Drug Discovery Toxicology: From Target Assessment to Translational Biomarkers [Will - Wiley - Blackwell]
- ISBN/EAN
- 9781119053330
- Editore
- Wiley - Blackwell
- Formato
- Cartonato
- Anno
- 2016
- Pagine
- 584
Disponibile
175,50 €
As a guide for pharmaceutical professionals to the issues and practices of drug discovery toxicology, this book integrates and reviews the strategy and application of tools and methods at each step of the drug discovery process.
• Guides researchers as to what drug safety experiments are both practical and useful
• Covers a variety of key topics – safety lead optimization, in vitro-in vivo translation, organ toxicology, ADME, animal models, biomarkers, and –omics tools
• Describes what experiments are possible and useful and offers a view into the future, indicating key areas to watch for new predictive methods
• Features contributions from firsthand industry experience, giving readers insight into the strategy and execution of predictive toxicology practices
Maggiori Informazioni
| Autore | Will Yvonne; McDuffie J. Eric; Olaharski Andrew J.; Jeffy Brandon D. |
|---|---|
| Editore | Wiley - Blackwell |
| Anno | 2016 |
| Tipologia | Libro |
| Lingua | Inglese |
| Indice | PART I. INTRODUCTION 1. EMERGING TECHNOLOGIES AND THEIR ROLE IN REGULATORY REVIEW Thomas Colatsky 1.1 INTRODUCTION 1.2 Safety Assessment in Drug Development and Review 1.2.1 Drug discovery 1.2.2 Preclinical development 1.3 The Role of New Technologies in Regulatory Safety Assessment 1.3.1 In silico models for toxicity prediction 1.3.2 Cell-Based Assays for Toxicity Prediction 1.4 CONCLUSIONS REFERENCES PART II. SAFETY LEAD OPTIMIZATION STRATEGIES 2. Small Molecule Safety Lead Optimization Donna Dambach 2.1 Background and Objectives of Safety Lead Optimization Approaches 2.2 Target Safety Assessments: Evaluation of Undesired Pharmacology and Therapeutic Area Consideration 2.3 Implementing Lead Optimization Strategies for Small Molecules 2.3.1 Strategic Approach 2.3.2 Application of Prospective Models 2.3.3 Selectivity and Secondary Pharmacology Assessments 2.3.4 Intrinsic Cytotoxicity Assessments 2.3.5 Focused Target Organ Assessments 2.3.6 ADME Assessments Related to Toxicity 2.3.7 Genotoxicity Assessments 2.3.8 Application of Retrospective Models 2.4 Conclusions References 3. Safety Assessment Strategies and Predictive Safety of Biopharmacueticals and Antibody Drug Conjugates Michelle Horner, Mary-Jane Hinrichs, Nicholas Buss 3.1 Background and objectives 3.2 Target Safety Assessments: Strategies to Understand Target Biology and Associated Liabilities 3.3 Strategic Approaches for Biopharmaceuticals and Antibody Drug Conjugates (ADCs) 3.4 Predictive Safety Tools for large molecules 3.5 Predicting and Assessing unintended adverse consequences 3.6 Strategies for Species Selection 3.7 Strategy for Dose-ranging studies for safety evaluation of biopharmaceuticals 3.8 Conclusions References 4. Discovery and Development Strategies for Small Interfering RNAs Scott Barros, Gregory Hinkle 4.1 Background 4.2 Target Assessments 4.3 siRNA Design and Screening Strategies 4.4 Safety Lead Optimization of siRNA 4.5 Integration of Lead Optimization Data for Candidate Selection and Development 4.6 Conclusions References PART III. BASIS FOR IN VITRO - IN VIVO PK TRANSLATION 5. Physicochemistry and the off target effects of drug molecules Dennis Smith 5.1 Lipohilicity, polar surface area and lipoidal permeability 5.2 Physicochemistry and basic ADME properties for high lipoidal permeability drugs 5.3 Relationship between Volume of Distribution (Vd) and Target Access for passively distributed drugs 5.4 Basicity, lipophilicity and volume of distribution as a predictor of toxicity (T): adding the T to ADMET 5.5 Basicity and lipophilicity as a predictor of toxicity (T): separating the D from T in ADMET 5.6 Lipophilicity and polar surface area as a predictor of toxicity): adding the T to ADMET 5.7 Metabolism and physicochemical properties 5.8 Concentration of compounds by transporters 5.9 Inhibition of excretion pumps 5.10 Conclusion References 6. The need for exposure projection in the interpretation of preclinical in vitro and in vivo ADME tox data Patrick Poulin 6.1 Introduction 6.2 Methodology used for human PK projection in drug discovery 6.2.1 Prediction of plasma concentration-time profile by using the Wajima allometric method 6.2.2 Prediction of plasma and tissue concentration-time profiles by using the PBPK modeling approach 6.2.3 Integrative approaches of toxicity prediction based on the extent of tissue distribution 6.3 Summary of the take-home messages from the PhRMA CPCDC Initiative on Predictive Models of Human PK from 2011 6.3.1 PhRMA initiative on the prediction of clearance 6.3.2 PhRMA initiative on the prediction of volume of distribution 6.3.3 PhRMA initiative on the prediction of concentration-time profile 6.3.4 Lead commentaries on the PhRMA initiative References 7. ADME properties leading to toxicity Katya Tsaioun 7.1. Introduction 7.2. The Science of ADME 7.3. The ADME Optimization Strategy 7.4. Conclusions and Future Directions References PART IV. PREDICTING ORGAN TOXICITY 8. Liver Gerry Kenna, Mikael Persson, Scott Siler, Ke Yu, Weida Tong, Joshua Xu, Minjun Chen, Chuchu Hu, Yvonne Will, Mike Aleo 8.1. Introduction 8.2. DILI mechanisms and susceptibility 8.3. Common Mechanisms that contribute to DILI 8.3.1 Mitochondrial injury 8.3.2 Reactive metabolite mediated toxicity 8.3.3 Bile Salt Export Pump (BSEP) inhibition 8.3.4 Complicity between dual inhibitors of BSEP and mitochondrial function 8.4. Models Systems Used to Study DILI 8.4.1 High content image analysis 8.4.2 Complex cell models 8.4.3 Zebrafish 8.5. In Silico Models 8.6. Systems pharmacology and DILI 8.7. Summary References 9. Cardiac David Gallacher, Robert Hamlin, Gary Gintant, Hugo Vargas, Kimberly Hoagland, Najah Abi-Gergis, HR Lu 9.1 General Introduction 9.2 Classical In Vitro/Ex Vivo Assessment of Cardiac Electrophysiologic Effects 9.2.1 Introduction 9.2.2 Subcellular techniques 9.2.3 Ionic currents 9.2.4 Action potentials/Repolarization assays 9.2.5 Proarrhythmia assays 9.2.6 Future directions 9.2.7 Conclusions 9.3 Cardiac ion channels and in silico prediction 9.4 From Animal Ex-vivo/in vitro models to Human Stem Cell-Derived Cardiomyocytes for Cardiac Safety Testing 9.4.1 Introduction 9.4.2 Currently available technologies 9.4.3 Conclusions 9.5 In Vivo Telemetry Capabilities and Preclinical Drug Development 9.6 Assessment of myocardial contractility in preclinical models 9.7 Assessment of large versus small molecules in cardiovascular safety pharmacology 9.8 Patients do not necessarily respond to drugs and devices as do genetically-identical, young-mature, healthy mice! 10. Predictive In Vitro Models for Assessment of Nephrotoxicity and Drug-Drug Interactions in Vitro Lawrence Lash 10.1. Introduction 10.1.1 Considerations for studying the kidneys as a target organ for drugs and toxic chemicals 10.1.2 Advantages and limitations of in vitro models in general for mechanistic toxicology and screening of potential adverse effects 10.1.3 Types of in vitro models available for studying human kidneys 10.2 Biological processes and toxic responses of the kidneys that are normally measured in toxicology research and drug development studies 10.3 Primary cultures of human proximal tubular (hPT) cells 10.3.1 Methods for hPT cell isolation 10.3.2 Validation of hPT primary cell cultures 10.3.3 Advantages and limitations of hPT primary cell cultures 10.3.4 Genetic polymorphisms and interindividual susceptibility 10.4 Toxicology studies in hPT primary cell cultures 10.5 Critical studies for drug discovery in hPT primary cell cultures 10.5.1 Phase I and Phase II drug metabolism 10.5.2. Membrane transport 10.6 Summary and conclusions 10.6.1 Advantages and limitations of performing studies in hPT primary cell cultures 10.6.2 Future Directions REFERENCES 11. Predicting organ toxicity in vitro: Bone marrow Ivan Rich, Andrew Olaharski 11.1 Introduction 11.2 Biology of the hematopoietic system 11.3 Hemotoxicity 11.4 Measuring hemotoxicity 11.5 Proliferation or differentiation? 11.6 Measuring and Predicting Hemotoxicity in vitro 11.7 Detecting Stem and Progenitor Cell Downstream Events 11.8 Bone marrow toxicity testing during drug development 11.9 Predicting Starting Doses for Animal and Human Clinical Trials 11.10 Future Trends 11.11 Conclusions References 12. Predicting Organ Toxicity In Vitro: Dermal Toxicity Patrick Hayden, Michael Bachelor 12.1 Introduction 12.2. Overview of drug-induced adverse cutaneous reactions 12.3. Overview of In Vitro skin models with relevance to preclinical drug development 12.4 Specific applications of in vitro skin models and predictive in vitro assays relevant to pharmaceutical development 12.4.1 Skin sensitization 12.4.2 phototoxicity 12.4.3 Skin irritation 12.5 Mechanism based cutaneous adverse effects 12.5.1 Percutaneous absorption 12.5.2 Genotoxicity 12.5.3 Skin Lightening/melanogenesis 12.6. Summary References 13. In Vitro Methods in Immunotoxicity Assessment Xu Zhu, Ellen Evans 13.1. Introduction and Perspectives on In Vitro Immunotoxicity Screening 13.2. Overview of the Immune System 13.3. Examples of In Vitro Approaches 13.3.1 Acquired Immune Responses 13.3.2 Fc Receptor/Complement Binding 13.3.3 Assessment of Hypersensitivity 13.3.4 Immunogenicity of Biologics 13.3.5 Immunotoxicity Due to Myelotoxicity 13.4 Conclusions References 14. Strategies and assays for minimizing risk of ocular toxicity during early development of systemically administered drugs Chris Somps, Jay Forner, Kerri Cannon, Wenhu Huang, Paul Butler 14.1. Introduction 14.2. In silico and In vitro tools and strategies 14.3. Higher throughput in vivo tools and strategies 14.3.1. Ocular reflexes and associated behaviors 14.3.2 Routine eye examinations 14.4. Strategies, gaps and emerging technologies 14.4.1 Strategic deployment of in silico, in vitro, and in vivo tools 14.4.2 Emerging biomarkers of retinal toxicity 14.5. Summary References 15. Predicting organ toxicity in vitro - Central Nervous System Greet Teuns, Alison Easter 15.1. Introduction 15.2. Models for assessment of CNS ADRs 15.2.1. In vivo behavioral batteries 15.2.2. In vitro models 15.3. Seizure Liability Testing 15.3.1. Introduction 15.3.2. Medium/high throughput approaches to assess seizure liability of drug candidates 15.3.3. In vivo approaches to assess seizure liability of drug candidates 15.4. Drug Abuse Liability Testing 15.4.1. Introduction 15.4.2. Preclinical models to test abuse potential of CNS-active drug candidates 15.5. General Conclusions References 16. Biomarkers, Cell Models and In Vitro Assays for Gastrointestinal Toxicology Gina Yanochko, Allison Vitsky 16.1. Introduction 16.2. Anatomic and physiologic considerations 16.2.1 Oral Cavity 16.2.2 Esophagus 16.2.3 Stomach 16.2.4 Small and large intestine 16.3. GI Biomarkers 16.3.1 Biomarkers of epithelial mass, intestinal function, or cellular damage 16.3.2 Biomarkers of inflammation 16.4. Cell Models of the GI Tract 16.4.1 Cell lines and primary cells 16.4.2 Induced pluripotent stem cells 16.4.3 Co-culture systems 16.4.4 3-D organoid models 16.4.5 Organs-on-a-chip 16.5. Cell-Based In Vitro Assays for Screening & Mechanistic Investigations to GI Toxicity 16.5.1 Cell viability 16.5.2 Cell migration 16.5.3 Barrier integrity 16.6. Summary, conclusions, and challenges References 17. Preclinical Safety assessment of Drug Candidate-Induced pancreatic toxicity Karrie Brenneman, Shashi Ramaiah, Lauren Gauthier 17.1 Drug-Induced Pancreatic Toxicity 17.1.1 Introduction 17.1.2 Drug-Induced Pancreatic Exocrine Toxicity in Humans – Pancreatitis 17.1.3 Mechanisms of Drug-Induced Pancreatic Toxicity 17.2. Preclinical Evaluation of Pancreatic Toxicity 17.2.1 Introduction 17.2.2 Risk Management and Understanding the Potential for Clinical Translation 17.2.3 Interspecies and Interstrain Differences in Susceptibility to Pancreatic Toxicity 17.3. Preclinical Pancreatic Toxicity Assessment - In Vivo 17.3.1 Routine Assessment 17.3.2 Specialized Techniques 17.4. Pancreatic Biomarkers 17.4.1 Introduction 17.4.2 Exocrine Injury Biomarkers in Humans and Preclinical Species 17.4.3 Endocrine/islet functional biomarkers for humans and preclinical species 17.4.4 A note on biomarkers of vascular injury relevant to the pancreas 17.4.5 Author’s opinion on the strategy for investments to address pancreatic biomarker gaps 17.5. Preclinical Pancreatic Toxicity Assessment – In Vitro 17.5.1 Introduction to Pancreatic Cell Culture 17.5.2 Modeling In Vivo Toxicity In Vitro, Testing Translatability and In Vitro Screening Tools 17.5.3 Case Study 1: Direct Acinar Cell Toxicant 17.5.4 Case Study 2: Primary Microvascular Toxicity with Secondary Endocrine/Exocrine Injury 17.5.5 Emerging Technologies/Gaps: Organotypic Models 17.6. Summary and Conclusions References PART V. ADDRESSING THE FALSE NEGATIVE SPACE- INCREASING PREDICTIVITY 18. Animal models of disease for future toxicity predictions Sherry Morgan and Chandikumar Elangbam 18.1 Introduction 18.2 HEPATIC DISEASE MODELS 18.2.1 Hepatic toxicity – relevance to drug attrition 18.2.2 Hepatic toxicity – Reasons for poor translation from animal to human 18.2.3 Available hepatic models to predict hepatic toxicity or understand molecular mechanisms of toxicity – advantages and limitations 18.3 CARDIOVASCULAR DISEASE MODELS 18.3.1 Cardiac toxicity – relevance to drug attrition 18.3.2 Cardiac toxicity – Reasons for poor translation from animal to human 18.3.3 Available CV models to predict cardiac toxicity or understand molecular mechanisms of toxicity – advantages and limitations 18.4 NERVOUS SYSTEM DISEASE MODELS 18.4.1 Nervous system toxicity – relevance to drug attrition 18.4.2. Nervous system toxicity – Reasons for poor translation from animal to human 18.4.3 Available nervous system models to predict nervous system toxicity or understand molecular mechanisms of toxicity – advantages and limitations 18.5 GASTROINTESTINAL INJURY MODELS 18.5.1 Gastrointestinal (GIT) toxicity – relevance to drug attrition 18.5.2 Gastrointestinal toxicity – Reasons for poor translation from animal to human 18.5.3. Available gastrointestinal animal models to predict gastrointestinal toxicity or understand molecular mechanisms of toxicity – advantages and limitations 18.6 RENAL INJURY MODELS 18.6.1. Renal toxicity – relevance to drug attrition 18.6.2. Renal toxicity – Reasons for poor translation from animal to human 18.6.3. Available Renal models to predict renal toxicity or understand molecular mechanisms of toxicity – advantages and limitations 18.7 RESPIRATORY DISEASE MODELS 18.7.1. Respiratory toxicity – relevance to drug attrition 18.7.2. Respiratory toxicity – Reasons for adequate translation from animal to human 18.7.3. Available hepatic models to predict respiratory toxicity or understand molecular mechanisms of toxicity – advantages and limitations 18.8 Conclusion References 19. The Use of Genetically-Modified Animals in Discovery Toxicology Dolores Diaz and Jonathan Maher 19.1 Introduction 19.2 Use of Genetically Modified Animal Models in Discovery Toxicology 19.3 Use of Genetically Modified Animal Models in Pharmacokinetics and Metabolism 19.3.1 Drug Metabolism 19.3.2 Drug Transporters 19.3.3 Nuclear Receptors 19.3. 4 Humanized Liver Models 19.4. Conclusions References 20. Addressing the False Negative Space- Increasing Predictivity Allison Harrill, Ted Choi 20.1. Introduction 20.2. Pharmacogenetics and Population Variability 20.3. Rodent Populations Enable a Population Based Approaches to Toxicology 20.3.1 Mouse Diversity Panel 20.3.2 Collaborative Cross Mice 20.3.3 Diversity Outbred Mice 20.4. Applications for Pharmaceutical Safety Science 20.4.1 Personalized Medicine – Development of Companion Diagnostics 20.4.2 Biomarkers of Sensitivity 20.4.3 Mode of Action 20.5. Study Design Considerations for Genomic Mapping 20.5.1 Dose Selection 20.5.2 Model Selection 20.5.3 Sample Size 20.5.4 Phenotyping 20.5.5 Genome Wide Association Analysis 20.5.6 Candidate Gene Analysis 20.5.7 Cost Considerations 20.6. Summary References PART VI. STEM CELLS IN TOXICOLOGY 21. Application of pluripotent stem cells in drug-induced liver injury safety assessment Chris S. Pridgeon, Fang Zhang, James A. Heslop, Charlotte M.L. Nugues, Neil R. Kitteringham, B. Kevin Park, Chris E.P. Goldring 21.1 The liver, hepatocytes and drug-induced liver injury 21.2 Current models of DILI 21.2.1 Primary human hepatocytes 21.2.2 Murine models 21.2.3 Cell lines 21.2.4 Stem cell models 21.3 Uses of iPSC HLCs 21.4 Challenges of using IPSCs and new directions for improvement 21.4.1 Complex culture systems 21.4.2 Co-culture 21.4.3 3D culture 21.4.4 Perfusion bioreactors 21.5 Alternate uses of hepatocyte-like cells in toxicity assessment References 22. Human pluripotent stem cell-derived cardiomyocytes Praveen Shukla, Priyanka Garg, Joseph Wu 22.1. Introduction 22.2. Advent of hPSCs: reprogramming and cardiac differentiation 22.2.1 Reprogramming 22.2.2 Cardiac differentiation 22.3. iPSC-based disease modeling and drug testing 22.4. Traditional target-centric drug discovery paradigm 22.5. iPSC-based drug discovery paradigm 22.5.1 Target identification and validation: “clinical trial in a dish” 22.5.2 Safety pharmacology and toxicological testing 22.6. Limitations & challenges 22.7. Conclusion and future perspective References 23 Stem cell-derived renal cells and predictive renal in vitro models Jacqueline Kai, Yue Ning, Peng Huang, Daniel Zink 23.1. Introduction 23.2. Protocols for the differentiation of pluripotent stem cells into cells of the renal lineage 23.2.1. Earlier protocols and the recent race 23.2.2. Protocols designed to mimic embryonic kidney development 23.2.3. Rapid and efficient methods for the generation of proximal tubular-like cells 23.3. Renal in vitro models for drug safety screening 23.3.1. Microfluidic and 3D models and other models that have been tested with lower numbers of compounds 23.3.2. In vitro models that have been tested with higher numbers of compounds and the first predictive renal in vitro model 23.3.3. Stem cell-based predictive models 23.4. Achievements and future directions Acknowledgements References PART VII. CURRENT STATUS OF PRECLINICAL IN VIVO TOXICITY BIOMARKERS 24 Predictive Cardiac Hypertrophy Biomarkers in Non clinical Studies Steven Engle 24.1. Introductory Background: Cardiovascular Toxicity 24.2. Cardiac Hypertrophy 24.3. Biomarkers of Cardiac Hypertrophy 24.4. Case Studies 24.5. Conclusion References 25. Vascular Injury Biomarkers Tanya Zabka and Kaidre Bendjama 25.1. Historical context of drug-induced vascular injury and drug development 25.2. Current state of DIVI biomarkers 25.3. Current status and future of in vitro systems to investigate DIVI 25.4. Incorporation of in vitro and in vivo tools in preclinical drug development 25.5. DIVI Case Study References 26. Novel Translational Biomarkers of Skeletal Muscle Injury Peter Burch and Warren Glaab 26.1. Introduction 26.2. Overview of drug-induced skeletal muscle injury 26.3.1 Skeletal Troponin I (sTnI) 26.3.2 Creatine Kinase M (CKM) 26.3.3 Myosin Light Chain 3 (Myl3) 26.3.4 Fatty Acid Binding Protein 3 26.3.5 Parvalbumin 26.3.6 Myoglobin 26.3.7 MicroRNAs 26.4. Regulatory Endorsement 26.5. Gaps and Future directions 26.6. Conclusions References 27. Translational Mechanistic Biomarkers and Model for Predicting Drug-Induced Liver Injury Daniel Antoine 27.1. Introduction 27.2. Drug-Induced Toxicity and the Liver 27.3. Current Status of Biomarkers for the Assessment of DILI 27.4. Novel Investigational Biomarkers for DILI 27.4.1. Glutamate Dehydrogenase (GLDH) 27.4.2. Acylcarnitines 27.4.3. High Mobility Group Box-1 (HMGB1) 27.4.4. Keratin-18 (K18) 27.4.5. MicroRNA-122 (miR-122) 27.5. In Vitro Models and the Prediction of Human DILI 27.6. Conclusions and Future Perspectives References PART VIII. Kidney Injury Biomarkers 28. Assessing and Predicting Drug-Induced Kidney Injury, Functional Change and Safety in Preclinical Studies in Rats Yafei Chen 28.1. Introduction 28.2. Kidney Functional Biomarkers (Glomerular Filtration and Tubular Reabsorption) 28.2.1. Traditional Functional Biomarkers 28.2.2. Novel Functional Biomarkers 28.3. Novel Kidney Tissue Injury Biomarkers 28.3.1. Urinary N-acetyl-beta-D-glucosaminidase (NAG) 28.3.2. Urinary Glutathione S-transferase alpha (α-GST) 28.3.3. Urinary Renal Papillary Antigen 1 (RPA-1) 28.3.4. Urinary Calbindin D28 28.4. Novel Biomarkers of Kidney Tissue Stress Response 28.4.1. Urinary Kidney Injury Molecule-1 (KIM-1) 28.4.2. Urinary Clusterin 28.4.3. Urinary Neutrophil Gelatinase-associated Lipocalin (NGAL) 28.4.4. Urinary Osteopontin (OPN) 28.4.5. Urinary L-type Fatty Acid Binding Protein (L-FABP) 28.4.6. Urinary Interleukin 18 (IL-18) 28.5. Application of an Integrated Rat Platform (Automated Blood Sampling and Telemetry; ABST) for Kidney Function and Injury Assessment References 29. Canine Kidney Safety Protein Biomarkers Manisha Sonee 29.1. Introduction 29.2. Novel Canine Renal Protein Biomarkers 29.3. Evaluations of Novel Canine Renal Protein Biomarker Performance 29.4. Conclusion References 30. Traditional Kidney Safety Protein Biomarkers and Next-Generation Drug-Induced Kidney Injury Biomarkers in Nonhuman Primates Jean-Charles Gautier and Xiaobing Zhou 30.1. Introduction 30.2. Evaluations of Novel Nonhuman Primate Renal Protein Biomarker Performance 30.3. New Horizons: Urinary MicroRNAs and Nephrotoxicity in NHPs References 31. Rat Kidney MicroRNA Atlas Aaron Smith 31.1 Introduction 31.2 Key findings References 32. MicroRNAs as Next-Generation Kidney Tubular Injury Biomarkers in Rats Heidrun Ellinger-Ziegelbauer and Rounak Nassirpour 32.1. Introduction 32. 2. Rat Tubular MicroRNAs 32.3. Conclusions References 33. MicroRNAs as Novel Glomerular Injury Biomarkers in Rats Rachel Church 33.1. Introduction 33.2. Rat Glomerular MicroRNAs References 34. Integrating Novel Imaging Technologies to Investigate Drug-Induced Kidney Toxicity Bettina Wilm and Neal Burton 34.1. Introduction 34.2. Overview 34.3. Summary References 35. In vitro-to-In Vivo Relationships with Respect to Kidney Safety Biomarkers Paul Jennings 35.1 Renal cell lines as tools for toxicological investigations 35.2. Mechanistic approaches and in vitro to in vivo translation 35.3. Closing Remarks References 36. Case Study: Fully Automated Image Analysis of Podocyte Injury Biomarker Expression in Rats Jing Ying Ma 36.1. Introduction 36.2. Material and Methods 36.3. Results 36.4. Conclusions References 37. Case Study: Novel Renal Biomarkers translation to humans Deborah Burt 37.1. Introduction 37.2. Implementation of Translational Renal Biomarkers in Drug Development 37.3. Conclusion References 38. Case Study: MicroRNAs as Novel Kidney Injury Biomarkers in Canines Craig Fisher, Erik Koenig, and Patrick Kirby 38.1 Introduction 38.2. Material and Methods 38.3. Results 38.4. Conclusions References 39. Novel Testicular Injury Biomarkers Hungyun Lin 39.1. Introduction 39.2. The Testis 39.3. Potential Biomarkers for Testicular Toxicity 39.3.1. Inhibin B 39.3.2. Androgen-Binding Protein 39.3.3. SP22 39.3.4. Emerging Novel Approaches 39.4. Conclusions References PART IX. Best Practices in Biomarker Evaluations 40. Best Practices in Preclinical Biomarker Sample Collections Jacqueline Tarrant 40.1. Considerations for reducing preanalytical variability in biomarker testing 40.2. Biological sample matrix variables 40.3. Collection variables 40.4. Sample processing and storage variables References 41. Best Practices in Novel Biomarker Assay Fit-for-Purpose Testing Karen Lynch 41.1. Introduction 41.2. Why Use a Fit-for-Purpose Assay? 41.3. Overview of Fit-for-Purpose Assay Method Validations 41.4. Assay Method Suitability in Preclinical Studies 41.5. Best Practices for Analytical Methods Validation 41.5.1. Assay Precision 41.5.2. Accuracy/Recovery 41.5.3. Precision and Accuracy of the Calibration Curve 41.5.4. Lower Limit of Quantification 41.5.5. Upper Limit of Quantification 41.5.6. Limit of Detection 41.5.7. Precision Assessment for Biological Samples 41.5.8. Dilutional Linearity and Parallelism 41.5.9. Quality Control 41.6. Species- and Gender-Specific Reference Ranges 41.7. Analyte Stability 41.8. Additional Method Performance Evaluations References 42. Best Practices in Evaluating Novel Biomarker Fit-for-Purpose and Translatability Amanda Baker 42.1. Introduction 42.2. Protocol Development 42.3. Assembling an Operations Team 42.4. Translatable Biomarker Use 42.5. Assay Selection 42.6. Biological Matrix Selection 42.7. Documentation of Patient Factors 42.8. Human Sample Collection Procedures 42.8.1. Biomarkers in Human Tissue Biopsy and Biofluid Samples 42.9. Choice of Collection Device 42.9.1. Tissue Collection Device 42.9.2. Plasma Collection Device 42.9.3. Serum Collection Device 42.9.4. Urine Collection Device 42.10. Schedule of Collections 42.11. Human Sample Quality Assurance 42.11.1. Monitoring Compliance to Sample Collection Procedures 42.11.2. Documenting Time and Temperature from Sample Collection to Processing 42.11.3. Optimal Handling and Preservation Methods 42.11.4. Choice of Sample Storage Tubes 42.11.5. Choice of Sample Labeling 42.11.6. Optimal Sample Storage Conditions 42.12. Logistics Plan 42.13. Database Considerations 42.14. Conclusive Remarks References 43. Best Practices in Translational Biomarker Data Analysis Robin Mogg and Daniel Holder 43.1. Introduction 43.2. Statistical Considerations for Pre-Clinical Studies of Safety Biomarkers 43.3. Statistical Considerations for Exploratory Clinical Studies of Translational Safety Biomarkers 43.4. Statistical Considerations for Confirmatory Clinical Studies of Translational Safety Biomarkers 43.5. Summary References 44 Translatable Biomarkers in Drug Development John-Michael Sauer, Elizabeth G Walker, and Amy C Porter 44.1. Safety Biomarkers 44.2. Qualification of Safety Biomarkers 44.3. Letter of Support for Safety Biomarkers 44.4. Critical Path Institute’s Predictive Safety Testing Consortium 44.5. Predictive Safety Testing Consortium and its Key Collaborations 44.6. Advancing the Qualification Process and Defining Evidentiary Standards References PART X CONCLUSIONS 45 Toxicogenomics in Drug Discovery Toxicology Brandon Jeffy, Richard Brennan, Joseph Milano 45.1 A Brief History of Toxicogenomics 45.2 Tools and strategies for analyzing Toxicogenomics Data 45.3 Drug Discovery Toxicology Case Studies References 46 Issue Investigation and Practices in Discovery Toxicology Dolores Diaz, Dylan Hartley Ray Kemper 46.1 Introduction 46.2 Overview of Issue Investigation in the Discovery Space 46.3 Strategies to Address Toxicities the Discovery Space 46.4 Cross-functional collaborative model 46.5 Case-Studies of Issue Resolution in the Discovery Space 46.6 Data inclusion in Regulatory Filings References Concluding Remarks Yvonne Will, Eric McDuffie, Andrew Olaharski and Brandon Jeffy Index |
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