Benedikt Stegmann

Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology: Update 2017

Authors C. Hiemke1, 2, N. Bergemann3, H. W. Clement4, A. Conca5, J. Deckert6, K. Domschke7, G. Eckermann8, K. Egberts9, M. Gerlach9, C. Greiner10, G. Gründer11, E. Haen12, U. Havemann-Reinecke13, G. Hefner14, R. Helmer15, G. Janssen16, E. Jaquenoud17, G. Laux18, T. Messer19, R. Mössner20, M. J. Müller21, M. Paulzen11, B. Pfuhlmann22, P. Riederer6, A. Saria23, B. Schoppek24, G. Schoretsanitis25, M. Schwarz26, M. Silva Gracia12, B. Stegmann12, W. Steimer27, J. C. Stingl10, M. Uhr28, S. Ulrich29, S. Unterecker6, R. Waschgler30, G. Zernig23, 31, G. Zurek32, P. Baumann33

Risperidone-induced extrapyramidal side effects: is the need for anticholinergics the consequence of high plasma concentrations?

Antipsychotic drugs can induce various undesirable adverse motor reactions, such as extrapyramidal side effects (EPS). A widely accepted pharmacodynamic mechanism underlying EPS includes an increase in striatal D2-receptor occupancy. However, less is known about the pharmacokinetic background of EPS. The aim of this study was to analyze in-vivo possible pharmacokinetic patterns underlying biperiden-treated EPS in risperidone (RIS)-medicated patients. A large therapeutic drug monitoring database containing plasma concentrations of RIS and its metabolite 9-hydroxyrisperidone (9-OH-RIS) of 2293 adult inpatients and outpatients was analyzed. Two groups were compared: a group receiving RIS (n=772) and a group comedicated with biperiden (n=68). Plasma concentrations, dose-adjusted plasma concentrations (C/D) of RIS, 9-OH-RIS, and active moiety (AM) (RIS+9-OH-RIS) as well as ratios of concentrations for metabolite to parent drug (9-OH-RIS/RIS) were computed. We compared the plasma concentrations of the different compounds between the two groups considering the prescription of biperiden as an indirect report of EPS. The daily dosage of RIS did not differ between groups. No differences were detected in case of plasma concentrations and C/D of RIS and active metabolite between the groups. However, plasma concentrations of the AM were significantly higher in the comedicated group (P=0.032) and showed a trend in terms of the active metabolite 9-OH-RIS (P=0.053). Data indicate enhanced AM plasma concentrations of RIS in patients comedicated with biperiden as an EPS treatment. This might underscore an association between higher plasma concentrations of the AM and treatment-requiring EPS.

Body mass index (BMI) but not body weight is associated with changes in the metabolism of risperidone; A pharmacokinetics-based hypothesis.

OBJECTIVE We sought to unravel the influence of body weight and body mass index (BMI), both consistently reported as pharmacokinetic relevant parameters, on metabolism of risperidone in a naturalistic sample. METHODS Conducting non parametrical tests we sought for correlations between plasma concentrations of RIS, 9-OH-RIS and AM and body weight and BMI in patients out of a therapeutic drug monitoring (TDM) database. Further, we stratified patients to three groups based upon BMI values and compared drug concentrations between groups. RESULTS Although body weight failed to correlate with pharmacokinetic parameters, BMI was positively correlated with plasma concentrations of the active metabolite (9-OH-RIS) (rs=0.121, p=0.002) and active moiety (sum of RIS+9-OH-RIS) (rs=0.128, p=0.001) as well as dose adjusted plasma concentrations of the active moiety (rs=0.08, p=0.04). The comparison of pharmacokinetic parameters between different BMI groups yielded lower plasma concentrations of 9-OH-RIS in patients with low BMI (<20kg/m2) and higher plasma concentrations of the active moiety in obese patients (BMI ≥30kg/m2) when compared with the control group (30>BMI≥20kg/m2). By comparing low vs. high BMI patients, the latter group showed higher 9-OH-RIS plasma concentrations. CONCLUSIONS AND LIMITATIONS Considerable alterations in metabolism of risperidone were detected when comparing obese and cachectic patients with the control group in alignment with the positive correlation between BMI values and plasma concentrations of the active metabolite and active moiety as well as dose adjusted plasma concentrations of the active moiety. We suggest changes in CYP2D6 or CYP3A4 activity or differences in P-glycoprotein function in obese patients with greater BMI as a plausible mechanism underlying these alterations.

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.

Pharmacokinetic Drug-Drug Interactions of Mood Stabilizers and Risperidone in Patients Under Combined Treatment.

Background The combination of anticonvulsant mood stabilizers with antipsychotic drugs may lead to clinically relevant drug-drug interactions. The objective of the study was to identify pharmacokinetic interactions of different mood stabilizers on the metabolism of risperidone (RIS) under natural conditions. Methods A large therapeutic drug monitoring database containing plasma concentrations of RIS and its metabolite 9-hydroxy-RIS (9-OH-RIS) of 1,584 adult patients was analyzed. Four groups (n = 1,072) were compared: a control group without a potentially cytochrome interacting comedication (R0, n = 852), a group comedicated with valproate (VPA) (RVPA, n = 153), a group comedicated with lamotrigine (LMT) (RLMT, n = 46), and a group under concomitant medication with carbamazepine (CBZ) (RCBZ, n = 21). Dose-adjusted plasma concentrations (C/D ratio) for RIS, 9-OH-RIS and active moiety (AM) (RIS + 9-OH-RIS), as well as metabolic ratios (RIS/9-OH-RIS) were computed. Results Groups did not differ with regard to the daily dosage (P = 0.46). Differences were detected for the distributions of the C/D ratios for RIS, 9-OH-RIS and AM (P = 0.003, P < 0.001 and P < 0.001, respectively). Differences remained significant after conducting a Bonferroni correction (P = 0.0125). Pairwise comparisons of the concomitant medication groups with the control group revealed significant differences; RIS C/D ratios were significantly higher in the VPA and the LMT group than in the control group (P = 0.013; P = 0.021). However, these differences did not remain significant after Bonferroni correction. In contrast, CBZ-treated patients showed lower dose-adjusted plasma concentrations of 9-OH-RIS (P < 0.001) as well as the AM (P < 0.001) than the control group; this difference survived the Bonferroni correction. Conclusions The data give evidence for pharmacokinetic interactions between RIS and different anticonvulsant mood stabilizers. Carbamazepine decreased serum concentrations of 9-OH-RIS and the AM when compared with the control group. In case of VPA and LMT, findings were less significant; hints for a weak RIS metabolism inhibition by LMT of unclear clinical significance were found.

Depressive Störungen im Kindes- und Jugendalter

OBJECTIVE The present analysis evaluates the prevalence and medication use in inpatients with depression during childhood and adolescence at the KinderAGATE hospitals in 2010. Also discussed are age and sex distribution. METHOD Since 2009 the following information has been recorded anonymously twice a year from each patient at the participating hospitals of KinderAGATE: age, sex, leading diagnosis, prescribed medication and dosage. The data obtained provide an excellent epidemiological basis for the observation of the prescription practice in child and adolescent psychiatry. RESULTS In 2010, 8.4 % of the patients included were treated for a depressive disorder at the KinderAGATE hospitals. This is only a small portion compared to the rates found in adult psychiatry (25.8 % of patients). In our sample male patients diagnosed with depression (58 % DPat, mean age 13.8 years) were treated more often and earlier than female patients (42 % DPat, mean age 15.3 years). Fluoxetine and mirtazapine were the most frequently prescribed substances. Sertraline, escitalopram, and citalopram were also prescribed. CONCLUSION A reserved medical treatment can be observed in child and adolescence psychiatry. Off-label use seems to be nearly unavoidable due to the lack of newly authorized medicine. Moreover, the numerous prescriptions for fluoxetine, the only SSRI currently approved for this age group in Germany, lead to the question of possible unauthorized alternatives.

TDM in psychiatry and neurology: A comprehensive summary of the consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology, update 2017; a tool for clinicians*

Abstract Objectives: Therapeutic drug monitoring (TDM) combines the quantification of drug concentrations in blood, pharmacological interpretation and treatment guidance. TDM introduces a precision medicine tool in times of increasing awareness of the need for personalized treatment. In neurology and psychiatry, TDM can guide pharmacotherapy for patient subgroups such as children, adolescents, pregnant women, elderly patients, patients with intellectual disabilities, patients with substance use disorders, individuals with pharmacokinetic peculiarities and forensic patients. Clear indications for TDM include lack of clinical response in the therapeutic dose range, assessment of drug adherence, tolerability issues and drug–drug interactions. Methods: Based upon existing literature, recommended therapeutic reference ranges, laboratory alert levels, and levels of recommendation to use TDM for dosage optimization without specific indications, conversion factors, factors for calculation of dose-related drug concentrations and metabolite-to-parent ratios were calculated. Results: This summary of the updated consensus guidelines by the TDM task force of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie offers the practical and theoretical knowledge for the integration of TDM as part of pharmacotherapy with neuropsychiatric agents into clinical routine. Conclusions: The present guidelines for TDM application for neuropsychiatric agents aim to assist clinicians in enhancing safety and efficacy of treatment.

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.

Quantification of Methylphenidate, Dexamphetamine, and Atomoxetine in Human Serum and Oral Fluid by HPLC With Fluorescence Detection.

Background: For psychostimulants, a marked individual variability in the dose–response relationship and large differences in plasma concentrations after similar doses are known. Therefore, optimizing the efficacy of these drugs is at present the most promising way to exploit their full pharmacological potential. Moreover, it seems important to examine oral fluid as less invasive biological matrix for its benefit in therapeutic drug monitoring for patients with hyperkinetic disorder. Methods: A high-performance liquid chromatography method for quantification of methylphenidate (MPH), dexamphetamine (DXA), and atomoxetine in serum and oral fluid has been developed and validated. The analytical procedure involves liquid–liquid extraction, derivatization with 4-(4,5-diphenyl-1H-imidazol-2-yl)benzoyl chloride as a label and chromatographic separation on a Phenomenex Gemini-NX C18 analytical column using gradient elution with water–acetonitrile. The derivatized analytes were detected at 330 nm (excitation wavelength) and 440 nm (emission wavelength). To examine the oral fluid/serum ratios, oral fluid samples were collected simultaneously to blood samples from patients with hyperkinetic disorder. Results: The method allows quantification of all analytes in serum and oral fluid within 16 minutes under the same or similar conditions. Oral fluid/serum ratios for MPH and DXA were highly variable and showed an accumulation of these drugs in oral fluid. Conclusions: The developed method covers the determination of MPH, DXA, and atomoxetine concentrations in serum and oral fluid after the intake of therapeutic doses. Oral fluid samples are useful for the qualitative detection of MPH and DXA.

Pharmacokinetic considerations in antipsychotic augmentation strategies : How to combine risperidone with low-potency antipsychotics

Objectives: To investigate in vivo the effect of low‐potency antipsychotics on metabolism of risperidone (RIS). Methods: A therapeutic drug monitoring database containing plasma concentrations of RIS and its metabolite 9‐OH‐RIS of 1584 patients was analyzed. Five groups were compared; a risperidone group (n = 842) and four co‐ medication groups; a group co‐medicated with chlorprothixene (n = 67), a group with levomepromazine (n = 32), a group with melperone (n = 46), a group with pipamperone (n = 63) and a group with prothipendyl (n = 24). Plasma concentrations, dose‐adjusted plasma concentrations (C/D) of RIS, 9‐OH‐RIS and active moiety (RIS + 9‐OH‐RIS; AM) as well as the metabolic ratios (9‐OH‐RIS/RIS; MR) were computed. Results: Differences in plasma concentrations were detected for AM and RIS. Pairwise comparisons revealed significant findings; RIS plasma concentrations were higher in co‐medication groups than in monotherapy group. Chlorprothixene‐ and prothipendyl‐ medicated patients demonstrated no other differences. In the levomepromazine and melperone group plasma and C/D concentrations of AM and RIS were higher, while MRs were lower. For pipamperone, differences included higher C/D values of RIS and lower MRs. Conclusions: Alterations of risperidone metabolism suggest pharmacokinetic interactions for levomepromazine and melperone. In the pipamperone‐group, lower MRs as well as higher plasma and C/D levels of RIS suggest potential interactions. Graphical abstract Figure. No caption available. HighlightsCombining low‐potency antipsychotics with 1st or 2nd generation antipsychotics may lead to pharmacokinetic interactions.Levomepromazine and melperone lead to higher blood concentrations of RIS and 9‐OH‐RIS by inhibiting the CYP2D6 activity.Chlorprothixene, prothipendyl and pipamperone are less likely to lead to risperidone metabolism alterations.