Predictive Toxicology E-Book

• Herausgeber: Wiley-VCH
• Kategorie: Fachliteratur
• Serie: Methods and Principles in Medicinal Chemistry
• Sprache: Englisch

Seitenzahl: 897

Veröffentlichungsjahr: 2014

Beschreibung

Tailored to the needs of scientists developing drugs, chemicals, cosmetics and other products this one-stop reference for medicinal chemists covers all the latest developments in the field of predictive toxicology and its applications in safety assessment.

With a keen emphasis on novel approaches, the topics have been tackled by selected expert scientists, who are familiar with the theoretical scientific background as well as with the practical application of current methods. Emerging technologies in toxicity assessment are introduced and evaluated in terms of their predictive power, with separate sections on computer predictions and simulation methods, novel in vitro systems including those employing stem cells, toxicogenomics and novel biomarkers. In each case, the most promising methods are discussed and compared to classical in vitro and in vivo toxicology assays. Finally, an outlook section discusses such forward-looking topics as immunotoxicology assessment and novel regulatory requirements.

With its wealth of methodological knowledge and its critical evaluation of modern approaches, this is a valuable guide for toxicologists working in pharmaceutical development, as well as in safety assessment and the regulation of drugs and chemicals.

Leseprobe

CONTENTS

Cover

Methods and Principles in Medicinal Chemistry

Title Page

Copyright

List of Contributors

Preface

A Personal Foreword

Chapter 1: Introduction to Predictive Toxicology Tools and Methods

1.1 Computational Tools and Bioinformatics

1.2 Omics Technologies

1.3 Data Interpretation and Knowledge Management

1.4 Biomarker Development

1.5 Advanced In Vitro Systems and Stem Cell Research

1.6 Immunogenicity

1.7 Integration and Validation

1.8 Research Initiative/Collaborations

1.9 Concluding Remarks

References

Chapter 2: In Silico Toxicology – Current Approaches and Future Perspectives to Predict Toxic Effects with Computational Tools

2.1 Introduction

2.2 Prediction of Hazard

2.3 Prediction of Risk

2.4 Thoughts on Validation

2.5 Conclusions and Outlook

References

Chapter 3: In Silico Approaches: Data Management – Bioinformatics

3.1 Introduction

3.2 Experimental Setup and Statistical Power

3.3 Properties of Different Omics Data

3.4 Statistical Methods

3.5 Prediction and Classification

3.6 Combining Different Omics Data and Biological Interpretations

3.7 Data Management

References

Chapter 4: Role of Modeling and Simulation in Toxicology Prediction

4.1 Introduction

4.2 The Need to Bring PK and PD in Predictive Models Together

4.3 Methodological Aspects and Concepts

4.4 Application During Lead Optimization

4.5 Application During Clinical Candidate Selection

4.6 Entry-into-Human Preparation and Translational PK/PD Modeling

4.7 Justification of Starting Dose, Calculation of Safety Margins, and Support of Phase I Clinical Trial Design

4.8 Outlook and Conclusions

References

Chapter 5: Genomic Applications for Assessing Toxicities of Liver and Kidney Injury

5.1 Introduction

5.2 Toxicogenomic Approaches

5.3 Specific Applications of Toxicogenomics

5.4 Toxicogenomic Applications for the Better Understanding of Hepatotoxicity

5.5 Toxicogenomic Profiling of Nephrotoxicity

5.6 Limitations of Toxicogenomics

5.7 Conclusions

References

Chapter 6: Use of Toxicogenomics for Mechanistic Characterization of Hepatocarcinogens in Shorter Term Studies

6.1 Introduction

6.2 Toxicogenomics

6.3 Conclusions and Outlook

References

Chapter 7: Discovery and Application of Novel Biomarkers

7.1 Introduction

7.2 Novel RNA Biomarkers

7.3 DNA as a Biomarker

7.4 Novel Biomarkers: Beyond Nucleotide-Based Discovery

7.5 Summary and Outlook

References

Chapter 8: Predictive Toxicology: Genetics, Genomics, Epigenetics, and Next-Generation Sequencing in Toxicology

8.1 Introduction

8.2 Technological Advances

8.3 Applications in Toxicology

8.4 Summary and Outlook

References

Chapter 9: Biomarkers as Tools for Predictive Safety Assessment: Novel Markers of Drug-Induced Kidney Injury

9.1 Need and Search for Novel Biomarkers of Kidney Injury

9.2 Urinary Biomarkers of Drug-Induced Kidney Injury

9.3 Genomic Biomarkers

9.4 Qualification and Use of Novel Kidney Injury Biomarkers in Preclinical Safety Assessment

9.5 Summary and Perspectives

References

Chapter 10: The Use of Renal Cell Culture for Nephrotoxicity Investigations

10.1 Introduction

10.2 In Vitro Renal Models

10.3 Stem Cells

10.4 Optimal Cell Culture Conditions

10.5 In Vitro Nephrotoxicity Assessment

10.6 Outlook

References

Chapter 11: The Zebrafish Model in Toxicology

11.1 The Need for a Physiologically Relevant Organ Model in Drug Toxicity Testing

11.2 Extensive Knowledge about Genetics, Development, and Physiology of D. rerio

11.3 Studies of Specific Organ Toxicities in Zebrafish Embryos and Larvae

References

Chapter 12: Predictive Method Development: Challenges for Cosmetics and Genotoxicity as a Case Study1)

12.1 Introduction

12.2 The Toolbox of Predictive Methods

12.3 Genotoxicity as a Case Study2)

12.4 The Way Forward: Combining In Silico and In Vitro Tools

Abbreviations

References

Chapter 13: Using Pluripotent Stem Cells and Their Progeny as an In Vitro Model to Assess (Developmental) Neurotoxicity

13.1 Introduction

13.2 Neurodevelopment In Vivo

13.3 Main Principle of In Vitro Test Systems to Model DNT

13.4 Requirements of an In Vitro Test System for DNT/NT

13.5 Modeling of Disease and Toxicant-Induced Damage

13.6 Using Stem Cells to Assess (Developmental) Neurotoxicity

13.7 Limitations

Acknowledgments

References

Chapter 14: Stem Cell-Based Methods for Identifying Developmental Toxicity Potential

14.1 Introduction

14.2 Developmental Toxicity Screening: Past and Present

14.3 Pluripotent Stem Cells

14.4 Metabolomics

14.5 Stem Cell-Based In Vitro Screens for Developmental Toxicity Testing

14.6 Summary

References

Chapter 15: Immunogenicity of Protein Therapeutics: Risk Assessment and Risk Mitigation

15.1 Introduction

15.2 The Central Role of CD4+ T Cells

15.3 Generation of T-Cell Epitopes

15.4 Tolerance to Therapeutic Drugs

15.5 Tool Set for Immunogenicity Risk Assessment

15.6 Immunogenicity Risk Mitigation

15.7 The Integrated Strategy of Risk Minimization

15.8 Summary

References

Chapter 16: Regulatory Aspects

16.1 The History of Medicines Regulations in Brief

16.2 Impact on Drug Success of the Current ICH Nonclinical Testing Paradigm

16.3 Actions Taken for Increasing the Drug Development Success

16.4 Innovative Drugs: Impact on Nonclinical Development Strategies

16.5 Envisaging a Paradigm Change

16.6 Regulatory Actions Needed to Shift the Animal-Based Paradigm

References

Index

End User License Agreement

List of Tables

Table 2.1

Table 6.1

Table 6.2

Table 7.1

Table 7.2

Table 8.1

Table 11.1

Table 12.1

Table 12.2

Table 13.1

Table 14.1

Table 14.2

Table 14.3

Table 15.1

Table 16.1

Table 16.2

Table 16.3

Table 16.4

Table 16.5

List of Illustrations

Figure 2.1

Figure 2.2

Figure 2.3

Figure 2.4

Figure 2.5

Figure 2.6

Figure 4.1

Figure 4.2

Figure 4.3

Figure 4.4

Figure 5.1

Figure 5.2

Figure 6.1

Figure 6.2

Figure 7.1

Figure 7.2

Figure 8.1

Figure 8.2

Figure 9.1

Figure 10.1

Figure 11.1

Figure 11.2

Figure 11.3

Figure 11.4

Figure 11.5

Figure 12.1

Figure 12.2

Figure 12.3

Figure 13.1

Figure 13.2

Figure 13.3

Figure 14.1

Figure 14.2

Figure 14.3

Figure 15.1

Figure 15.2

Figure 15.3

Guide

Cover

Table of Contents

Begin Reading

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Methods and Principles in Medicinal Chemistry

Edited by R. Mannhold, H. Kubinyi, G. Folkers

Editorial Board

H. Buschmann, H. Timmerman, H. van de Waterbeemd, T. Wieland

Previous Volumes of this Series:

Kirchmair, Johannes (Ed.)

Drug Metabolism Prediction

2014

ISBN: 978-3-527-33566-4

Vol. 63

Vela, José Miguel / Maldonado, Rafael / Hamon, Michel (Eds.)

In vivo Models for Drug Discovery

2014

ISBN: 978-3-527-33328-8

Vol. 62

Liras, Spiros / Bell, Andrew S. (Eds.)

Phosphodiesterases and Their Inhibitors

2014

ISBN: 978-3-527-33219-9

Vol. 61

Hanessian, Stephen (Ed.)

Natural Products in Medicinal Chemistry

2014

ISBN: 978-3-527-33218-2

Vol. 60

Lackey, Karen / Roth, Bruce (Eds.)

Medicinal Chemistry Approaches to Personalized Medicine

2013

ISBN: 978-3-527-33394-3

Vol. 59

Brown, Nathan (Ed.)

Scaffold Hopping in Medicinal Chemistry

2013

ISBN: 978-3-527-33364-6

Vol. 58

Hoffmann, Rémy / Gohier, Arnaud / Pospisil, Pavel (Eds.)

Data Mining in Drug Discovery

2013

ISBN: 978-3-527-32984-7

Vol. 57

Dömling, Alexander (Ed.)

Protein-Protein Interactions in Drug Discovery

2013

ISBN: 978-3-527-33107-9

Vol. 56

Kalgutkar, Amit S. / Dalvie, Deepak / Obach, R. Scott / Smith, Dennis A.

Reactive Drug Metabolites

2012

ISBN: 978-3-527-33085-0

Vol. 55

Brown, Nathan (Ed.)

Bioisosteres in Medicinal Chemistry

2012

ISBN: 978-3-527-33015-7

Vol. 54

Predictive Toxicology

From Vision to Reality

Edited by

Friedlieb Pfannkuch

Laura Suter-Dick

All books published by Wiley-VCH are carefully produced. Nevertheless, authors, editors, and publisher do not warrant the information contained in these books, including this book, to be free of errors. Readers are advised to keep in mind that statements, data, illustrations, procedural details or other items may inadvertently be inaccurate.

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© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Boschstr. 12, 69469 Weinheim, Germany

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List of Contributors

Arnd Brandenburg

Genedata AG

Business Unit – Expressionist

Margarethenstrasse 38

4053 Basel

Switzerland

Robert E. Burrier

Stemina Biomarker Discovery, Inc.

504 South Rosa Road

Madison, WI 53719

USA

Antonello Caruso

Roche Pharma Research and Early Development (pRED)

Modeling & Simulation, Pharmaceutical Sciences

Roche Innovation Center Basel

F. Hoffmann-La Roche Ltd

Grenzacherstrasse 124

4070 Basel

Switzerland

Elizabeth L.R. Donley

Stemina Biomarker Discovery, Inc.

504 South Rosa Road

Madison, WI 53719

USA

Laura A. Egnash

Stemina Biomarker Discovery, Inc.

Client Services and Operations

504 South Rosa Road

Madison, WI 53719

USA

Heidrun Ellinger-Ziegelbauer

Bayer Pharma AG

Investigational Toxicology

Aprather Weg 18a

42096 Wuppertal

Germany

Brigitte Faquet

L'Oréal Research & Innovation

Predictive Model and Method Development Department

1 Avenue Eugène Schueller

93601 Aulnay-sous-Bois

France

Nicole Flamand

L'Oréal Research & Innovation

Predictive Model and Method Development Department

1 Avenue Eugène Schueller

93601 Aulnay-sous-Bois

France

Timothy W. Gant

Public Health England

Centre for Radiation, Chemical and Environmental Hazards

Harwell Science and Innovation Campus

Didcot

Oxfordshire OX11 0RQ

UK

Hans Gmuender

Genedata AG

Business Unit – Expressionist

Margarethenstrasse 38

4053 Basel

Switzerland

Hans Peter Grimm

Roche Pharma Research and Early Development (pRED)

Modeling & Simulation, Pharmaceutical Sciences

Roche Innovation Center Basel

F. Hoffmann-La Roche Ltd

Grenzacherstrasse 124

4070 Basel

Switzerland

Tobias Heckel

F. Hoffmann-La Roche Ltd

Pharma Early Research and Development (pRED) – Innovation Center Basel

Pharmaceutical Sciences (PS)

Grenzacherstrasse 124

4070 Basel

Switzerland

Philip Hewitt

Merck KGaA

Non-Clinical Safety

Frankfurterstrasse 250

D-64283 Darmstadt

Germany

Lisa Hoelting

University of Konstanz

Department of Biology, Research School Chemical Biology

Universitätsstraße 10

78457 Konstanz

Germany

Paul Jennings

Innsbruck Medical University

Department of Physiology and Medical Physics

Division of Physiology

Fritz-Pregl-Straße 3

6020 Innsbruck

Austria

Esther Johann

Merck KGaA

Non-Clinical Safety

Frankfurterstrasse 250

D-64283 Darmstadt

Germany

Harald Kropshofer

F. Hoffmann-La Roche Ltd

Pharmaceutical Division

Grenzacherstrasse 124

4070 Basel

Switzerland

Doris Lagache

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Thierry Lavé

Roche Pharma Research and Early Development (pRED)

Project leaders/Modeling & Simulation, Pharmaceutical Sciences

Roche Innovation Center Basel

F. Hoffmann-La Roche Ltd

Grenzacherstrasse 124

4070 Basel

Switzerland

Marcel Leist

University of Konstanz

Department of Biology

Universitätsstraße 10

78457 Konstanz

Germany

Martin O. Leonard

Public Health England

Centre for Radiation, Chemical and Environmental Hazards

Harwell Campus

Harwell Oxford Science Park

Chilton, Didcot Oxfordshire OX11 0RQ

UK

Angela Mally

University of Würzburg

Department of Toxicology

Versbacher Strasse 9

97078 Würzburg

Germany

Emma L. Marczylo

Public Health England

Centre for Radiation, Chemical and Environmental Hazards

Harwell Campus

Harwell Oxford Science Park

Chilton, Didcot Oxfordshire OX11 0RQ

UK

Astrid Mayoux

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Christophe Meille

Roche Pharma Research and Early Development (pRED)

Modeling & Simulation, Pharmaceutical Sciences

Roche Innovation Center Basel

F. Hoffmann-La Roche Ltd

Grenzacherstrasse 124

4070 Basel

Switzerland

Natalie Mesens

Janssen Pharmaceutical Companies of Johnson & Johnson

Discovery Support and Investigative Toxicology

Preclinical Development & Safety

Turnhoutseweg 30

2340 Beerse

Belgium

Lauren Nakab

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Fabrice Nesslany

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Gladys Ouédraogo

L'Oréal Research & Innovation

Predictive Model and Method Development Department

1 Avenue Eugène Schueller

93601 Aulnay-sous-Bois

France

Jessica A. Palmer

Stemina Biomarker Discovery, Inc.

Cell Biology Department

504 South Rosa Road

Madison, WI 53719

USA

Neil Parrott

Roche Pharma Research and Early Development (pRED)

Modeling & Simulation, Pharmaceutical Sciences

Roche Innovation Center Basel

F. Hoffmann-La Roche Ltd

Grenzacherstrasse 124

4070 Basel

Switzerland

Friedlieb Pfannkuch

Toxconsult

Steingrubenweg 160

4125 Riehen

Switzerland

Beatriz Silva Lima

Universidaded de Lisboa

Faculdade de Farmácia

iMED.ULisboa

Avenida Professor Gama Pinto

1649-003 Lisbon

Portugal

Sophie Simar

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Thomas Steger-Hartmann

Bayer HealthCare

Investigational Toxicology

Müllerstrasse 178

13353 Berlin

Germany

Luc Stoppini

University of Applied Sciences Western Switzerland

Tissue Engineering Laboratory

Haute école du paysage, d'ingénierie et d'architecture de Genève – hepia

Rue de la Prairie 4

1202 Geneva

Switzerland

Laura Suter-Dick

University of Applied Sciences North-Western Switzerland

High School of Life Sciences – Molecular Toxicology

Gründenstrasse 40

4132 Muttenz

Switzerland

Smail Talahari

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Eric Vercauteren

Institut Pasteur de Lille

Laboratoire de toxicologie

1 rue du Professeur Calmette

59019 Lille Cedex

France

Antje-Christine Walz

Roche Pharma Research and Early Development (pRED)

Modeling & Simulation, Pharmaceutical Sciences

Roche Innovation Center Basel

F. Hoffmann-La Roche Ltd

Grenzacherstrasse 124

4070 Basel

Switzerland

Anja Wilmes

Innsbruck Medical University

Department of Physiology and Medical Physics

Division of Physiology

Fritz-Pregl-Straße 3

6020 Innsbruck

Austria

Timo Wittenberger

Genedata AG

Business Unit – Expressionist

Margarethenstrasse 38

4053 Basel

Switzerland

Preface

With great pleasure we announce volume 64 of our book series “Methods and Principles in Medicinal Chemistry.” The volume editors Friedlieb Pfannkuch and Laura Suter-Dick present an excellent book dedicated to predictive toxicology, a highly important research area with prime impact on the quality of compounds from drug discovery and development projects. Therapeutic use of any new compound is in demand of a thorough identification and profiling of its safety. Protection of human safety is a primary objective of toxicology research and risk assessment.

Toxicology is the study of the adverse effects of drugs and other chemicals on living systems and the means to prevent or at least minimize such effects. Toxicology is a multifaceted field, overlapping with biochemistry, histology, pharmacology, pathology, and several others. Subdisciplines of toxicology include clinical, regulatory, forensic, and occupational toxicology as well as risk assessment.

Poor pharmacokinetics, side effects, and compound toxicity are frequent causes of late-stage failures in drug development. A safe in silico identification of adverse effects triggered by drugs and chemicals would be highly desirable as it not only bears economic potential but also spawns a variety of ecological benefits.

The drug development industry has undertaken significant efforts to identify toxic events at the earliest opportunity during the development process, moving from a predominantly observational science at the level of disease-specific models to a more predictive model focused on target-specific mechanism-based biological observations. The growth in such Early Safety Assessment initiatives has driven the need for more reliable, cost-effective high-throughput in vitro toxicity assays capable of predicting toxic liabilities prior to investment in more costly preclinical and clinical trials.

In silico toxicology studies can help to focus in vitro and in vivo experiments to make the latter highly efficient. In some cases, in silico studies might even replace particularly expensive, lengthy, uninformative, or offensive in vitro or in vivo experiments. Moreover, by virtue of being computer-based and, hence, inexpensively replicable, in silico toxicology can vastly expand the applicability and availability of toxicological analysis [1–6].

The ultimate goal for predictive toxicology would be the ability to go from visualizing the chemical compound structure to predicting its safety profile. The major challenge is to translate the tremendous scientific progress in this field into practical use or general acceptance. Scientists are using biological data very effectively – whether it is gene expression data or even data from proteomic or other profiling techniques – to gain a sense of whether a drug is having off-target effects or otherwise adversely impacting the system. As technologies become more mechanism-based and as more data accrue, it should enable predictions with better accuracy and decrease occurrences of false negatives and false positives.

Chapters of this comprehensive volume consider all topic areas relevant in the field of predictive toxicology, such as in silico approaches, data management, and bioinformatics (Chapters 2–4), omics technologies and biomarker development (Chapters 5–10), advanced in vitro systems (Chapter 11), models for cosmetic products (Chapter 12), use of stem cells with focus on neurotoxicology and teratology (Chapters 13 and 14), immunogenicity of protein therapeutics (Chapter 15), and finally aspects on acceptance by Drug Regulatory Authorities (Chapter 16).

The series editors are grateful to Friedlieb Pfannkuch and Laura Suter-Dick for organizing this volume and collaborating with excellent authors. Last but not least, we thank Frank Weinreich and Heike Nöthe from Wiley-VCH for their valuable contributions to this project and to the entire book series.

DüsseldorfWeisenheim am SandZürichOctober 2014

Raimund Mannhold

Hugo Kubinyi

Gerd Folkers

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Davis, M., Boekelheide, K., Boverhof, D.R., Eichenbaum, G., Hartung, T., Holsapple, M.P., Jones, T.W., Richard, A.M., and Watkins, P.B. (2013) The new revolution in toxicology: the good, the bad, and the ugly.

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Sturla, S.J., Boobis, A.R., FitzGerald, R.E., Hoeng, J., Kavlock, R.J., Schirmer, K., Whelan, M., Wilks, M.F., and Peitsch, M.C. (2014) Systems toxicology: from basic research to risk assessment.

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A Personal Foreword

Knowingly or unknowingly, toxicology affects most parts of our society. There is clear public interest in only accepting products with a well-characterized safety profile in the market. There is also a requirement for several industries such as pharmaceutical, chemical, and cosmetic industries to perform a battery of in vitro and animal studies in order to avoid harm to the general public, volunteers in clinical trials, patients, workers in production plants, and the environment.

Toxicology is a multidisciplinary science for evaluation of risk/benefit ratio and takes its methods from other sciences such as chemistry and pharmacological chemistry, pharmacology, pathology, biochemistry, clinical medicine, and forensic medicine.

The spectrum of toxicity assays comprises computational (in silico) methods as well as the testing of chemicals with in vitro methods and in selected laboratory animal species to describe the dose–effect relationship over a broad range of doses in order to detect secondary (harmful/unwanted) pharmacological effects and adverse (toxic) effects.

The final goal must be the extrapolation and prediction of adverse effects to humans. The challenge is to identify a safe dose in humans and setting exposure limits (ceiling), if required. In this context, potential target organs of toxicity and reversibility of potential side effects should be identified and meaningful parameters for (clinical) monitoring should be chosen. Finally, the discipline should contribute to the elucidation of mechanisms of toxic/adverse effects.

Industry's activities are driven by national, regional, and global regulatory requirements [1–4], strategic and commercial aspects, and scientific and technological state of the art. These aspects are the main driving forces for advances in toxicology. In addition, there is an increasing public pressure to refine, reduce, and replace animal testing (“3Rs” [5]) for ethical reasons.

The scientific and regulatory environment is changing rapidly. The introduction of new technologies (e.g., for testing of biologics or new approaches to improve carcinogenicity testing) and the trend toward perfectionism (e.g., including as many investigation parameters as possible) have caused the extension of the existing study programs and a dramatic increase in the investment of human and financial resources.

However, we have relied for decades on the use of animal studies (in vivo toxicology) with generally unsatisfactory predictive performance (acknowledged by many and summarized by Olson et al. [6]). In particular for the pharmaceutical industry, several products have caused serious adverse reactions despite having been through a battery of mandatory toxicity tests. The consequences of this suboptimal predictive performance are often disastrous for the patients and for the pharmaceutical industry.

Thus, for the past few decades, predictive approaches other than studies in animals have been considered and employed with varying degrees of success. Among the more commonly used approaches are in silico tools, in vitro assays with primary cells and cell lines combined with specific endpoints, omics technologies, and the use of stem cell-derived cells.

The diversity of technologies and scientific knowledge that flows into the advanced approaches used currently to predict toxicity require a new type of biologist, different from the one traditionally recruited for performing toxicology testing. They must have an in-depth knowledge of the applied technological advancements, biological networks, and adverse outcome pathways, and, most importantly, a thorough understanding of the contextual relevance of the biological findings in relation to toxicology and pathology, and ultimately to the effect on the human population.

Any future activity, however, must focus on the improvement of the predictivity of toxicology/safety testing, since identification of potential safety issues upstream in the drug discovery process is a major bottleneck in drug development. New technologies may play a central role in this respect.

The final goal must be to combine the results from new technologies and classical toxicology methodology in a scientifically sound way in order to gain acceptance by Regulatory Authorities and we strongly hope that this book is contributing to this challenge.

The aim of this book is to provide a comprehensive overview of the latest scientific developments in the field of “predictive” toxicology and their applications in safety assessment. The topics have been tackled by selected expert scientists, who are familiar with the theoretical scientific background as well as with the practical application of methods and technologies. To ensure scientific excellence related with practical application of the contributions, we have invited scientists active both in the academic and in the industrial toxicology research.

Finally, we want to acknowledge the pleasant collaboration with Dr. Heike Noethe and Dr. Frank Weinreich from Wiley-VCH for their constant support during all steps of editing this book.

BaselOctober 2014

Friedlieb Pfannkuch and Laura Suter-Dick

References

1.

European Community (EC) (2014) The Rules Governing Medicinal Products in the European Community. Available at

http://ec.europa.eu/health/documents/eudralex/index_en.htm

(last assessed February 2014).

2.

FDA (2013) Guidelines for the Format and Content of the Nonclinical Pharmacology/Toxicology Section of an Application. US Department of Health and Human Services, Public Health Service, Food and Drug Administration, Washington, DC. Available at

http://www.fda.gov/Drugs/DevelopmentApprovalProcess/HowDrugsareDevelopedandApproved/ApprovalApplications/NewDrugApplicationNDA/

(last assessed February 2014).

3.

Japanese Ministry of Health and Welfare (1993) Guidelines for Toxicity Studies of Drugs. Notification No. 88 of the Pharmaceutical Affairs Bureau of the Ministry of Health and Welfare. Available at

http://www.jpma.or.jp/english/parj/pdf/2012.pdf

(last assessed February 2014).

4.

European Union (2014) ICH Guidelines. Available at

www.ich.org

(last assessed February 2014).

5.

Russell, W.M.S. and Burch, R.L. (1959) BT The Principles of Humane Experimental Technique, Methuen & Co. Ltd, London (reissued 1992). Available at

http://altweb.jhsph.edu/pubs/books/humane_exp/het-toc

(last assessed February 2014).

6.

Olson, H., Betton, G., Robinson, D., Thomas, K., Monro, A., Kolaja, G., Lilly, P., Sanders, J., Sipes, G., Bracken, W., Dorato, M., Van Deun, K., Smith, P., Berger, B., and Heller, A. (2000) Concordance of the toxicity of pharmaceuticals in humans and in animals.

Regul. Toxicol. Pharmacol.

,

32

(1), 56–67.

1Introduction to Predictive Toxicology Tools and Methods

Laura Suter-Dick and Friedlieb Pfannkuch

1.1 Computational Tools and Bioinformatics

1.1.1 In Silico Prediction Tools

Computational tools are used in many life sciences research areas, including toxicity prediction. They take advantage of complex mathematical models to predict the effects caused by a given compound on an organism. Due to the complexity of the possible interactions between a treatment and a patient and the diversity of possible outcomes, models are applied to well-defined and specific fields, such as DNA damaging potential, estimation of the necessary dose to elicit an effect in a patient, or identification of relevant gene expression changes.

In silico tools make use of information regarding chemical structures and the immense data legacy that allows inferring interactions between chemical structures, physicochemical properties, and biological processes. These methods are farthest away from traditional animal studies, since they rely on existing databases rather than on generating experimental animal data.

Due to the complexity of this task, there are a fairly small number of endpoints that can be predicted with commonly employed tools such as DEREK, VITIC, and M-Case with acceptable accuracy. In order to improve the current models and to expand to additional prediction algorithms, further validation and extension of the underlying databases is ongoing.