DOCSLIB.ORG

Front Matter

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Front Matter k Computational Toxicology k k k k Wiley Series on Technologies for the Pharmaceutical Industry Sean Ekins, Series Editor Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals Edited by Sean Ekins Pharmaceutical Applications of Raman Spectroscopy Edited by Slobodan Šašic´ Pathway Analysis for Drug Discovery: Computational Infrastructure and Applications Edited by Anton Yuryev Drug Efficacy, Safety, and Biologics Discovery: Enmerging Technologies and Tools Edited by Sean Ekins and Jinghai J. Xu The Engines of Hippocrates: From the Dawn of Medicine to Medical and Pharmaceutical Informatics Barry Robson and O.K. Baek Pharmaceutical Data Mining: Applications for Drug Discovery Edited by Konstantin V. Balakin The Agile Approach to Adaptive research: Optimizing Efficiency in Clinical Development Michael J. Rosenberg Pharmaceutical and Biomedical Project Management in a Changing Global Environment, Edited by Scott D. Babler k Systems Biology in Drug Discovery and Development k Edited by Daniel L. Young and Seth Michelson Collaborative Computational Technologies for Biomedical Research Edited by Sean Ekins, Maggie A.Z. Hupcey and Antony J. William Predictive Approaches in Drug Discovery and Development: Biomarkers and In Vitro/ In Vivo correlations Edited by J. Andrew Williams, Richard Lalonde, Jeffrey Koup and David D. Christ Collaborative Innovation in Drug Discovery, Strategies for Public and Private Partnerships Edited by Rathnam Chaguturu Computational Toxicology: Risk Assessment for Chemicals Edited by Sean Ekins k k Computational Toxicology Risk Assessment for Chemicals Edited by Sean Ekins k Collaborations Pharmaceuticals, Inc. Raleigh, USA k k k This edition first published 2018 © 2018 John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. The right of Sean Ekins to be identified as the Editor in this work has been asserted in accordance with law. Registered Office John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA Editorial Office 111 River Street, Hoboken, NJ 07030, USA For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com. Wiley also publishes its books in a variety of electronic formats and by print-on-demand. Some content that appears in standard print versions of this book may not be available in other formats. Limit of Liability/Disclaimer of Warranty In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by k sales representatives, written sales materials or promotional statements for this work. The fact that an k organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Library of Congress Cataloging-in-Publication Data: Names: Ekins, Sean, editor. Title: Computational toxicology : risk assessment for chemicals / edited by Sean Ekins. Description: First edition. | Hoboken, NJ : John Wiley & Sons, 2018. | Series: Wiley series on technologies for the pharmaceutical industry | Includes bibliographical references and index. | Identifiers: LCCN 2017037714 (print) | LCCN 2017046458 (ebook) | ISBN 9781119282570 (pdf) | ISBN 9781119282587 (epub) | ISBN 9781119282563 (cloth) Subjects: LCSH: Toxicology–Mathematical models. | Toxicology–Computer simulation. | QSAR (Biochemistry) Classification: LCC RA1199.4.M37 (ebook) | LCC RA1199.4.M37 C66 2018 (print) | DDC 615.90285–dc23 LC record available at https://lccn.loc.gov/2017037714 Cover Design: Wiley Cover Images: (Front cover) Courtesy of Daniela Schuster; (Author photo) Courtesy of Sean Ekins Set in 10/12pt WarnockPro by SPi Global, Chennai, India 10987654321 k k v I should have no objection to go over the same life from its beginning to the end: requesting only the advantage authors have, of correcting in a second edition the faults of the first. Benjamin Franklin k k k k To my family and collaborators. k k k k ix Contents List of Contributors xvii Preface xxi Acknowledgments xxiii Part I Computational Methods 1 1 Accessible Machine Learning Approaches for Toxicology 3 k Sean Ekins, Alex M. Clark, Alexander L. Perryman, Joel S. Freundlich, k Alexandru Korotcov, and Valery Tkachenko 1.1 Introduction 3 1.2 Bayesian Models 5 1.2.1 CDD Models 7 1.3 Deep Learning Models 13 1.4 Comparison of Different Machine Learning Methods 16 1.4.1 Classic Machine Learning Methods 17 1.4.1.1 Bernoulli Naive Bayes 17 1.4.1.2 Linear Logistic Regression with Regularization 18 1.4.1.3 AdaBoost Decision Tree 18 1.4.1.4 Random Forest 18 1.4.1.5 Support Vector Machine 19 1.4.2 Deep Neural Networks 19 1.4.3 Comparing Models 20 1.5 Future Work 21 Acknowledgments 21 References 21 2 Quantum Mechanics Approaches in Computational Toxicology 31 Jakub Kostal 2.1 Translating Computational Chemistry to Predictive Toxicology 31 k k x Contents 2.2 Levels of Theory in Quantum Mechanical Calculations 33 2.3 Representing Molecular Orbitals 38 2.4 Hybrid Quantum and Molecular Mechanical Calculations 39 2.5 Representing System Dynamics 40 2.6 Developing QM Descriptors 42 2.6.1 Global Electronic Parameters 42 2.6.1.1 Electrostatic Potential, Dipole, and Polarizability 43 2.6.1.2 Global Electronic Parameters Derived from Frontier Molecular Orbitals (FMOs) 45 2.6.2 Local (Atom-Based) Electronic Parameters 47 2.6.2.1 Parameters Derived from Frontier Molecular Orbitals (FMOs) 48 2.6.2.2 Partial Atomic Charges 51 2.6.2.3 Hydrogen-Bonding Interactions 51 2.6.2.4 Bond Enthalpies 53 2.6.3 Modeling Chemical Reactions 53 2.6.4 QM/MM Calculations of Covalent Host-Guest Interactions 56 2.6.5 Medium Effects and Hydration Models 59 2.7 Rational Design of Safer Chemicals 61 References 64 k k Part II Applying Computers to Toxicology Assessment: Pharmaceutical, Industrial and Clinical 69 3 Computational Approaches for Predicting hERG Activity 71 Vinicius M. Alves, Rodolpho C. Braga, and Carolina Horta Andrade 3.1 Introduction 71 3.2 Computational Approaches 73 3.3 Ligand-Based Approaches 73 3.4 Structure-Based Approaches 77 3.5 Applications to Predict hERG Blockage 77 3.5.1 Pred-hERG Web App 79 3.6 Other Computational Approaches Related to hERG Liability 82 3.7 Final Remarks 83 References 83 4 Computational Toxicology for Traditional Chinese Medicine 93 Ni Ai and Xiaohui Fan 4.1 Background, Current Status, and Challenges 93 4.2 Case Study: Large-Scale Prediction on Involvement of Organic Anion Transporter 1 in Traditional Chinese Medicine-Drug Interactions 99 k k Contents xi 4.2.1 Introduction to OAT1 and TCM 99 4.2.2 Construction of TCM Compound Database 101 4.2.3 OAT1 Inhibitor Pharmacophore Development 101 4.2.4 External Test Set Evaluation 102 4.2.5 Database Searching 102 4.2.6 Results: OAT1 Inhibitor Pharmacophore 103 4.2.7 Results: OAT1 Inhibitor Pharmacophore Evaluation 104 4.2.8 Results: TCM Compound Database Searching Using OAT1 Inhibitor Pharmacophore 104 4.2.9 Discussion 110 4.3 Conclusion 114 Acknowledgment 114 References 114 5 Pharmacophore Models for Toxicology Prediction 121 Daniela Schuster 5.1 Introduction 121 5.2 Antitarget Screening 125 5.3 Prediction of Liver Toxicity 125 5.4 Prediction of Cardiovascular Toxicity 127 k 5.5 Prediction of Central Nervous System (CNS) Toxicity 128 k 5.6 Prediction of Endocrine Disruption 130 5.7 Prediction of ADME 135 5.8 General Remarks on the Limits and Future Perspectives for Employing Pharmacophore Models in Toxicological Studies 136 References 137 6 Transporters in Hepatotoxicity 145 Eleni Kotsampasakou, Sankalp Jain, Daniela Digles, and Gerhard F. Ecker 6.1 Introduction 145 6.2 Basolateral Transporters 146 6.3 Canalicular Transporters 148 6.4 Data Sources for Transporters in Hepatotoxicity 148 6.5 In Silico Transporters Models 150 6.6 Ligand-Based Approaches 150 6.7 OATP1B1 and OATP1B3 150 6.8 NTCP 154 6.9 OCT1 154 6.10 OCT2 154 6.11 MRP1, MRP3, and MRP4 155 6.12 BSEP 155 6.13 MRP2 156 6.14 MDR1/P-gp 156 k k xii Contents 6.15 MDR3 157 6.16 BCRP 157 6.17 MATE1 158 6.18 ASBT 159 6.19 Structure-Based Approaches 159 6.20 Complex Models Incorporating Transporter Information 160 6.21 In Vitro Models 160 6.22 Multiscale Models 161 6.23 Outlook 162 Acknowledgments 164 References 164 7 Cheminformatics in a Clinical Setting 175 Matthew D.
Load more

Recommended publications
  • Freundlich CV
    Joel S. Freundlich Department of Pharmacology, Physiology & Neuroscience Department of Medicine Center for Emerging and Reemerging Pathogens Rutgers University – New Jersey Medical School Medical Sciences Building, I503 185 South Orange Avenue Newark, NJ 07103 [email protected] (973) 972-7165 (office) (609)-865-7344 (cell) ____________________________________________________________________ RESEARCH INTERESTS Dr. Freundlich leads a research group of eleven scientists pursuing the development and application of computational, chemical, and biological platforms to study infectious diseases. • How do antibacterial small molecules leverage the modulation of more than one target to achieve significant cidality? • How are potent antibacterial agents metabolized by the mammalian host or the bacterium in detoxification and/or activation events with a specific focus on achieving a quantitative mass balance? • How may the properties (physiochemical, ADME, biological) of chemical tools be predicted and then evolved via machine learning methodologies? PROFESSIONAL EXPERIENCE RUTGERS UNIVERSITY-NEW JERSEY MEDICAL SCHOOL, Newark, NJ July 2017 to present Associate professor with Tenure (Department of Pharmacology & Physiology) Associate professor with Tenure (Department of Medicine) Member (Center for Emerging and Reemerging Pathogens) Member (Graduate Program in Medicinal Chemistry) Courses taught: The Chemical Biology of Pathogens GSBS 5160Q – Spring 2015 – 2017 Medical School Foundations II (7 lectures) – Winter 2016 – 2017 Select Agent Biology MSBS N517Q – Spring 2012 - 2013 Pharmacology PHRM 7206 – Spring 2012 - 2018 Advanced Concepts in I3 GSBS 5022Q – Spring 2012, 2013, 2015, 2016 Topics in Pharmacology PHPY-N5030 – Spring 2016 – 2017 Introduction to Genomics, Proteomics, and Bioinformatics MBGC 5002Q – Spring 2015, 2017 – 8 University Activities: Faculty Committee on Appointments and Promotions (2017–) Admissions Committee for M.D./Ph.D.
    [Show full text]
  • Multifaceted Roles of Ultra-Rare and Rare Disease Patients/Parents In
    Drug Discovery Today Volume 18, Numbers 21/22 November 2013 PERSPECTIVE feature Multifaceted roles of ultra-rare and rare disease patients/parents in drug discovery 1,2 3,4 5 2,4,6,7,8,9,10 Jill Wood , Lori Sames , Allison Moore and Sean Ekins , [email protected] 1 Jonah’s Just Begun, P. O. Box 150057, Brooklyn, NY 11215, USA 2 Phoenix Nest, P. O. Box 150057, Brooklyn, NY 11215, USA 3 Hannah’s Hope Fund, P. O. Box 130, Rexford, NY 12148, USA 4 BioGAN Therapeutics, P. O. Box 130, Rexford, NY 12148, USA 5 Hereditary Neuropathy Foundation, 432 Park Avenue South – 4th Floor, New York, NY 10016, USA 6 Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay Varina, NC 27526, USA 7 Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA 94010, USA 8 Department of Pharmaceutical Sciences, University of Maryland, 20 Penn Street, Baltimore, MD 21201, USA 9 PERSPECTIVE Department of Pharmacology, Rutgers University-Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, NJ 08854, USA 10 Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, NC 27599-7355, USA Features Individual parents and patients are increasingly doing more to fund, discover and develop treatments for rare and ultra-rare diseases that afflict their children, themselves or their friends. They are performing roles in business development that would be classed as entrepreneurial; and their organizational roles in driving the science in some cases are equivalent to those of principal investigators. These roles are in addition to their usual positioning as advocates.
    [Show full text]
  • Collaborative Drug Discovery's 10 Anniversary Community Meeting
    Collaborative Drug Discovery’s 10th Anniversary Community Meeting April 4th, 2014 8am-6pm UCSF Mission Bay Conference Center 1675 Owens St. San Francisco, CA 94158 Please use this Twitter hashtag for the event: #CDDx14 Agenda 7:45 Registration - refreshments in Foyer and Exhibition room 8:15 Opening Remarks - with UCSF Host, Stephanie Robertson and CDD CEO, Barry Bunin Collaborative Workflow: Basic and Advanced Use Cases of CDD Vault 8:20 Charlie Weatherall (CDD) & Anna Spektor (CDD) 9:10 Morning Sessions - moderated by Sylvia Ernst (CDD) The Rockefeller University Compound Screening Library 9:15 J. Fraser Glickman (Rockefeller University) Recent Progress in De-Orphanization of Nuclear Receptors 9:40 Ruo Steensma (Orphagen Pharmaceuticals) 10:05 Morning Break - located in the Foyer and Exhibition room Large small molecules in a Small large molecule world 10:35 Leanna Staben (Genentech) Linking the Molecular Structure of Medicines to their Biological Effects 11:00 Bob Volkmann (Systamedic & Mnemosyne Pharmaceuticals) Panel: Externalized Research - What Makes a Good Partnership? Wisdom from Experts 11:25 Who've "Been There - Done That," moderated by Sylvia Ernst (CDD) 11:50 Lunch - boxed lunches in the Foyer and Exhibition room Optional: “What if CDD had...” provide feedback to our product team (12:35) Kellan Gregory (CDD) 10 Years Evolving Our Collaborative Drug Discovery Vaults 1:05 Barry Bunin (CDD) CDD Vault: Noteworthy recent enhancements and a preview of things to come 1:30 David Blondeau (CDD) & Kellan Gregory (CDD) 2:20 Afternoon sessions - moderated Christopher Lipinski The Tuberculosis Drug Accelerator: A New Paradigm For Drug Discovery 2:25 Jerry Shipps (Tuberculosis Drug Accelerator) The role of NIAID in the development of therapeutics for Infectious Diseases 2:50 Martin John Rogers (NIAID) 3:15 Afternoon Break - located in the Foyer and Exhibition Room Targeting the Immunoproteasome 3:40 Dustin L.
    [Show full text]
  • A Weight of Evidence Approach for Improving the Quality in Public
    Keynote Review Towards a Gold Standard: Regarding Quality in Public Domain Chemistry Databases and Approaches to Improving the Situation Antony J. Williams1, Sean Ekins2 and Valery Tkachenko1 1 Royal Society of Chemistry, US Office, 904 Tamaras Circle, Wake Forest, NC-27587, U.S.A. 2 Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC 27526, U.S.A. Corresponding Author: Antony Williams, 904 Tamaras Circle, Wake Forest, NC27587 Email: [email protected] Tel 919-201-1516. Short Biographies Antony J. Williams graduated with a Ph.D. in chemistry as an NMR spectroscopist. Dr Williams is currently VP, Strategic development for ChemSpider at the Royal Society of Chemistry. Dr. Williams has written chapters for many books and authored or >120 peer reviewed papers and book chapters on NMR, predictive ADME methods, internet-based tools, crowdsourcing and database curation. He is an active blogger and participant in the internet chemistry network. Sean Ekins graduated from the University of Aberdeen; receiving his M.Sc., Ph.D. and D.Sc. He is Principal Consultant for Collaborations in Chemistry and Collaborations Director at Collaborative Drug Discovery Inc. He has written over 170 papers and book chapters on topics including drug-drug interaction screening, computational ADME/Tox, collaborative computational technologies and neglected disease research. He has edited or co-edited 4 books. Valery Tkachenko has graduated from the Lomonosov Moscow State University, receiving his M.Sc. in Chemistry and B.Sc. in Computer Sciences. He is currently Chief Technology Officer of ChemSpider at the Royal Society of Chemistry. Over the course of the last 15 years he has participated in development of a number of successful enterprise projects for large pharma and public domain.
    [Show full text]
  • Tilorone: a Broad-Spectrum Antiviral Invented in the USA and Commercialized in Russia and Beyond
    Pharm Res (2020) 37:71 https://doi.org/10.1007/s11095-020-02799-8 PERSPECTIVE Tilorone: a Broad-Spectrum Antiviral Invented in the USA and Commercialized in Russia and beyond Sean Ekins1 & Thomas R. Lane1 & Peter B. Madrid 2 Received: 14 February 2020 /Accepted: 10 March 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020 ABSTRACT For the last 50 years we have known of a HIV Human immunodeficiency virus broad-spectrum agent tilorone dihydrochloride (Tilorone). ICH International Council for Harmonization of This is a small-molecule orally bioavailable drug that was Technical Requirements for Pharmaceuticals for originally discovered in the USA and is currently used clini- Human Use cally as an antiviral in Russia and the Ukraine. Over the years IFN Interferon there have been numerous clinical and non-clinical reports of MARV Marburg virus its broad spectrum of antiviral activity. More recently we have MERS Middle East Respiratory Syndrome identified additional promising antiviral activities against RIG-I Retinoic acid-inducible gene I Middle East Respiratory Syndrome, Chikungunya, Ebola SARS Severe Acute Respiratory Syndrome and Marburg which highlights that this old drug may have VEEV Venezuelan Equine Encephalitis Virus; other uses against new viruses. This may in turn inform the types of drugs that we need for virus outbreaks such as for the new coronavirus severe acute respiratory syndrome coronavi- INTRODUCTION rus 2 (SARS-CoV-2). Tilorone has been long neglected by the west in many respects but it deserves further reassessment in In the last 5 years there have been 2 major Ebola virus out- light of current and future needs for broad-spectrum breaks in Africa (1), the Zika virus in Brazil (2) and currently antivirals.
    [Show full text]
  • CDD 2008 Community Post-Meeting
    Collaborative Drug Discovery Collaborative Drug Discovery Community Users Meeting Tuesday, October 7th, 2008 The J. David Gladstone Institutes Robert W. Mahley Auditorium UCSF Mission Bay Campus, San Francisco, CA 1 Acknowledgements Douglas Crawford, Ph.D., QB3 Millo Pasquini, QB3 Bruce Conklin, M.D., The J. David Gladstone Institutes Catharine Evans, The J. David Gladstone Institutes Where available, speaker presentations and audio recordings are available via links in this document and the meeting web page at Collaborative Drug Discovery Community Users Meeting 2008 . 2 2nd Annual QB3-CDD Community Meeting Schedule 8AM - Register Opens: Socialize over bagels and coffee 8:30-9:30AM - CDD System Training lead by Kellan Gregory Audio 9:30-10:00 - Symposium Registration: Meet participants over coffee 10:00AM - Symposium Welcome: Barry Bunin (CDD) Audio | Slides 10:05-10:30 - Repurposing approved clinical drugs for protozoan diseases David Sullivan, MD, Johns Hopkins Bloomberg School of Public Health 10:30-10:55 - Data Management in an Academic Drug Discovery Program Fred Buckner MD, University of Washington, Department of Medicine 10:55-11:20 - A ‘Broad’ View of Translational Research at the Stanley Center Janice Kranz, PhD, Stanley Center for Psychiatric Research, Broad Institute of MIT 11:20-11:40 - Short Break with Poster Viewing in Lobby and Rooms A & B 11:40-12:05 - Novel drugs for schistosomiasis: establishment of a medium-throughput whole-organism screen at UCSF Conor Caffrey, PhD, Sandler Center, University of California San Francisco
    [Show full text]
  • Dmd # 35113 1 a Predictive Ligand-Based Bayesian
    Downloaded from dmd.aspetjournals.org at ASPET Journals on September 23, 2021 1 and Jinghai J. Xu Xu J. Jinghai and INDUCED LIVER INJURY Sean Ekins, Antony J. Williams DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward. Published on September 15, 2010 as DOI: 10.1124/dmd.110.035113 DMD Fast Forward.
    [Show full text]
  • How Artificial Intelligence Can Change the Pharmaceutical Landscape
    IBSA FOUNDATION PAPERS 16 How Artifi cial Intelligence can change the pharmaceutical landscape XVI Forum October 9th 2019, Lugano Program & Abstract Chairman Andrea Danani Istituto Dalle Molle di studi sull’Intelligenza Artificiale (IDSIA), Lugano, Switzerland; Università della Svizzera italiana (USI), Lugano, Switzerland; Scuola universitaria professionale della Svizzera italiana (SUPSI), Lugano, Switzerland Speakers Alessandro Curioni IBM Research lab, Zurich, Switzerland; Swiss Academy of Engineering Sciences, Zurich, Switzerland Gianni De Fabritiis ICREA, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Acellera, Barcelona, Spain Sean Ekins Collaborations Pharmaceuticals, Inc., Raleigh, United States of America; UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, United States of America Ed J. Griffen MedChemica Ltd., Biohub, Alderley Park, Macclesfield, Cheshire, United Kingdom Jürgen Schmidhuber NNAISENSE, Lugano, Switzerland; Swiss AI Lab Istituto Dalle Molle di studi sull’Intelligenza Artificiale (IDSIA), Manno, Switzerland; Università della Svizzera italiana (USI), Lugano, Switzerland; Scuola universitaria professionale della Svizzera italiana (SUPSI), Lugano, Switzerland Alex Zhavoronkov Insilico Medicine, Hong Kong; Buck Institute for Research on Aging, Novato, United States of America; Biogerontology Research Foundation, London, United Kingdom Scientific Committee Andrea Danani Istituto Dalle Molle di studi sull’Intelligenza Artificiale (IDSIA), Lugano, Switzerland; Università
    [Show full text]
  • Systems-ADME/Tox: Resources and Network Approaches
    Journal of Pharmacological and Toxicological Methods 53 (2006) 38 – 66 www.elsevier.com/locate/jpharmtox Appraisal of state-of-the art Systems-ADME/Tox: Resources and network approaches Sean Ekins * GeneGo, 500 Renaissance Drive, Suite 106, St. Joseph, MI 49085, USA School of Pharmacy Department of Pharmaceutical Sciences, University of Maryland, USA Received 23 May 2005; accepted 23 May 2005 Abstract The increasing cost of drug development is partially due to our failure to identify undesirable compounds at an early enough stage of development. The application of higher throughput screening methods have resulted in the generation of very large datasets from cells in vitro or from in vivo experiments following the treatment with drugs or known toxins. In recent years the development of systems biology, databases and pathway software has enabled the analysis of the high-throughput data in the context of the whole cell. One of the latest technology paradigms to be applied alongside the existing in vitro and computational models for absorption, distribution, metabolism, excretion and toxicology (ADME/Tox) involves the integration of complex multidimensional datasets, termed toxicogenomics. The goal is to provide a more complete understanding of the effects a molecule might have on the entire biological system. However, due to the sheer complexity of this data it may be necessary to apply one or more different types of computational approaches that have as yet not been fully utilized in this field. The present review describes the data generated currently and introduces computational approaches as a component of ADME/Tox. These methods include network algorithms and manually curated databases of interactions that have been separately classified under systems biology methods.
    [Show full text]
  • Transparency in Decision Modelling: What, Why, Who, and How?
    Transparency in decision modelling: what, why, who, and how? Christopher James Sampson1 [ORCID: 0000-0001-9470-2369], The Office of Health Economics, 7th Floor, Southside, 105 Victoria Street, London, SW1E 6QT, United Kingdom Renée Arnold [ORCID: 0000-0001-5935-3220], Arnold Consultancy & Technology, LLC, 15 West 72nd Street - 23rd Floor, New York, NY 10023-3458, United States Stirling Bryan [ORCID: 0000-0001-7093-3058], University of British Columbia, 701-828 West 10th Avenue, Research Pavilion, Vancouver, BC V5Z 1M9, Canada Philip Clarke [ORCID: 0000-0002-7555-5348], University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom Sean Ekins [ORCID: 0000-0002-5691-5790], Collaborations Pharmaceuticals Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC 27606, United States Anthony Hatswell [ORCID: https://orcid.org/0000-0003-1129-326X], Delta Hat, 212 Tamworth Road, Nottingham, NG10 3GS, United Kingdom Neil Hawkins [ORCID: 0000-0003-3199-221X], University of Glasgow, 1 Lilybank Gardens, Glasgow G12 8RZ, United Kingdom Sue Langham [ORCID: 0000-0003-2088-3333], Maverex Limited, 5 Brooklands Place, Brooklands Road, Sale, Cheshire, M33 3SD, United Kingdom Deborah Marshall [ORCID: 0000-0002-8467-8008], University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta T2N 4Z6, Canada Mohsen Sadatsafavi [ORCID: 0000-0002-0419-7862], University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, V6T1Z3, Canada Will Sullivan [ORCID: 0000-0001-5221-7074], BresMed Health Solutions, Steel City House, West Street, Sheffield, S1 2GQ, United Kingdom Edward C F Wilson [ORCID: 0000-0002-8369-1577], Health Economics Group, Norwich Medical School, University of East Anglia, Norwich, NR4 7TJ, United Kingdom Tim Wrightson, Adis Publications, 5 The Warehouse Way, Northcote 0627, Auckland, New Zealand 1 Corresponding author.
    [Show full text]
  • Incorporating Green Chemistry Concepts Into Mobile Chemistry Applications and Their
    Incorporating Green Chemistry Concepts into Mobile Chemistry Applications and Their Potential Uses Sean Ekins*1‡, Alex M. Clark2‡ and Antony J. Williams3‡ 1 Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC 27526, U.S.A. 2 Molecular Materials Informatics, 1900 St. Jacques #302, Montreal, Quebec, Canada H3J 2S1. 3 Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC 27587, U.S.A. *Corresponding author: E-mail: [email protected] KEYWORDS Drug Discovery, Green Chemistry, Mobile Applications, Open Drug Discovery Teams 1 Green Chemistry related information is generally proprietary and papers on the topic are commonly behind pay walls which limits their accessibility. Several new mobile applications (Apps) have been recently released for the Apple iOS platform, which incorporate green chemistry concepts. Due to the large number of people who now own a mobile device across all demographics, this population represents a highly novel way to communicate green chemistry, which has not previously been appreciated. We have made the American Chemical Society Green Chemistry Institute® (ACS GCI) Pharmaceutical Roundtable Solvent Selection Guide more accessible, and increased its visibility by creating a free mobile app for the Apple iOS platform called Green Solvents. We have also used this content for molecular similarity calculations using additional solvents to predict potential environmental and health categories, which could help in solvent selection. This approach predicted the correct waste or health class for over 60% of solvents when the Tanimoto similarity was > 0.5. Additional mobile apps that incorporate green chemistry content or concepts are also described including Open Drug Discovery Teams and Yield101.
    [Show full text]
  • SYSTEMS BIOLOGY in DRUG DISCOVERY and DEVELOPMENT Wiley Series on Technologies for the Pharmaceutical Industry Sean Ekins, Series Editor
    SYSTEMS BIOLOGY IN DRUG DISCOVERY AND DEVELOPMENT Wiley Series on Technologies for the Pharmaceutical Industry Sean Ekins, Series Editor Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals Edited by Sean Ekins Pharmaceutical Applications of Raman Spectroscopy Edited by Slobodan Sasic Pathway Analysis for Drug Discovery: Computational Infrastructure and Applications Edited by Anton Yuryev Drug Efficacy, Safety, and Biologics Discovery: Emerging Technologies and Tools Edited by Sean Ekins and Jinghai J. Xu The Engines of Hippocrates: From the Dawn of Medicine to Medical and Pharmaceutical Informatics Barry Robson and O. K. Baek Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery Edited by Konstantin V. Balakin The Agile Approach to Adaptive Research: Optimizing Efficiency in Clinical Development Michael J. Rosenberg Pharmaceutical and Biomedical Project Management in a Changing Global Environment Edited by Scott D. Babler Systems Biology in Drug Discovery and Development Edited by Daniel L. Young and Seth Michelson Editorial Advisory Board Dr. Renee Arnold (ACT LLC, USA) Dr. David D. Christ (SNC Partners LLC, USA) Dr. Michael J. Curtis (Rayne Institute, St Thomas’ Hospital, UK) Dr. James H. Harwood (Delphi BioMedical Consultants, USA) Dr. Maggie A.Z. Hupcey (PA Consulting, USA) Dr. Dale Johnson (Emiliem, USA) Prof. Tsuguchika Kaminuma (Tokyo Medical and Dental University, Japan) Dr. Mark Murcko (Vertex, USA) Dr. Peter W. Swaan (University of Maryland, USA) Dr. Ana Szarfman (Food and Drug Administration, USA) Dr. David Wild (Indiana University, USA) SYSTEMS BIOLOGY IN DRUG DISCOVERY AND DEVELOPMENT Edited by Daniel L. Young Seth Michelson A JOHN WILEY & SONS, INC., PUBLICATION Copyright © 2012 by John Wiley & Sons, Inc.
    [Show full text]