Therapies Under Investigation for Treating Parkinson's Disease
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Prevalence and Type of Potential Pharmacokinetic Drug-Drug Interactions in Old Aged Psychiatric Patients
Contemporary Behavioral Health Care Research Article ISSN: 2058-8690 Prevalence and type of potential pharmacokinetic drug- drug interactions in old aged psychiatric patients Gudrun Hefner1,2*, Stefan Unterecker3, Nagia Ben-Omar4, Margarete Wolf4, Tanja Falter2, Christoph Hiemke1 and Ekkehard Haen4 1Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Germany 2Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Germany 3Department of Psychiatry, Psychosomatics, and Psychotherapy, University Hospital of Würzburg, Germany 4Department of Psychiatry and Psychotherapy, University of Regensburg, Germany Abstract Purpose: The number of prescribed drugs increases with age, and resulting polypharmacy bears the risk of drug-drug interactions (DDI). We assessed the prevalence and type of cytochrome P450 (CYP) associated pharmacokinetic DDI that were considered as clinically relevant in elderly psychiatric patients under conditions of every day pharmacotherapy. Methods: For retrospective analysis a large therapeutic drug monitoring (TDM) data base was used. Patients included were elderly in- and outpatients, aged ≥ 65 years with a psychiatric disorder for whom serum level measurements of a psychotropic drug had been requested. Medication data were examined for co-prescription of clinically relevant CYP inhibitors or inducers and drugs that are substrates of these enzymes (victim drugs). Results: Data from 1243 patients (65.3% female) with a mean (± standard deviation) age of 73 ± 6 years were available for analysis. Mean number of prescribed drugs was 5.3 ± 3.4 per patient. Moderate (n=189, 73.8%) or strong (n=67, 26.2%) CYP inhibitors or inducers were prescribed in 18.9% of all patients. Most frequently prescribed CYP inhibitors were duloxetine (CYP2D6 inhibitor, n=73, 31.7%), melperone (CYP2D6 inhibitor, n=63, 27.4%) and omeprazole (CYP2C19 inhibitor, n=20, 8.7%). -
Pharmacotherapy, Drug-Drug Interactions and Potentially
medRxiv preprint doi: https://doi.org/10.1101/2021.03.31.21254518; this version posted April 6, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Pharmacotherapy, drug-drug interactions and potentially inappropriate medication in depressive disorders Jan Wolff1,2,3, Pamela Reißner4, Gudrun Hefner5, Claus Normann2, Klaus Kaier6, Harald Binder6, Christoph Hiemke7, Sermin Toto8, Katharina Domschke2, Michael Marschollek1, Ansgar Klimke4,9 1 Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Germany. 2 Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. 3 Evangelical Foundation NeuerKerode, Germany. 4 Vitos Hochtaunus, Friedrichsdorf, Germany. 5 Vitos Clinic for Forensic Psychiatry, Eltville, Germany 6 Institute of Medical Biometry and Statistics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany. 7 Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Germany. 8 Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Germany. 9 Heinrich-Heine-University Düsseldorf, Germany. ___ Correspondence Dr. Jan Wolff, Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover, Germany. Address: Karl- Wiechert-Allee 3, 30625 Hannover. Email: [email protected], wolff.jan@mh- hannover.de, ORCID: https://orcid.org/0000-0003-2750-0606 Key words (MeSH) Depression, Polypharmacy, Antidepressants, Hospitals, Drug Interactions, Psychiatry NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. -
The Effects of Antipsychotic Treatment on Metabolic Function: a Systematic Review and Network Meta-Analysis
The effects of antipsychotic treatment on metabolic function: a systematic review and network meta-analysis Toby Pillinger, Robert McCutcheon, Luke Vano, Katherine Beck, Guy Hindley, Atheeshaan Arumuham, Yuya Mizuno, Sridhar Natesan, Orestis Efthimiou, Andrea Cipriani, Oliver Howes ****PROTOCOL**** Review questions 1. What is the magnitude of metabolic dysregulation (defined as alterations in fasting glucose, total cholesterol, low density lipoprotein (LDL) cholesterol, high density lipoprotein (HDL) cholesterol, and triglyceride levels) and alterations in body weight and body mass index associated with short-term (‘acute’) antipsychotic treatment in individuals with schizophrenia? 2. Does baseline physiology (e.g. body weight) and demographics (e.g. age) of patients predict magnitude of antipsychotic-associated metabolic dysregulation? 3. Are alterations in metabolic parameters over time associated with alterations in degree of psychopathology? 1 Searches We plan to search EMBASE, PsycINFO, and MEDLINE from inception using the following terms: 1 (Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Asenapine or Benperidol or Blonanserin or Bromperidol or Butaperazine or Carpipramine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clocapramine or Clopenthixol or Clopentixol or Clothiapine or Clotiapine or Clozapine or Cyamemazine or Cyamepromazine or Dixyrazine or Droperidol or Fluanisone or Flupehenazine or Flupenthixol or Flupentixol or Fluphenazine or Fluspirilen or Fluspirilene or Haloperidol or Iloperidone -
Association Between N-Desmethylclozapine and Clozapine-Induced Sialorrhea
JPET Fast Forward. Published on August 29, 2020 as DOI: 10.1124/jpet.120.000164 This article has not been copyedited and formatted. The final version may differ from this version. 1 Title page Association between N-desmethylclozapine and clozapine-induced sialorrhea: Involvement of increased nocturnal salivary secretion via muscarinic receptors by N- desmethylclozapine Downloaded from Authors and Affiliations: Shuhei Ishikawa, PhD1, 2, a, Masaki Kobayashi, PhD1, 3, *, Naoki Hashimoto, PhD, jpet.aspetjournals.org MD4, Hideaki Mikami, BPharm1, Akihiko Tanimura, PhD5, Katsuya Narumi, PhD1, Ayako Furugen, PhD1, Ichiro Kusumi, PhD, MD4, and Ken Iseki, PhD1 at ASPET Journals on September 23, 2021 1 Laboratory of Clinical Pharmaceutics & Therapeutics, Division of Pharmasciences, Faculty of Pharmaceutical Sciences, Hokkaido University 2 Department of Pharmacy, Hokkaido University Hospital 3 Education Research Center for Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Hokkaido University 4 Department of Psychiatry, Hokkaido University Graduate School of Medicine 5 Department of Pharmacology, School of Dentistry, Health Sciences University of Hokkaido a Present address: Department of Psychiatry, Hokkaido University Hospital JPET Fast Forward. Published on August 29, 2020 as DOI: 10.1124/jpet.120.000164 This article has not been copyedited and formatted. The final version may differ from this version. 2 Running title page Association between N-desmethylclozapine and CIS Corresponding author: Masaki Kobayashi Downloaded from Laboratory of Clinical Pharmaceutics & Therapeutics, Division of Pharmasciences, Faculty of Pharmaceutical Sciences, Hokkaido University, Kita-12-jo, Nishi-6-chome, jpet.aspetjournals.org Kita-ku, Sapporo 060-0812, Japan. Phone/Fax: +81-11-706-3772/3235. E-mail: [email protected] at ASPET Journals on September 23, 2021 Number of text pages: 25 Number of tables: 1 Number of figures: 6 Number of words in the Abstract: 249 Number of words in the Introduction: 686 Number of words in the Discussion: 1492 JPET Fast Forward. -
Rapid and Robust Analysis Method for Quantifying Antidepressants and Major Metabolites in Human Serum by UHPLC-MS/MS
PO-CON1352E Rapid and Robust Analysis Method for Quantifying Antidepressants and Major Metabolites in Human Serum by UHPLC-MS/MS ASMS 2013 WP-095 Vincent Goudriaan1, Christ Pijnenburg2, Jacob Diepenbroek2, Jan Giesbertsen2, Annemieke Vermeulen Windsant-v.d. Tweel2 1Shimadzu Benelux BV, ‘s-Hertogenbosch, Netherlands. 2ZANOB BV, ‘s-Hertogenbosch, Netherlands. Rapid and Robust Analysis Method for Quantifying Antidepressants and Major Metabolites in Human Serum by UHPLC-MS/MS 1. Introduction Therapeutic drug monitoring (TDM) of antidepressants is administered drugs, metabolites or endogenic compounds. one of the most widely utilized analysis in clinical labs in UHPLC-MS/MS is much more sensitive, more selective, and Dutch hospitals nowadays. Traditionally quantitation of if robust the perfect replacement of routine HPLC analysis. antidepressants is performed by means of HPLC with Due to simplified sample prep, faster analysis and less diode-array detection (DAD). Obvious disadvantages of the solvent consumption UHPLC-MS/MS is much more cost latter method are: sensitivity, selectivity and possibility of effective. UHPLC-MS/MS methods will replace routine HPLC false positives as a result of co-elution with other methods in clinical labs. 2. Methods and Materials Human serum samples were extracted by means of off-line solid phase extraction. The extracts were analyzed with a Shimadzu Nexera UHPLC combined with a LCMS-8040 Tandem Mass Spectrometer. 5 µL of sample was injected with a SIL-30AC autosampler. 2-1. Sample Preparation Standards both for calibration and control are ready made serum standards. The standards are pretreated in the same way as the samples. 1. Precondition SPE material1 with 1 mL 3% ammonia in acetonitrile 2. -
Antipsychotics
The Fut ure of Antipsychotic Therapy (page 7 in syllabus) Stepp,,hen M. Stahl, MD, PhD Adjunct Professor, Department of Psychiatry Universityyg of California, San Diego School of Medicine Honorary Visiting Senior Fellow, Cambridge University, UK Sppyonsored by the Neuroscience Education Institute Additionally sponsored by the American Society for the Advancement of Pharmacotherapy This activity is supported by an educational grant from Sunovion Pharmaceuticals Inc. Copyright © 2011 Neuroscience Education Institute. All rights reserved. Individual Disclosure Statement Faculty Editor / Presenter Stephen M. Stahl, MD, PhD, is an adjunct professor in the department of psychiatry at the University of California, San Diego School of Medicine, and an honorary visiting senior fellow at the University of Cambridge in the UK. Grant/Research: AstraZeneca, BioMarin, Dainippon Sumitomo, Dey, Forest, Genomind, Lilly, Merck, Pamlab, Pfizer, PGxHealth/Trovis, Schering-Plough, Sepracor/Sunovion, Servier, Shire, Torrent Consultant/Advisor: Advent, Alkermes, Arena, AstraZeneca, AVANIR, BioMarin, Biovail, Boehringer Ingelheim, Bristol-Myers Squibb, CeNeRx, Cypress, Dainippon Sumitomo, Dey, Forest, Genomind, Janssen, Jazz, Labopharm, Lilly, Lundbeck, Merck, Neuronetics, Novartis, Ono, Orexigen, Otsuka, Pamlab, Pfizer, PGxHealth/Trovis, Rexahn, Roche, Royalty, Schering-Plough, Servier, Shire, Solvay/Abbott, Sunovion/Sepracor, Valeant, VIVUS, Speakers Bureau: Dainippon Sumitomo, Forest, Lilly, Merck, Pamlab, Pfizer, Sepracor/Sunovion, Servier, Wyeth Copyright © 2011 Neuroscience Education Institute. All rights reserved. Learninggj Objectives • Differentiate antipsychotic drugs from each other on the basis of their pharmacological mechanisms and their associated therapeutic and side effects • Integrate novel treatment approaches into clinical practice according to best practices guidelines • Identify novel therapeutic options currently being researched for the treatment of schizophrenia Copyright © 2011 Neuroscience Education Institute. -
Screening of 300 Drugs in Blood Utilizing Second Generation
Forensic Screening of 300 Drugs in Blood Utilizing Exactive Plus High-Resolution Accurate Mass Spectrometer and ExactFinder Software Kristine Van Natta, Marta Kozak, Xiang He Forensic Toxicology use Only Drugs analyzed Compound Compound Compound Atazanavir Efavirenz Pyrilamine Chlorpropamide Haloperidol Tolbutamide 1-(3-Chlorophenyl)piperazine Des(2-hydroxyethyl)opipramol Pentazocine Atenolol EMDP Quinidine Chlorprothixene Hydrocodone Tramadol 10-hydroxycarbazepine Desalkylflurazepam Perimetazine Atropine Ephedrine Quinine Cilazapril Hydromorphone Trazodone 5-(p-Methylphenyl)-5-phenylhydantoin Desipramine Phenacetin Benperidol Escitalopram Quinupramine Cinchonine Hydroquinine Triazolam 6-Acetylcodeine Desmethylcitalopram Phenazone Benzoylecgonine Esmolol Ranitidine Cinnarizine Hydroxychloroquine Trifluoperazine Bepridil Estazolam Reserpine 6-Monoacetylmorphine Desmethylcitalopram Phencyclidine Cisapride HydroxyItraconazole Trifluperidol Betaxolol Ethyl Loflazepate Risperidone 7(2,3dihydroxypropyl)Theophylline Desmethylclozapine Phenylbutazone Clenbuterol Hydroxyzine Triflupromazine Bezafibrate Ethylamphetamine Ritonavir 7-Aminoclonazepam Desmethyldoxepin Pholcodine Clobazam Ibogaine Trihexyphenidyl Biperiden Etifoxine Ropivacaine 7-Aminoflunitrazepam Desmethylmirtazapine Pimozide Clofibrate Imatinib Trimeprazine Bisoprolol Etodolac Rufinamide 9-hydroxy-risperidone Desmethylnefopam Pindolol Clomethiazole Imipramine Trimetazidine Bromazepam Felbamate Secobarbital Clomipramine Indalpine Trimethoprim Acepromazine Desmethyltramadol Pipamperone -
Emea/666243/2009
European Medicines Agency London, 29 October 2009 EMEA/666243/2009 ISSUE NUMBER: 0910 MONTHLY REPORT PHARMACOVIGILANCE WORKING PARTY (PHVWP) OCTOBER 2009 PLENARY MEETING The CHMP Pharmacovigilance Working Party (PhVWP) held its October 2009 plenary meeting on 19-21 October 2009. PhVWP DISCUSSIONS ON SAFETY CONCERNS Below is a summary of the discussions regarding non-centrally authorised medicinal products in accordance with the PhVWP publication policy (see under http://www.emea.europa.eu/htms/human/phv/reports.htm). Positions agreed by the PhVWP for non- centrally authorised products are recommendations to Member States. For safety updates concerning centrally authorised products and products subject to ongoing CHMP procedures, readers are referred to the CHMP Monthly Report (see under http://www.emea.europa.eu/pressoffice/presshome.htm). The PhVWP provides advice on these products to the Committee of Medicinal Products for Human Use (CHMP) upon its request. Antipsychotics - risk of venous thromboembolism (VTE) Identify risk factors for VTE for preventive action before and during treatment with antipsychotics The PhVWP completed their review on the risk of VTE of antipsychotics1. The review was triggered by and based on data from the UK spontaneous adverse drug reactions reporting system and the published literature. The PhVWP carefully considered the data, including the limitations of both information sources, such as the lack of randomised controlled trial data, the heterogeneity of published studies and the potential confounding factors such as sedation and weight gain, commonly present in antipsychotic users. The PhVWP concluded that an association between VTE and antipsychotics cannot be excluded. Distinguishing different risk levels between the various active substances was not possible. -
Pharmacokinetic Considerations in Antipsychotic Augmentation Strategies: How to Combine Risperidone with Low-Potency Antipsychotics
Progress in Neuro-Psychopharmacology & Biological Psychiatry 76 (2017) 101–106 Contents lists available at ScienceDirect Progress in Neuro-Psychopharmacology & Biological Psychiatry journal homepage: www.elsevier.com/locate/pnp Pharmacokinetic considerations in antipsychotic augmentation strategies: How to combine risperidone with low-potency antipsychotics Michael Paulzen a,b,1, Georgios Schoretsanitis a,b,f,⁎,1, Benedikt Stegmann d,ChristophHiemkeg,h, Gerhard Gründer a,b,KoenR.J.Schruerse, Sebastian Walther f, Sarah E. Lammertz a,b,EkkehardHaenc,d a Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany b JARA – Translational Brain Medicine, Aachen, Germany c Clinical Pharmacology, Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany d Department of Pharmacology and Toxicology, University of Regensburg, Regensburg, Germany e Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands f University Hospital of Psychiatry, Bern, Switzerland g Department of Psychiatry and Psychotherapy, University Medical Center of Mainz, Germany h Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center of Mainz, Germany article info abstract Article history: Objectives: To investigate in vivo the effect of low-potency antipsychotics on metabolism of risperidone (RIS). Received 22 December 2016 Methods: A therapeutic drug monitoring database containing plasma concentrations of RIS and its metabolite 9-OH- Accepted 12 March 2017 RIS of 1584 patients was analyzed. Five groups were compared; a risperidone group (n = 842) and four co- med- Available online 14 March 2017 ication 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). -
LEGISLATIVE ASSEMBLY Question on Notice
LEGISLATIVE ASSEMBLY Question On Notice Thursday, 15 February 2018 2560. Ms M. M Quirk to the Minister for Police; I refer to the commencement of operation of the Road Traffic Amendment Act 2016 in March 2017 which introduced compulsory blood or urine samples to be taken from drivers involved in serious crashes, and I ask: (a) since March 2017 how many such samples have been taken; (b) for what specific substances are those blood or urine samples tested; (c) what are the results of those tests to date; and (d) what percentage of drivers have been found to have ingested more than one substance capable of impairing driving skills? Answer (a) The compulsory taking of blood from all drivers involved in serious crashes commenced on 10 March 2017. Between 10 March 2017 and 22 February 2018 (inclusive) a total of 398 blood test samples have been collected under the provision of the Road Traffic Amendment Act 2016. There have been no urine tests collected. (b) Please see attached table for a list of substances in blood sample that are identifiable in ChemCentre toxicology analysis (Paper Number). (c) Of the 398 blood samples collected, 48 are pending results of ChemCentre analysis. Of the 350 analysed, 259 samples had a specific substance(s) detected and 91 samples had no specific substance detected. d) Of the 259 samples with specific substance(s) detected, 92% were found to have multiple substances (more than one). Detectable Substances in Blood Samples capable of identification by the ChemCentre WA. ACETALDEHYDE AMITRIPTYLINE/NORTRIPTYLINE -
Neuromodulators for Functional Gastrointestinal Disorders (Disorders of Gutlbrain Interaction): a Rome Foundation Working Team Report Douglas A
Gastroenterology 2018;154:1140–1171 SPECIAL REPORT Neuromodulators for Functional Gastrointestinal Disorders (Disorders of GutLBrain Interaction): A Rome Foundation Working Team Report Douglas A. Drossman,1,2 Jan Tack,3 Alexander C. Ford,4,5 Eva Szigethy,6 Hans Törnblom,7 and Lukas Van Oudenhove8 1Center for Functional Gastrointestinal and Motility Disorders, University of North Carolina, Chapel Hill, North Carolina; 2Center for Education and Practice of Biopsychosocial Care and Drossman Gastroenterology, Chapel Hill, North Carolina; 3Translational Research Center for Gastrointestinal Disorders, University of Leuven, Leuven, Belgium; 4Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, United Kingdom; 5Leeds Gastroenterology Institute, St James’s University Hospital, Leeds, United Kingdom; 6Departments of Psychiatry and Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania; 7Departments of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; and 8Laboratory for BrainÀGut Axis Studies, Translational Research Center for Gastrointestinal Disorders, University of Leuven, Leuven, Belgium BACKGROUND & AIMS: Central neuromodulators (antide- summary information and guidelines for the use of central pressants, antipsychotics, and other central nervous neuromodulators in the treatment of chronic gastrointestinal systemÀtargeted medications) are increasingly used for treat- symptoms and FGIDs. Further studies are needed to confirm ment -
Concentrations of Antidepressants, Antipsychotics, and Benzodiazepines in Hair Samples from Postmortem Cases
SN Comprehensive Clinical Medicine (2020) 2:284–300 https://doi.org/10.1007/s42399-020-00235-x MEDICINE Concentrations of Antidepressants, Antipsychotics, and Benzodiazepines in Hair Samples from Postmortem Cases Maximilian Methling1,2 & Franziska Krumbiegel1 & Ayesha Alameri1 & Sven Hartwig1 & Maria K. Parr2 & Michael Tsokos1 Accepted: 30 January 2020 /Published online: 10 February 2020 # The Author(s) 2020 Abstract Certain postmortem case constellations require intensive investigation of the pattern of drug use over a long period before death. Hair analysis of illicit drugs has been investigated intensively over past decades, but there is a lack of comprehensive data on hair concentrations for antidepressants, antipsychotics, and benzodiazepines. This study aimed to obtain data for these substances. A LC-MS/MS method was developed and validated for detection of 52 antidepressants, antipsychotics, benzodiazepines, and metabolites in hair. Hair samples from 442 postmortem cases at the Institute of Legal Medicine of the Charité-University Medicine Berlin were analyzed. Postmortem hair concentrations of 49 analytes were obtained in 420 of the cases. Hair sample segmentation was possible in 258 cases, and the segments were compared to see if the concentrations decreased or increased. Descriptive statistical data are presented for the segmented and non-segmented cases combined (n = 420) and only the segmented cases (n = 258). An overview of published data for the target substances in hair is given. Metabolite/parent drug ratios were investigated for 10 metabolite/parent drug pairs. Cases were identified that had positive findings in hair, blood, urine, and organ tissue. The comprehensive data on postmortem hair concentrations for antidepressants, antipsychotics, and benzodiazepines may help other investigators in their casework.