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Prediction of Clinical Transporter‐Mediated Drug–Drug Interactions
Citation: CPT Pharmacometrics Syst. Pharmacol. (2020) 9, 211–221; doi:10.1002/psp4.12505 ARTICLE Prediction of Clinical Transporter-Mediated Drug–Drug Interactions via Comeasurement of Pitavastatin and Eltrombopag in Human Hepatocyte Models Simon J. Carter1, Bhavik Chouhan2, Pradeep Sharma3 and Michael J. Chappell1,* A structurally identifiable micro-rate constant mechanistic model was used to describe the interaction between pitavastatin and eltrombopag, with improved goodness-of-fit values through comeasurement of pitavastatin and eltrombopag. Transporter association and dissociation rate constants and passive rates out of the cell were similar between pitavastatin and eltrom- bopag. Translocation into the cell through transporter-mediated uptake was six times greater for pitavastatin, leading to pronounced inhibition of pitavastatin uptake by eltrombopag. The passive rate into the cell was 91 times smaller for pitavas- tatin compared with eltrombopag. A semimechanistic physiologically-based pharmacokinetic (PBPK) model was developed to evaluate the potential for clinical drug–drug interactions (DDIs). The PBPK model predicted a twofold increase in the pita- vastatin peak blood concentration and area under the concentration-time curve in the presence of eltrombopag in simulated healthy volunteers. The use of structural identifiability supporting experimental design combined with robust micro-rate con- stant parameter estimates and a semimechanistic PBPK model gave more informed predictions of transporter-mediated DDIs. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? model fits through micro-rate constants compared with ✔ Currently, most in vitro models are not guided by macro-rate constants in human hepatocytes, with addi- structural identifiability analysis, relying on substrate-only tional information provided regarding transporter binding. -
A Primer on Pharmacology
A primer on pharmacology Universidade do Algarve Faro 2017 by Ferdi Engels, Ph.D. 1 2 1 3 Utrecht university campus ‘de Uithof’ Dept. of Pharmaceutical Sciences Division of Pharmacology 4 2 Bachelor and master education Ferdi Engels, PhD ‐ Associate professor of pharmacology ‐ Director of Undergraduate School of Science PhD training Research expertise 5 for today 1. Understand the main concepts of pharmacokinetics Main concept 2. Be able to apply this new knowledge 6 3 Pharmacology is about drugs………. Drugs = chemicals that alter physiological processes in the body for treatment, prevention, or cure of diseases input output (administration of the drug) (biological response) ‐ dose ‐ no effect ‐ frequency of administration ‐ beneficial effects ‐ route of administration ‐ adverse / toxic effects onset, intensity, and duration of therapeutic effects 7 Pharmacology is about drugs………. Drugs = chemicals that alter physiological processes in the body for treatment, prevention, or cure of diseases What does the body do to the drug? pharmacokinetics What does the drug do to the body? pharmacodynamics 8 4 Thursday, June 15 Lecture on topic 1 Workshop on topic 1 Friday, June 16 Lecture on topic 2 Workshop on topic 2 Course Topic 1 Course Topic 2 9 Rosenbaum ‐ Basic pharmacokinetics and pharmacodynamics: an integrated textbook and computer simulations, 1st ed. (2011) input output (administration of the drug) (biological response) ‐ dose ‐ no effect ‐ frequency of administration ‐ beneficial effects ‐ route of administration ‐ adverse / toxic effects -
Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions□S
Supplemental material to this article can be found at: http://dmd.aspetjournals.org/content/suppl/2006/11/08/dmd.106.012633.DC1.html 0090-9556/07/3502-246–255$20.00 DRUG METABOLISM AND DISPOSITION Vol. 35, No. 2 Copyright © 2007 by The American Society for Pharmacology and Experimental Therapeutics 12633/3169778 DMD 35:246–255, 2007 Printed in U.S.A. Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions□S R. Scott Obach, Robert L. Walsky, and Karthik Venkatakrishnan Pharmacokinetics, Dynamics, and Drug Metabolism (R.S.O., R.L.W.) and Clinical Pharmacology (K.V.), Pfizer, Inc., Groton, Connecticut Received August 30, 2006; accepted November 2, 2006 ABSTRACT: The ability to use vitro inactivation kinetic parameters in scaling to proaches to identifying mechanism-based inactivators were devel- in vivo drug-drug interactions (DDIs) for mechanism-based inacti- oped. Testing potential inactivators at a single concentration (IC25) vators of human cytochrome P450 (P450) enzymes was examined in a 30-min preincubation with human liver microsomes in the Downloaded from using eight human P450-selective marker activities in pooled hu- absence and presence of NADPH followed by assessment of P450 man liver microsomes. These data were combined with other pa- marker activities readily identified those compounds known to be rameters (systemic Cmax, estimated hepatic inlet Cmax, fraction mechanism-based inactivators and represents an approach that unbound, in vivo P450 enzyme degradation rate constants -
1. Disposition and Pharmacokinetics
1. DISPOSITION AND PHARMACOKINETICS The disposition and pharmacokinetics of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and related compounds have been investigated in several species and under various exposure conditions. Several reviews on this subject focus on TCDD and related halogenated aromatic hydrocarbons (Neal et al., 1982; Gasiewicz et al., 1983a; Olson et al., 1983; Birnbaum, 1985; van den Berg et al., 1994). The relative biological and toxicological potency of TCDD and related compounds depends not only on the affinity of these compounds for the aryl hydrocarbon receptor (AhR), but on the species-, strain-, and congener-specific pharmacokinetics of these compounds (Neal et al., 1982; Gasiewicz et al., 1983a; Olson et al., 1983; Birnbaum, 1985; van den Berg et al., 1994, DeVito and Birnbaum, 1995). 2,3,7,8-TCDD and other similar compounds discussed here are rapidly absorbed into the body and slowly eliminated, making body burden (bioaccumulation) a reliable indicator of time- integrated exposure and absorbed dose. Because of the slow elimination kinetics, it will be shown in this section that lipid or blood concentrations, which are often measured, are in dynamic equilibrium with other tissue compartments in the body, making the overall body burden and tissue disposition relatively easy to estimate. Finally, it will be shown that body burdens can be correlated with adverse health effects (Hardell et al., 1995; Leonards et al., 1995), further leading to the choice of body burden as the optimal indicator of absorbed dose and potential effects. 1.1. ABSORPTION/BIOAVAILABILITY FOLLOWING EXPOSURE Gastrointestinal, dermal, and transpulmonary absorptions represent potential routes for human exposure to this class of persistent environmental contaminants. -
The Impact of Assay Acceptance Criteria on Derived Data – Pharmacokinetic Assessment Through Simulation
The Impact of Assay Acceptance Criteria on Derived Data – Pharmacokinetic Assessment Through Simulation Oriol Peris – Charles River Laboratories EBF 2021 EVERY STEP OF THE WAY EVERY STEP OF THE WAY CONFIDENTIAL Objective • Samples analysed using chromatographic assays have an acceptance criteria for QCs of ±15%. In contrast, ligand binding assays have an acceptance criteria for QCs of ±20% • This could potentially lead to a greater variability introduced in samples analysed using ligand binding assays, compared to chromatographic assays. • The aim of this presentation is to assess, from a PK perspective, the impact that the variability associated to each of these methodologies may have in the assessment of the data. To do this: • Plausible data with and without variability needs to be generated • The generated data needs to be assessed using an objective method Methodology: Data generation • Concentration vs time profiles were simulated using open source R software and its library mrgsolve, under different scenarios • Low between subject variability (BSV) and 15% acceptance criterion for QCs • High BSV and 15% acceptance criterion for QCs • Low BSV and 20% acceptance criterion for QCs • High BSV and 20% acceptance criterion for QCs • To do this, it was assumed that all chromatographic and ligand binding assays may introduce up to ± 15 or ± 20% deviation from nominal concentrations • The data was simulated using a population 1 compartment extravascular PK model with parameters CL, Vd and Ka #$%$& • 1 compartment extravascular model � = ' �*&+$- − �*&'$- () &'*&+ Methodology: Data generation • PK compartmental models: • Set of exponential equations that are useful to model a concentration vs time profile • Define the body as divided in separate compartments where a compartment can be the body, blood circulatory system or a set of tissues or organs sharing similar affinity to a drug • PK compartmental models are useful as they are mathematically plausible and their parameters (i.e. -
Monoamine Reuptake Inhibitors in Parkinson's Disease
Hindawi Publishing Corporation Parkinson’s Disease Volume 2015, Article ID 609428, 71 pages http://dx.doi.org/10.1155/2015/609428 Review Article Monoamine Reuptake Inhibitors in Parkinson’s Disease Philippe Huot,1,2,3 Susan H. Fox,1,2 and Jonathan M. Brotchie1 1 Toronto Western Research Institute, Toronto Western Hospital, University Health Network, 399 Bathurst Street, Toronto, ON, Canada M5T 2S8 2Division of Neurology, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, University of Toronto, 399BathurstStreet,Toronto,ON,CanadaM5T2S8 3Department of Pharmacology and Division of Neurology, Faculty of Medicine, UniversitedeMontr´ eal´ and Centre Hospitalier de l’UniversitedeMontr´ eal,´ Montreal,´ QC, Canada Correspondence should be addressed to Jonathan M. Brotchie; [email protected] Received 19 September 2014; Accepted 26 December 2014 Academic Editor: Maral M. Mouradian Copyright © 2015 Philippe Huot et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The motor manifestations of Parkinson’s disease (PD) are secondary to a dopamine deficiency in the striatum. However, the degenerative process in PD is not limited to the dopaminergic system and also affects serotonergic and noradrenergic neurons. Because they can increase monoamine levels throughout the brain, monoamine reuptake inhibitors (MAUIs) represent potential therapeutic agents in PD. However, they are seldom used in clinical practice other than as antidepressants and wake-promoting agents. This review article summarises all of the available literature on use of 50 MAUIs in PD. The compounds are divided according to their relative potency for each of the monoamine transporters. -
The Effect of Altering Brain CYP2B Activity on Nicotine Self-Administration Behaviour and Nicotine Levels in the Brain
The Effect of Altering Brain CYP2B Activity on Nicotine Self-Administration Behaviour and Nicotine Levels in the Brain by Kristine Garcia A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Pharmacology and Toxicology University of Toronto © Copyright by Kristine Garcia 2016 The Effect of Altering Brain CYP2B Activity on Nicotine Self- Administration and Nicotine Levels in the Brain Kristine Garcia Doctor of Philosophy Pharmacology and Toxicology University of Toronto 2016 Abstract Cytochrome P450 (CYP) enzymes play an important role in drug metabolism. While CYPs are abundantly expressed in the liver, where CYP-mediated drug metabolism typically occurs, these enzymes are also expressed in other tissues such as the brain. Local brain drug metabolism can influence the response to drugs that act within the brain. The CYP subfamily 2B (CYP2B) is expressed in the brain and is responsible for metabolizing many central nervous system (CNS)- acting drugs including nicotine, the main psychoactive ingredient in cigarettes. Genetic variation in human CYP2B6 is associated with greater conversion to nicotine dependence and risk of relapse in smokers without influencing peripheral nicotine metabolism. This suggests that local brain nicotine metabolism could influence nicotine levels that in turn mediate nicotine reinforcement and resulting behaviours. The role of brain CYP2B activity in nicotine reinforcement was investigated by injecting a pharmacological CYP2B inhibitor into the brain of rats that then underwent nicotine self-administration (NSA), which models smoking behaviour. Inhibitor-treatment increased NSA acquisition, motivation to obtain nicotine and the number of sessions required to extinguish behaviour, suggesting that inhibiting brain CYP2B activity can augment nicotine-reinforced behaviour. -
Pharmacology Part 2: Introduction to Pharmacokinetics
J of Nuclear Medicine Technology, first published online May 3, 2018 as doi:10.2967/jnmt.117.199638 PHARMACOLOGY PART 2: INTRODUCTION TO PHARMACOKINETICS. Geoffrey M Currie Faculty of Science, Charles Sturt University, Wagga Wagga, Australia. Regis University, Boston, USA. Correspondence: Geoff Currie Faculty of Science Locked Bag 588 Charles Sturt University Wagga Wagga 2678 Australia Telephone: 02 69332822 Facsimile: 02 69332588 Email: [email protected] Foot line: Introduction to Pharmacokinetics 1 Abstract Pharmacology principles provide key understanding that underpins the clinical and research roles of nuclear medicine practitioners. This article is the second in a series of articles that aims to enhance the understanding of pharmacological principles relevant to nuclear medicine. This article will build on the introductory concepts, terminology and principles of pharmacodynamics explored in the first article in the series. Specifically, this article will focus on the basic principles associated with pharmacokinetics. Article 3 will outline pharmacology relevant to pharmaceutical interventions and adjunctive medications employed in general nuclear medicine, the fourth pharmacology relevant to pharmaceutical interventions and adjunctive medications employed in nuclear cardiology, the fifth the pharmacology related to contrast media associated with computed tomography (CT) and magnetic resonance imaging (MRI), and the final article will address drugs in the emergency trolley. 2 Introduction As previously outlined (1), pharmacology is the scientific study of the action and effects of drugs on living systems and the interaction of drugs with living systems (1-7). For general purposes, pharmacology is divided into pharmacodynamics and pharmacokinetics (Figure 1). The principle of pharmacokinetics is captured by philosophy of Paracelsus (medieval alchemist); “only the dose makes a thing not a poison” (1,8,9). -
Antidepressants, Other Review 04/14/2009
Antidepressants, Other Review 04/14/2009 Copyright © 2004 - 2009 by Provider Synergies, L.L.C. All rights reserved. Printed in the United States of America. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, digital scanning, or via any information storage and retrieval system without the express written consent of Provider Synergies, L.L.C. All requests for permission should be mailed to: Attention: Copyright Administrator Intellectual Property Department Provider Synergies, L.L.C. 5181 Natorp Blvd., Suite 205 Mason, Ohio 45040 The materials contained herein represent the opinions of the collective authors and editors and should not be construed to be the official representation of any professional organization or group, any state Pharmacy and Therapeutics committee, any state Medicaid Agency, or any other clinical committee. This material is not intended to be relied upon as medical advice for specific medical cases and nothing contained herein should be relied upon by any patient, medical professional or layperson seeking information about a specific course of treatment for a specific medical condition. All readers of this material are responsible for independently obtaining medical advice and guidance from their own physician and/or other medical professional in regard to the best course of treatment for their specific medical condition. This publication, inclusive of all forms contained herein, is intended to be -
2020 DFS Annual Report
Division of Forensic Science 2020 Annual Report Revised June 29th, 2021 State of Delaware Department of Safety and Homeland Security 200 South Adams Street Wilmington, DE 19801 John Evans, Director Melissa Newell, Deputy Director Dr. Gary Collins, Chief Medical Examiner Jessica Smith, Chief Forensic Toxicologist Amrita Lal-Paterson, DNA Technical Leader Ashley Wang, Forensic Chemistry Unit Leader Johna Esposito, Quality Assurance Manager Table of Contents The Division of Forensic Science ................................................................................................................. 3 Divisional Initiatives, Collaboration, and Information Sharing .................................................................... 4 Overview ................................................................................................................................................... 4 DFSRP- Delaware Forensic Science Reporting System ........................................................................... 5 National Violent Death Reporting System ................................................................................................ 6 Centers for Disease Control Biorepository Program ................................................................................ 6 Delaware Drug Monitoring Initiative........................................................................................................ 7 Disaster Preparation ................................................................................................................................. -
Pharmacokinetic and Pharmacodynamic Interactions Between Antiepileptics and Antidepressants Domenico Italiano University of Messina, Italy
University of Kentucky UKnowledge Psychiatry Faculty Publications Psychiatry 11-2014 Pharmacokinetic and Pharmacodynamic Interactions between Antiepileptics and Antidepressants Domenico Italiano University of Messina, Italy Edoardo Spina University of Messina, Italy Jose de Leon University of Kentucky, [email protected] Right click to open a feedback form in a new tab to let us know how this document benefits oy u. Follow this and additional works at: https://uknowledge.uky.edu/psychiatry_facpub Part of the Psychiatry and Psychology Commons Repository Citation Italiano, Domenico; Spina, Edoardo; and de Leon, Jose, "Pharmacokinetic and Pharmacodynamic Interactions between Antiepileptics and Antidepressants" (2014). Psychiatry Faculty Publications. 40. https://uknowledge.uky.edu/psychiatry_facpub/40 This Article is brought to you for free and open access by the Psychiatry at UKnowledge. It has been accepted for inclusion in Psychiatry Faculty Publications by an authorized administrator of UKnowledge. For more information, please contact [email protected]. Pharmacokinetic and Pharmacodynamic Interactions between Antiepileptics and Antidepressants Notes/Citation Information Published in Expert Opinion on Drug Metabolism & Toxicology, v. 10, Issue 11, p. 1457-1489. © 2014 Taylor & Francis Group This is an Accepted Manuscript of an article published by Taylor & Francis Group in Expert Opinion on Drug Metabolism & Toxicology in Nov. 2014, available online: http://www.tandfonline.com/10.1517/ 17425255.2014.956081 Digital Object Identifier (DOI) http://dx.doi.org/10.1517/17425255.2014.956081 This article is available at UKnowledge: https://uknowledge.uky.edu/psychiatry_facpub/40 1 This is an Accepted Manuscript of an article published by Taylor & Francis Group in Expert Opinion on Drug Metabolism & Toxicology in Nov. -
Pharmacokinetic Models to Characterize the Absorption Phase and the Influence of a Proton Pump Inhibitor on the Overall Exposure of Dacomitinib
pharmaceutics Article Pharmacokinetic Models to Characterize the Absorption Phase and the Influence of a Proton Pump Inhibitor on the Overall Exposure of Dacomitinib Ana Ruiz-Garcia 1, Weiwei Tan 2, Jerry Li 2, May Haughey 2, Joanna Masters 2, Jennifer Hibma 2 and Swan Lin 2,* 1 Metrum Research Group, San Diego, CA 92121, USA; [email protected] 2 Department of Pharmacometrics, Pfizer Inc, San Diego, CA 92121, USA; weiwei.tan@pfizer.com (W.T.); jerry.li@pfizer.com (J.L.); may.haughey@pfizer.com (M.H.); joanna.c.masters@pfizer.com (J.M.); jennifer.e.hibma@pfizer.com (J.H.) * Correspondence: swan.lin@pfizer.com; Tel.: +1-(858)-622-7377 Received: 17 March 2020; Accepted: 3 April 2020; Published: 7 April 2020 Abstract: Introduction: Dacomitinib is an epidermal growth factor receptor (EGFR) inhibitor approved for the treatment of metastatic non-small cell lung cancer (NSCLC) in the first line in patients with EGFR activating mutations. Dacomitinib is taken orally once daily at 45 mg with or without food, until disease progression or unacceptable toxicity occurs. Oncology patients often can develop gastroesophageal reflux disease (GERD), which may require management with an acid-reducing agent. Proton pump inhibitors (PPIs), such as rabeprazole, inhibit sodium-potassium adenosine triphosphatase (H+/K+-ATPase) pumps that stimulate acid secretion in the stomach and have a prolonged pharmacodynamic effect that extends beyond 24 h post-administration. The aim of this work was to characterize the absorption of dacomitinib via modeling with a particular interest in quantifying the impact of rabeprazole on the pharmacokinetics (PK) of dacomitinib.