-center cross-sectional study, systematic review and meta-analysis.

Evidence regarding effectiveness and safety of clozapine once- vs. multiple-daily dosing is limited. We compared demographic and clinical parameters between patients with once- vs. multiple-daily dosing in the Department of Psychiatry and Psychotherapy, University of Regensburg, Germany (AGATE dataset), and the Department of Psychiatry, Lausanne University Hospital, Switzerland, using non-parametric tests. Effectiveness and safety outcomes were available in the AGATE dataset. We performed a systematic review in PubMed/Embase until February 2022, meta-analyzing studies comparing clozapine once- vs. multiple-daily-dosing. We estimated a pooled odds ratio for adverse drug-induced reactions (ADRs) and meta-analyzed differences regarding clinical symptom severity, age, percentage males, smokers, clozapine dose, and co-medications between patients receiving once- vs. multiple-daily dosing. Study quality was assessed using the Newcastle-Ottawa-Scale. Of 1494 and 174 patients included in AGATE and Lausanne datasets, clozapine was prescribed multiple-daily in 74.8% and 67.8%, respectively. In the AGATE cohort, no differences were reported for the clinical symptoms severity or ADR rate (p > 0.05). Meta-analyzing eight cohorts with a total of 2810 clozapine-treated individuals, we found more severe clinical symptoms (p = 0.036), increased ADR risk (p = 0.01), higher clozapine doses (p < 0.001), more frequent co-medication with other antipsychotics (p < 0.001), benzodiazepines (p < 0.001), anticholinergics (p = 0.039), and laxatives (p < 0.001) in patients on multiple- vs. once-daily dosing. Of six studies, five were rated as good, and one as poor quality. Patients responding less well to clozapine may be prescribed higher doses multiple-daily, also treated with polypharmacy, potentially underlying worse safety outcomes. Patient preferences and adherence should be considered during regimen selection.

Effects of body weight, smoking status, and sex on plasma concentrations of once-monthly paliperidone palmitate.

OBJECTIVES: Knowledge about the impact of body composition features on pharmacokinetics of newer long-acting injectable antipsychotics is limited. METHODS: We analyzed steady-state plasma concentrations of paliperidone in different body mass index (BMI), age, sex, and smoking status patient subgroups treated with once-monthly paliperidone palmitate (PP1M). Paliperidone plasma concentrations and dose-adjusted-plasma concentrations (C/D) from a therapeutic drug monitoring (TDM) database of PP1M-treated patients were compared among normal BMI, overweight, and obese patients as well as between females vs. males, elderly vs. non-elderly, and smokers vs. non-smokers using non-parametric tests. RESULTS: In a total of 183 PP1M-treated patients, we found highly variable paliperidone plasma concentrations between individuals but no significant effect of PP1M dose or dosing intervals (p> 0.05). C/D ratios were similar in 54 obese, 82 overweight, and 47 normal BMI patients (p> 0.05). Females had 13.7% higher C/D ratios compared to males, yet this difference was not significant (p> 0.05). No differences were found between elderly vs. non-elderly patients or for smokers vs. non-smokers (p> 0.05). CONCLUSION: Our findings suggest that age, sex, smoking, or body weight may not substantially affect pharmacokinetic indices of PP1M. The high interindividual variation of plasma concentrations implies that TDM may be helpful to enhance PP1M efficacy and tolerability.

Pharmacokinetic Correlates of Once-Monthly Paliperidone Palmitate-Related Adverse Drug Reactions.

OBJECTIVE: The objective of this study was to investigate associations between pharmacokinetic correlates and once-monthly paliperidone palmitate (PP1M)-related adverse drug reactions (ADRs). METHODS: Plasma concentrations and dose-adjusted plasma concentrations ('concentration-by-dose' [C/D]) of paliperidone from a naturalistic therapeutic drug monitoring database of PP1M-treated patients were compared between patients with ADRs, classified according to the Udvalg for Kliniske Undersogelser side-effect rating scales categories, and patients without ADRs. Analyses included non-parametric tests and a logistic regression model with a significance level set at 0.05. RESULTS: In 172 patients, we found no differences in sex, age, smoking, body mass index, PP1M dose, paliperidone plasma concentrations, and C/D values (p > 0.05) between 44 patients with and 128 patients without PP1M-related ADRs. We did not detect differences when specifying for different types of ADRs (p > 0.05). Injection intervals were shorter in patients with vs patients without ADRs (p = 0.03). The logistic regression did not report effects for sex, plasma concentrations, or C/D values (p > 0.05). Post hoc analyses in male patients receiving PP1M every 28 weeks reported higher paliperidone concentrations and C/D values in patients with vs without ADRs (p = 0.049 and p = 0.022). Within the group of male patients, we found an odds ratio of 3.07 for PP1M-associated ADRs in patients with C/D values above 7.7 (ng/mL)/(mg/day). CONCLUSIONS: Our findings did not reveal distinct patterns of paliperidone concentrations in patients with PP1M-related ADRs. However, male patients receiving PP1M every 28 days with C/D values higher than 7.7 (ng/mL)/(mg/day) showed a higher risk for ADRs, implying that therapeutic drug monitoring may be useful in assessing the risk of PP1M-related ADRs.

Lack of Smoking Effects on Pharmacokinetics of Oral Paliperidone-analysis of a Naturalistic Therapeutic Drug Monitoring Sample.

INTRODUCTION: Major smoking effects have been reported for a series of psychotropic agents, mainly including substrates of CYP450 1A2, although smoking may also affect alternative metabolic pathways. To our knowledge, smoking effects on paliperidone pharmacokinetics have not been assessed yet. METHODS: We compared plasma concentrations of paliperidone as well as dose-corrected-plasma concentrations (C/D) from a naturalistic database between smokers and nonsmokers using nonparametrical tests, such as the Mann-Whitney U-test (MWU). Additionally, we compared light and heavy smokers with nonsmokers separately. RESULTS: Comparing 55 smokers with 37 nonsmokers treated with oral paliperidone, no differences in the percentage of females, age, body weight, body mass index, and daily paliperidone dose were reported (p=0.709 for χ2, p=0.26, p=0.38, p=0.67, and p=0.8 for MWU). No differences were detected in plasma concentrations or C/D values (p=0.50 and p=0.96 for MWU). Likewise, differences in daily dose, plasma concentrations, or C/D values were not significant between light smokers (n=17) and nonsmokers (p=0.61, p=0.81, and p=0.33 for MWU) or heavy smokers (n=22) and nonsmokers (p=0.874, p=0.38, and p=0.59; MWU in all cases). DISCUSSION: Paliperidone is not affected by smoking, and paliperidone dose-adjustments in smokers may not be necessary. This may be seen as an essential difference to risperidone, whose cytochrome-mediated metabolism might be affected by smoking.

Subtherapeutic bupropion and hydroxybupropion serum concentrations in a patient with CYP2C19*1/*17 genotype suggesting a rapid metabolizer status.

Bupropion is hydroxylated to its primary active metabolite hydroxybupropion by cytochrome P450 enzyme CYP2B6. In vitro data suggest the existence of alternative hydroxylation pathways mediated by the highly polymorphic enzyme CYP2C19. However, the impact of its genetic variants on bupropion metabolism in vivo is still under investigation. We report the case of a 28-year-old male Caucasian outpatient suffering from major depressive disorder who did not respond to a treatment with bupropion. Therapeutic drug monitoring revealed very low serum concentrations of both bupropion and hydroxybupropion. Genotyping identified a heterozygous status for the gain-of-function allele with the genotype CYP2C19*1/*17 predicting enhanced enzymatic activity. The present case shows a reduced bupropion efficacy, which may be explained by a reduced active moiety of bupropion and its active metabolite hydroxybupropion, due to alternative hydroxylation pathways mediated by CYP2C19 in an individual with CYP2C19 rapid metabolizer status. The case report thus illustrates the clinical relevance of therapeutic drug monitoring in combination with pharmacogenetics diagnostics for a personalized treatment approach.

Pharmacokinetic interactions between clozapine and sertraline in smokers and non-smokers.

Clozapine is an effective antipsychotic drug for treatment-resistant schizophrenia. Sertraline is a widely prescribed antidepressant and often concomitantly applied to address negative symptoms or depression. However, data on interactions between clozapine and sertraline are inconsistent. The aim of our study was to evaluate pharmacokinetic interactions between clozapine and sertraline analysing a therapeutic drug monitoring database of 1644 clozapine-medicated patients. We compared four groups: non-smokers (n = 250) and smokers (n = 326) with co-medication without known effects on cytochrome P450 and without sertraline, and non-smokers (n = 18) and smokers (n = 17) with sertraline co-medication. Measured and dose-corrected concentrations (C/D) of clozapine were compared between the groups using non-parametrical tests with a significance level of 0.05. Post hoc analyses included pairwise comparisons to account for smoking status. Although we detected significant differences for clozapine levels and C/D values between study groups (P < .001 for Kruskal-Wallis test in both cases), post hoc analyses revealed no differences for concentrations and C/D values of clozapine (P > .05 for Mann-Whitney U test in both cases). A negative correlation between the sertraline dose and the clozapine concentration was found in non-smokers (Spearman's rank correlation, rs = -0.535, P = .048). A potential pharmacokinetic interaction between clozapine and a standard therapeutic sertraline dose seems to be of minor clinical importance.

The Effects of Co-prescription of Pantoprazole on the Clozapine Metabolism.

BACKGROUND: Polypharmacy including somatic medications such as proton pump inhibitors is a common phenomenon in psychiatric care. The aim of this study was to evaluate the pantoprazole effects on clozapine metabolism. METHODS: A large therapeutic drug-monitoring database containing plasma concentrations of CLZ was analyzed. The results were stratified into four groups: a non-smoking (n=250) and a smoking group (n=326), and two groups co-medicated with pantoprazole: non-smokers (n=26) and smokers (n=29). The analysis was based on the non-parametrical Mann-Whitney U test (M-W-U) with a significance level of 0.05. RESULTS: Differences reached statistical significance for pharmacokinetic parameters between CLZ monotherapy and co-medication with pantoprazole neither in smokers nor in non-smokers (p>0.05 for M-W-U in pairwise comparisons). In patients with clozapine monotherapy, smokers had a higher daily dosage of CLZ compared to non-smokers (mean dosage 363±181 vs. 291±145 mg/day, p<0.001 for M-W-U). CONCLUSIONS: Adding pantoprazole to an ongoing treatment with clozapine does not alter the metabolism of clozapine to a significant extent.

Clinically Significant Drug-Drug Interactions with Agents for Attention-Deficit/Hyperactivity Disorder.

This article provides an overview of the pharmacokinetic drug-drug interactions (DDIs) for agents prescribed for attention-deficit/hyperactivity disorder (ADHD). Polypharmacy in the treatment of patients with ADHD leads to high exposures to DDIs and possibly adverse safety outcomes. We performed a systematic search of DDI reports for ADHD agents in Embase and Medline. We also searched for agents in the pharmacological pipeline, which include (1) mazindol, molindone and viloxazine, which were previously prescribed for other indications; (2) centanafadine and AR-08, never before approved; and (3) two extracts (Polygala tenuifolia extract and the French maritime pine bark extracts). The identified literature included case reports, cross-sectional, cross-over and placebo-controlled studies of patient cohorts and healthy volunteers. The DDIs were classified as follows: ADHD agents acting as perpetrators, i.e., affecting the clearance of co-prescribed agents (victim drugs), or ADHD agents being the victim drugs, being affected by other agents. Ratios for changes in pharmacokinetic parameters before and after the DDI were used as a rough estimate of the extent of the DDI. Alcohol may increase plasma dextroamphetamine concentrations by presystemic effects. Until studies are done to orient clinicians regarding dosing changes, clinicians need to be aware of the potential for cytochrome P450 (CYP) 2D6 inhibitors to increase amphetamine levels, which is equivalent to increasing dosages. Atomoxetine is a wide therapeutic window drug. The CYP2D6 poor metabolizers who do not have CYP2D6 activity had better atomoxetine response, but also an increased risk of adverse effects. CYP2D6 inhibitors have been used to increase atomoxetine response in CYP2D6 extensive metabolizers. Guanfacine is mainly metabolized by CYP3A4, which can be induced and inhibited. The package insert recommends that in guanfacine-treated patients, after adding potent CYP3A4 inducers, the guanfacine dose should be doubled; after adding potent CYP3A4 inhibitors the guanfacine dose should be halved. Based on a phenobarbital case report and our experience with CYP3A4-metabolized antipsychotics, these correction factors may be too low. According to two case reports, carbamazepine is a clinically relevant inducer of methylphenidate (MPH). A case series study suggested that MPH may be associated with important elevations in imipramine concentrations. Due to the absence of or limitations in the data, no comments for clinicians can be provided on the pharmacokinetic DDIs for clonidine, centanafadine, mazindol, molindone, AR-08, P. tenuifolia extract and the French maritime pine bark extracts. According to currently available data, clinicians should not expect that ADHD drugs modify each other's serum concentrations. A summary table for clinicians provides our current recommendations on pharmacokinetic DDIs of ADHD agents based on our literature review and the package inserts; whenever it was possible, we provide information on serum concentrations and dose correction factors. There will be a need to periodically update these recommendations and these correction factors as new knowledge becomes available.

Effect of fluvoxamine augmentation and smoking on clozapine serum concentrations.

BACKGROUND: Clozapine (CLZ) is metabolized via cytochrome P450 CYP1A2 to N-desmethylclozapine (NCLZ). Smoking induces CYP1A2 thereby increasing clozapine metabolism whereas fluvoxamine inhibits CYP1A2. Studies suggest that the beneficial effect of fluvoxamine augmentation in raising serum clozapine concentrations also occurs when serum concentrations are low due to smoking. Yet, little is known about the influence of fluvoxamine augmentation on clozapine serum concentrations in smoking versus non-smoking patients. METHODS: A TDM database was analyzed. Serum concentrations of CLZ, NCLZ, dose-adjusted serum concentrations (C/D) and metabolite-to-parent ratios (MPR) were compared using non-parametrical tests in four groups: clozapine-monotherapy in non-smokers (VNS, n = 28) and smokers (VS, n = 43); combined treatment with clozapine and fluvoxamine in non-smokers (VNS+F, n = 11) and smokers (VS+F, n = 43). RESULTS: The CLZ monotherapy smoking group showed lower values of C/D CLZ of -38.6% (p < 0.001), C/D NCLZ -35.6% (p < 0.001) and a higher MPR (p = 0.021) than in the non-smoking group. The combination of CLZ and fluvoxamine in non-smoking patients led to higher C/D values: C/D CLZ +117.9% (p < 0.001), C/D NCLZ +60.8% (p = 0.029) while the MPR did not differ between groups (p = 0.089). Changes were comparable to fluvoxamine augmentation in the smoking group with increased C/D CLZ of +120.1% (p < 0.001), C/D NCLZ of +85.8% (p < 0.001) and lower MPR (p = 0.006). CONCLUSIONS: Smoking in clozapine monotherapy reduced median dose-adjusted serum concentrations more than a third. Combined treatment with fluvoxamine and clozapine led to higher median C/D values in both, smokers and non-smokers. The opposing effects of CYP1A2 induction by smoking and inhibition by fluvoxamine on clozapine serum concentrations balanced out.

Cytochrome P450-mediated inhibition of venlafaxine metabolism by trimipramine.

OBJECTIVE: The aim of this study was to ensure patients' safety and to enhance treatment efficacy, knowledge about pharmacokinetic interactions even in complex clinical situations of polypharmacy is invaluable. This study is to uncover the potential of pharmacokinetic interactions between venlafaxine and trimipramine in a naturalistic sample. METHODS: Out of a therapeutic drug monitoring database with plasma concentrations of venlafaxine (VEN) and O-desmethylvenlafaxine (ODV), we considered two groups of patients receiving venlafaxine without known cytochrome P450 confounding medications, taking solely venlafaxine: V0 (n = 905), and a group of patients co-medicated with trimipramine, VTRIM (n = 33). For VEN, ODV and active moiety (sum of VEN + ODV) plasma concentrations and dose-adjusted concentrations as well as ODV/VEN ratios were compared between groups using the Mann-Whitney U test with a significance level of 0.05. RESULTS: Patients co-medicated with trimipramine had higher plasma concentrations of VEN (183.0 vs. 72.0, +154%, P = 0.002) and AM (324.0 vs. 267.5, +21%, P = 0.005) and higher dose adjusted plasma concentrations than patients in the control group (P = 0.001 and P = 0.003). No differences were found for ODV and C/D ODV (P < 0.05 for both comparisons). The metabolite to parent ratio, ODV/VEN, was significantly lower in the VTRIM group (1.15 vs. 2.37, P = 0.012). CONCLUSION: Findings suggest inhibitory effects of trimipramine on venlafaxine pharmacokinetics most likely via an inhibition of CYP 2D6 or by saturated enzyme capacity. The lack of in vitro data hampers the understanding of the exact mechanisms. Clinicians should be aware of drug-drug interactions when combining these agents. Therapeutic drug monitoring helps to ensure treatment efficacy and patients' safety.

Differences in Duloxetine Dosing Strategies in Smoking and Nonsmoking Patients: Therapeutic Drug Monitoring Uncovers the Impact on Drug Metabolism.

BACKGROUND: For certain psychotropic drugs, such as clozapine or olanzapine, the influence of smoking on drug metabolism is well studied. Tobacco smoke increases the metabolism of drugs that are substrates for cytochrome P450 (CYP) 1A2 due to CYP induction. The antidepressant duloxetine, acting as a serotonin-norepinephrine reuptake inhibitor, is mainly metabolized via CYP1A2. To date, little is known about the influence of smoking on serum duloxetine concentrations. METHODS: A therapeutic drug monitoring database consisting of plasma concentrations of duloxetine collected from January 2013 to June 2017 was analyzed. A group of nonsmoking patients undergoing treatment with duloxetine (n = 89) was compared to a group of active smokers also receiving duloxetine (n = 36). Serum concentrations of duloxetine and dose-adjusted serum concentrations were compared using non-parametric tests. RESULTS: Groups did not differ concerning sex (P = .063), but the group of active smokers was younger (P < .001) and received higher daily doses of duloxetine (P = .001). Smokers showed significantly lower median serum duloxetine concentrations (38.4% lower, P = .002) and 53.6% lower dose-adjusted serum concentrations (0.325 [ng/mL]/[mg/d] in smokers vs 0.7 [ng/mL]/[mg/d] in nonsmokers, P < .001). CONCLUSIONS: Despite higher daily doses, smokers had considerably lower serum duloxetine concentrations. The induction of CYP1A2 by tobacco smoke is a clinically relevant factor for drugs that are substrates for CYP1A2. Clinicians should actively assess smoking status, inform patients about the effect of smoking on duloxetine metabolism, and anticipate higher serum concentrations in the case of smoking cessation. Therapeutic drug monitoring ensures treatment efficacy by enabling the personalizing of treatment, as smokers need higher duloxetine doses to target serum concentrations within the therapeutic reference range.

Antidepressant polypharmacy and the potential of pharmacokinetic interactions: Doxepin but not mirtazapine causes clinically relevant changes in venlafaxine metabolism.

BACKGROUND: To uncover pharmacokinetic interactions between venlafaxine and doxepin or mirtazapine in a naturalistic sample. METHODS: A therapeutic drug monitoring database containing plasma concentrations of venlafaxine (VEN) and its active metabolite O-desmethylvenlafaxine (ODVEN) was analyzed. We included 1067 of 1594 patients in the analysis. Three study groups were considered; a group of patients under venlafaxine without confounding medications, V0 (n = 905), a group of patients co-medicated with doxepin, VDOX (n = 25) and a second group, co-medicated with mirtazapine, VMIR, n = 137. Plasma concentrations of VEN, ODVEN and the clinically relevant active moiety, sum of venlafaxine and O-desmethylvenlafaxine (ODVEN) (AM), as well as dose-adjusted plasma concentrations (C/D) were compared. RESULTS: Median concentrations in the doxepin group showed 57.7% and 194.4% higher values for AM and VEN respectively; these differences were statistically significant (p < 0.001 for AM and p = 0.002 for VEN). Similar differences were detected for C/D concentrations of active moiety and VEN (p < 0.001 and p = 0.001) with higher values also in the doxepin group. The ratios ODVEN/VEN were lower in the doxepin group (p < 0.001). A co-medication with mirtazapine did not cause any changes in venlafaxine metabolism. CONCLUSIONS: Higher concentrations for VEN and AM imply an inhibiting effect of doxepin on the metabolism of venlafaxine, although the huge variability of concentrations has to be taken into account. It is recommended to monitor plasma concentrations in combination treatment to avoid problems in safety and efficacy. LIMITATIONS: Despite the large size of our study sample, the naturalistic nature of this data may arise some concerns of information bias potentially resulting from non-standardized data recording.

Cytochrome P450-mediated interaction between perazine and risperidone: implications for antipsychotic polypharmacy.

BACKGROUND: Although clinically widespread, scientific evidence for antipsychotic polypharmacy is still limited. Combining different drugs increases the potential for drug-drug interactions, enhancing the risk of adverse drug reactions. We aimed to unravel the potential pharmacokinetic interactions between risperidone (RIS) and perazine. METHODS: Using a therapeutic drug monitoring database containing plasma concentrations of RIS and its active metabolite [9-hydroxyrisperidone (9-OH-RIS)], we considered two groups: a group of patients under antipsychotic monotherapy with RIS (n = 40) and a group of patients that was comedicated with perazine (n = 16). Groups were matched for demographic characteristics and daily dosage of RIS. Plasma concentrations, concentrations corrected for the dose (C/D) of RIS, 9-OH-RIS and the active moiety (RIS + 9-OH-RIS), as well as the metabolic ratios of concentrations of 9-OH-RIS/RIS, were compared using nonparametric tests. RESULTS: All parameters other than plasma concentrations and the C/D ratio of 9-OH-RIS differed between groups. Median values for plasma concentrations of the active moiety and C/D of the active moiety were higher in the perazine group (P < 0.001 and P < 0.001, respectively). Differences were driven by variations in the plasma concentrations and C/D of RIS, which were higher in the perazine group (P < 0.001 and P < 0.001, respectively). Metabolic ratios were lower in the perazine group (P = 0.003). DISCUSSION: The coadministration of perazine in RIS-medicated patients leads to significantly higher plasma concentrations and C/D values of RIS and its active moiety, and a lower metabolic ratio, reflecting the cytochrome P450 (CYP) 2D6 phenotype. We suggest that the mechanism underlying the effect of perazine on RIS metabolism is based on an inhibition of CYP2D6 and CYP3A4 activity.

Effect of smoking on risperidone pharmacokinetics - A multifactorial approach to better predict the influence on drug metabolism.

PURPOSE: To disentangle an association between tobacco smoking, smoking habits and pharmacokinetic patterns such as plasma concentrations of risperidone (RIS), its active metabolite 9-hydroxyrisperidone (9-OH-RIS) and the active moiety, AM, (RIS+9-OH-RIS) in a naturalistic sample. METHODS: Plasma concentrations, dose adjusted plasma concentrations (C/D) of RIS, 9-OH-RIS and AM in patients out of a therapeutic drug monitoring (TDM) database were compared between smokers (n=401) and non-smokers (n=292). RESULTS: Daily dosage of risperidone differed significantly with smokers receiving higher doses than patients in the control group (p=0.001). No differences were detected in plasma concentrations of the active moiety, RIS and 9-OH-RIS (p=0.8 for AM, p=0.646 for RIS and p=0.538 for 9-OH-RIS). However, dose corrected concentrations (C/D) of metabolite (C/D 9-OH-RIS) and active moiety (C/D AM) differed between significantly between groups (p=0.002 and p=0.007). After stratifying smokers to a group of moderate smokers (<20cigarettes/day) (RS1, n=109) and a group of heavy smokers (≥20cigarettes/day) (RS2, n=135), the comparison between non-smokers and both groups only showed lower values of C/D for 9-OH-RIS (p=0.011) for the group of moderate smokers while other pharmacokinetic parameters did not differ. CONCLUSIONS: Apart from the well-known induction of CYP1A2 activity by polycyclic aromatic hydrocarbons, smoking might exert an effect on other CYP isoenzymes as well. A possible interpretation proposes a slight inducing effect of smoking on risperidone metabolism most likely via CYP3A4.

Pharmacokinetic considerations in the treatment of hypertension in risperidone-medicated patients - thinking of clinically relevant CYP2D6 interactions.

BACKGROUND: Treatment of arterial hypertension in patients with severe mental illnesses often results in polypharmacy, potentially leading to drug-drug interactions. The objective of the study was to analyse the in vivo inhibitory potential of two antihypertensive drugs, amlodipine and metoprolol on CYP2D6 catalysed 9-hydroxylation of risperidone (RIS). METHODS: A therapeutic drug monitoring database with plasma concentrations of RIS and 9-hydroxyrisperidone (9-OH-RIS) of 1584 patients was analysed. Three groups were considered; a group of patients receiving RIS without a potentially cytochrome influencing co-medication (control group, R0, n=852), a group co-medicated with amlodipine (RA, n=27) and a group, co-medicated with metoprolol (RM, n=41). Plasma concentrations, concentration-to-dose ratios (C/Ds) of RIS, 9-OH-RIS and the active moiety (AM), as well as the metabolic ratios were computed and compared using the Kruskal-Wallis test, the Mann-Whitney U test and the Jonckheere-Terpstra test to determine the means and different patterns of distribution of plasma concentrations as well as the concentration-to-dose ratios. RESULTS: The median daily dosage of RIS did not differ between the groups (p=0.708). No differences were found in median plasma concentrations of RIS, 9-OH-RIS and AM. However, concentration-to-dose ratios for RIS, 9-OH-RIS and AM were significantly higher in the amlodipine group (p=0.025, p=0.048 and p=0.005). In the metoprolol group, the concentration-to-dose ratio for RIS was significantly higher than in the control group (p=0.017), while the C/D for 9-OH-RIS and AM was not. CONCLUSIONS AND LIMITATIONS: Our data show a potential pharmacokinetic interaction, most likely via CYP3A4 between amlodipine and RIS, reflected in significantly different C/Ds for RIS, 9-OH-RIS and AM. Although the interaction did not result in significantly higher plasma levels, changes in C/Ds and their distribution with regard to the median concentrations were observed.