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Outlook for Predictive Safety TechnologiesPublished by: CHI Insight Pharma Reports Published: Nov. 1, 2006 - 135 Pages Table of ContentsCHAPTER 1. INTRODUCTION 1.1. ADME/Tox: The Cornerstone of Safety Assessments 1.2. Areas of Potential for Improvement of Safety Pharmacology CHAPTER 2. PRECLINICAL SAFETY TESTING AND DRUG DEVELOPMENT COSTS 2.1. Unexpected Toxicity: A Constant Source of Attrition to Pharmaceutical Productivity 2.2. Complex Drug Actions Cause Complex Failures 2.3. A Savings Scenario for a Mid-Sized Drug Developer 2.4. Cutting Back on Research Animal Use CHAPTER 3. ASPECTS OF DRUG SAFETY CONCERNS 3.1. Relative Drug Safety, Not Absolute Toxicity, is the Issue 3.2. Toxicity vs. Side Effects 3.3. The Objective for Predictive Safety Testing 3.4. Mutagenicity and Reproductive Toxicity 3.5. Drug-Drug Interactions and “Metabolic Poisoning” 3.6. High-Throughput Testing: A Challenge for Predictive Safety Assessments 3.7. Knockout Safety Tests with Essentially Unknown Positive Predictive Value CHAPTER 4. PREDICTIVE SAFETY TOOLS AND TECHNOLOGIES 4.1. Toxicogenomics A New Dynamic 4.2. High-Content Cell-Based Screening for Safety Parameters HCS for General Aspects of Drug Safety Rat and Human Hepatocytes Cell Models for Modulation of Cardiac Function In Vitro Nephrotoxicity Evaluation Using Primary Human Kidney Cells HCS for Assessing Hematology Toxicity HCS for Genotoxicity Profiling Biochips as Solid-State Biosensors for Toxicity and Mutagenicity 4.3. Tissue Histology and Tissue Proteomics: Creating Powerful New Tools from Old Ones Pioneering Efforts in Histopathology NeuroScience Associates HistoRX Phase I Molecular Toxicology 4.4. Metabolite Profiling and Metabonomics As a Tool for Toxicity Prediction Metabolite Profiling Predicting Drug Interactions from In Vitro Metabolic Data Predicting Cytochrome P450 Interactions and Inhibition Pharmaco-Metabolomics 4.5. Animal Models The Zebrafish: An Intriguing Vertebrate Model for Toxicity Testing Rodents Tailored for Predictive Toxicology Isogenic Rat Panels Mice Under Realistic Stress Conditions Transgenic Animals for Carcinogenicity Testing Unconventional Animal Models 4.6. In Silico Approaches to Toxicity and Carcinogenicity The ToxML Format: A Platform for Toxicity Data Exchange Structure-Based Prediction of Hepatotoxicity In Silico Identification of Compounds at Risk for Inducing Cardiac Arrythmia Other In Silico Toxicity Prediction Models Commercial Software Packages and Services CHAPTER 5. SAFETY SIGNALS FOR BIOTECH DRUG CANDIDATES: AN EMERGING FIELD 5.1. Cases in Point 5.2. Predictive Safety Testing and Regulatory Authorities The Predictive Safety Testing Consortium: A Spin-Off from the Critical Path Initiative Voluntary Genomics Data Submissions: An Exercise for the Future The FDA’s Intramural Biomarker Program 5.3. The European Innovative Medicines Initiative 5.4. A Synopsis of Facts and Perspectives for Predictive Safety Testing Approaches CHAPTER 6. INTERIVEWS WITH EXPERTS IN THE PREDICTIVE SAFETY TESTING FIELD Felix W. Frueh, PhD, US Food and Drug Administration Joseph F. Contrera, PhD, US Food and Drug Administration Donald Halbert, PhD, Iconix Biosciences D. Lansing Taylor, PhD, Cellumen Michael Milburn, PhD, Metabolon Patricia McGrath, MBA, Phylonix Paul Stroobant, PhD, HistoRx Peter-Jan van Doorn, MD, MBA, MDS Pharma Services Manfred Windisch, PhD, JSW Research APPENDIX A WEB SURVEY OF INDUSTRY EXPERTS HANDLING OR DECIDING PREDICTIVE SAFETY TESTING Glossary Company Index with Web Addresses AbstractUnexpected toxicity is the single greatest cause of pipeline attrition. Despite the fact that a typical preclinical safety program will consume about 1,300 rats and 90 dogs, there is no guarantee that the compound will not present safety problems serious enough to warrant termination. Outlook for Predictive Safety Technologies, a new CHA Advances report, surveys the latest developments in discovery-stage and preclinical predictive safety assessment tools—from in silico methods for lead selection and optimization to high-content cell-based screens, toxicogenomics, tissue proteomics, and advanced animal models. It provides the information and analysis you need to get the best return—in terms of confidence, cost-benefit, and ease of maintenance and use—on your preclinical safety technology investments. Specifically, the report delivers:
Nearly half of the respondents to our survey used some sort of predictive safety technology. Other noteworthy trends revealed in our research:
Outlook for Predictive Safety Technologies is designed to help managers understand the range of technologies available, their pros and cons, and to decide on the one best suited to their organization.
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