Drug Discovery Toxicology: From Target Assessment to Translational Biomarkers

Developing novel pharmaceuticals requires nonclinical safety studies on candidate drugs to assess general toxicology (through in vivo experiments), safety pharmacology (effects on major organ systems), and genetic toxicity tests. These data provide risk assessment data that supports progression of candidate drugs from discovery phase through clinical development, to regulatory submission and registration. Traditionally, however, less emphasis was placed on the evaluation of safety issues for projects while still in the drug design phase.

In response to this costly attrition, many pharmaceutical companies invested in drug discovery toxicology or drug discovery safety to identify hazards and take steps to design out or significantly reduce undesirable safety liabilities earlier; with the ultimate aim of enhancing the probability of success in non–clinical and clinical drug development. Because of this, there is a strong need for personnel involved with toxicology and pharmacology studies need to understand the varied tools and approaches to perform early drug discovery safety analysis.

Drug Discovery Toxicology: From Target Assessment to Translational Biomarkers serves as a valuable tool for those discovery scientists. The authors, writing from firsthand industry experience, give readers insight into the strategy and execution of predictive toxicology practices, including what experiments are possible and useful. In addition, they offer a view into the future, indicating key areas to watch for new predictive methods. Broken into different sections, the book deals with the key topics Safety Lead Optimization Strategies, In Vitro–In Vivo Pharmacokinetics Translation, Predicting Organ Toxicity In Vitro, False Negative Space, ––Omics in Predictive Toxicology, Translational Biomarkers, and Signal Investigation Rationale and Practices.

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 throughout the pre–clinical drug discovery development process.

PREFACE
Eric Blomme

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 ( –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

Yvonne Will, PhD, is a Senior Director and the Head of Science and Technology Strategy, Drug Safety Research and Development at Pfizer, Connecticut, USA. She co–edited the book Drug–Induced Mitochondrial Dysfunction, published by Wiley in 2008.

J. Eric McDuffie, PhD, is the Director of the Discovery / Investigative Toxicology and Laboratory Animal Medicine groups at Janssen Research & Development, California, USA.

Andrew J. Olaharski, PhD, is an Associate Director of Toxicology at Agios Pharmaceuticals, Massachusetts, USA.

Brandon D. Jeffy, PhD, is a Senior Principal Scientist in the Exploratory Toxicology division of Nonclinical Development at Celgene Pharmaceuticals, California, USA.