Predictive Admet. Integrated Approaches in Drug Discovery and Development

Description

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.

Table of Contents

PREFACE
CONTRIBUTORS

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
  Laszlo Urban, Jean-Pierre Valentin, Kenneth I Kaitin, and Jianling Wang
• 2 Polypharmacology and Adverse Bioactivity Profiles Predict Potential Toxicity and Drug-related ADRs 23
  Teresa Kaserer, Veronika Temml, and Daniela Schuster

II INTELLIGENT INTEGRATION AND EXTRAPOLATION OF ADMET DATA

• 3 ADMET Diagnosis Models 49
  Bernard Faller, Suzanne Skolnik, and Jianling Wang
• 4 PATH (Probe ADME and Test Hypotheses): A Useful Approach Enabling Hypothesis-driven ADME Optimization 63
  Leslie Bell, Suzanne Skolnik, and Dallas Bednarczyk
• 5 PK-MATRIX—A Permeability: Intrinsic Clearance System for Prediction, Classification, and Profiling of Pharmacokinetics and Drug–drug Interactions 89
  Urban Fagerholm
• 6 Maximizing the Power of a Local Model for ADMET-property Prediction 103
  Sebastien Ronseaux, Jeremy Beck, and Clayton Springer
• 7 Chemoinformatic and Chemogenomic Approach to ADMET 125
  Virginie Y. Martiny, Ilza Pajeva, Michael Wiese, Andrew M. Davis, and Maria A. Miteva
• 8 Multiparameter Optimization of ADMET for Drug Design 145
  Matthew D. Segall and Edmund J. Champness
• 9 PBPK: Integrating In Vitro and In Silico Data in Physiologically Based Models 167
  Hannah M. Jones and Neil Parrott
• 10 Emerging Full Mechanistic Physiologically Based Modeling 189
  Kiyohiko Sugano
• 11 Pharmacokinetic/Pharmacodynamic Modeling in Drug Discovery: A Translational Tool to Optimize Discovery Compounds Toward the Ideal Target-specific Profile 211
  Patricia Schroeder

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
  Christian Wagner and Jennifer B. Dressman
• 13 Evaluation of the Collective Impact of Passive Permeability and Active Transport on In Vivo Blood-brain Barrier and Gastrointestinal Drug Absorption 263
  Donna A. Volpe, Hong Shen, and Praveen V. Balimane
• 14 Integrated Assessment of Drug Clearance and Cross-Species Scalability 291
  Kevin Beaumont, James R. Gosset, and Chris E. Keefer
• 15 Practical Anticipation of Human Efficacious Doses and Pharmacokinetics using Preclinical In Vitro and In Vivo Data 319
  Tycho Heimbach, Rakesh Gollen, and Handan He
• 16 Management and Mitigation of Human Drug–drug Interaction Risks in the Drug Discovery and
  Development Phases 353
  Heidi J. Einolf and Imad Hanna
• 17 Integrated Assessment and Clinical Translation of In Vitro Off-target Safety Pharmacology Risks 397
  Patrick Y. Muller and Christian F. Trendelenburg
• 18 Integrated Risk Assessment of Cardiovascular Safety in Drug Discovery 407
  G¨ul Erdemli and Ruth L. Martin
• 19 Drug-induced Hepatotoxicity: Advances in Preclinical Predictive Strategies and Tools 433
  Donna M. Dambach
• 20 Carcinogenicity and Teratogenicity Assessment 467
  Hans-J¨org Martus, David Beckman, and Lutz Mueller
• 21 Nephrotoxicity: Development of Biomarkers for Preclinical and Clinical Application 491
  Frank Dieterle and Estelle Marrer

IV SUCCESS STORIES AND LESSONS LEARNED

• 22 Early Intervention with Formulation Strategies for Multidimensional Problems to Optimize for Success 507
  Stephanie Dodd, Christina Capacci-Daniel, Christopher Towler, Riccardo Panicucci, and Keith Hoffmaster
• 23 Cytochrome P450-mediated Drug Interaction and Cardiovascular Safety: The Seldane to Allegra
  Transformation 523
  F. Peter Guengerich
• 24 Clinical Toxicity Profile of VEGF Inhibitors 535
  Mark P. S. Sie and Ferry A. L. M. Eskens
• 25 Cardiomyopathy: Drug Induced and Predisposed 555
  Shirley A. Aguirre and Eileen R. Blasi
• 26 Safety Management by Pharmacokinetic Considerations: Ranibizumab (Lucentis) and Bevacizumab (Avastin) 569
  Nicole H. Siegel and Manju L. Subramanian

INDEX 583

Author Information

Jianling Wang is the Cambridge Head of Discovery ADME at Novartis Institutes for BioMedical Research. He has published over 40 journal papers, reviews, and book chapters and lectured at over 30 scientific conferences and courses.

Laszlo Urban is the Executive Director for Preclinical Safety Profiling at Novartis Institutes for BioMedical Research. He has over 10 years of experience in academia and 20 years in the pharmaceutical industry. Among Dr. Urban’s publications are over 120 peer-reviewed scientific papers, 3 books including Hit and Lead Profiling: Identification and Optimization of Drug-like Molecules (Wiley, 2009).