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Predictive ADMET
Integrated Approaches in Drug Discovery and Development
Jianling Wang (Author), Laszlo Urban (Author)
9781118299920, Wiley
Hardback, published 30 May 2014
624 pages
24.4 x 16.4 x 3.9 cm, 0.989 kg
“In conclusion, this volume fulfills its promise of being a very useful tool for guidance and diagnosis on ADMET matters, and I would recommend it to any scientist in the field.” (ChemMedChem, 1 June 2015)
This book helps readers integrate in silico, in vitro, and in vivo ADMET (absorption, distribution, metabolism, elimination and toxicity) and PK (pharmacokinetics) data with routine testing applications so that pharmaceutical scientists can diagnose ADMET problems and present appropriate recommendations to move drug discovery programs forward. The book introduces the current clinical practice for drug discovery and development along with the impact on early risk assessment; consolidates the tools and models to intelligently integrate existing in silico, in vitro and in vivo ADMET data; and demonstrates successful cases and lessons learned from real drug discovery and development. In short, it is a book aimed to provide a practical road map for drug discovery and development scientists to generate efficacious and safe drugs for unmet medical needs.
Preface ix Contributors xi I Introduction to the Current Scientific, Clinical, and Social Environment of Drug Discovery and Development 1 Current Social, Clinical, and Scientific Environment of Pharmaceutical R&D 3 2 Polypharmacology and Adverse Bioactivity Profiles Predict Potential Toxicity and Drug-related ADRs 23 II Intelligent Integration and Extrapolation of Admet Data 3 ADMET Diagnosis Models 49 4 PATH (Probe ADME and Test Hypotheses): A Useful Approach Enabling Hypothesis-driven ADME Optimization 63 5 PK-MATRIX—A Permeability: Intrinsic Clearance System for Prediction, Classification, and Profiling of Pharmacokinetics and Drug–drug Interactions 89 6 Maximizing the Power of a Local Model for ADMET-property Prediction 103 7 Chemoinformatic and Chemogenomic Approach to ADMET 125 8 Multiparameter Optimization of ADMET for Drug Design 145 9 PBPK: Integrating In Vitro and In Silico Data in Physiologically Based Models 167 10 Emerging Full Mechanistic Physiologically Based Modeling 189 11 Pharmacokinetic/Pharmacodynamic Modeling in Drug Discovery: A Translational Tool to Optimize Discovery Compounds Toward the Ideal Target-specific Profile 211 III Assessment and Mitigation of Critical Clinically Relevant Admet Risks in Drug Discovery and Development 12 In Vitro–In Silico Tools to Predict Pharmacokinetics of Poorly Soluble Drug Compounds 235 13 Evaluation of the Collective Impact of Passive Permeability and Active Transport on In Vivo Blood-brain Barrier and Gastrointestinal Drug Absorption 263 14 Integrated Assessment of Drug Clearance and Cross-Species Scalability 291 15 Practical Anticipation of Human Efficacious Doses and Pharmacokinetics using Preclinical In Vitro and In Vivo Data 319 16 Management and Mitigation of Human Drug–drug Interaction Risks in the Drug Discovery and Development Phases 353 17 Integrated Assessment and Clinical Translation of In Vitro Off-target Safety Pharmacology Risks 397 18 Integrated Risk Assessment of Cardiovascular Safety in Drug Discovery 407 19 Drug-induced Hepatotoxicity: Advances in Preclinical Predictive Strategies and Tools 433 20 Carcinogenicity and Teratogenicity Assessment 467 21 Nephrotoxicity: Development of Biomarkers for Preclinical and Clinical Application 491 IV Success Stories and Lessons Learned 22 Early Intervention with Formulation Strategies for Multidimensional Problems to Optimize for Success 507 23 Cytochrome P450-mediated Drug Interaction and Cardiovascular Safety: The Seldane to Allegra Transformation 523 24 Clinical Toxicity Profile of VEGF Inhibitors 535 25 Cardiomyopathy: Drug Induced and Predisposed 555 26 Safety Management by Pharmacokinetic Considerations: Ranibizumab (Lucentis) and Bevacizumab (Avastin) 569 Index 583
Laszlo Urban, Jean-Pierre Valentin, Kenneth I Kaitin, and Jianling Wang
Teresa Kaserer, Veronika Temml, and Daniela Schuster
Bernard Faller, Suzanne Skolnik, and Jianling Wang
Leslie Bell, Suzanne Skolnik, and Dallas Bednarczyk
Urban Fagerholm
Sebastien Ronseaux, Jeremy Beck, and Clayton Springer
Virginie Y. Martiny, Ilza Pajeva, Michael Wiese, Andrew M. Davis, and Maria A. Miteva
Matthew D. Segall and Edmund J. Champness
Hannah M. Jones and Neil Parrott
Kiyohiko Sugano
Patricia Schroeder
Christian Wagner and Jennifer B. Dressman
Donna A. Volpe, Hong Shen, and Praveen V. Balimane
Kevin Beaumont, James R. Gosset, and Chris E. Keefer
Tycho Heimbach, Rakesh Gollen, and Handan He
Heidi J. Einolf and Imad Hanna
Patrick Y. Muller and Christian F. Trendelenburg
Gül Erdemli and Ruth L. Martin
Donna M. Dambach
Hans-Jörg Martus, David Beckman, and Lutz Mueller
Frank Dieterle and Estelle Marrer
Stephanie Dodd, Christina Capacci-Daniel, Christopher Towler, Riccardo Panicucci, and Keith Hoffmaster
F. Peter Guengerich
Mark P. S. Sie and Ferry A. L. M. Eskens
Shirley A. Aguirre and Eileen R. Blasi
Nicole H. Siegel and Manju L. Subramanian
Subject Areas: Chemistry [PN]
