Table of Contents

Cover

Previous Volumes of this Series

Title Page

List of Contributors

Preface

Reference

A Personal Foreword

References

Chapter 1: Introduction

1.1 Animal Models in Biomedical Research
1.2 Animals in the Drug Development Process: Historic Background
1.3 Problems with Translation of Animal Data to the Clinic
1.4 Animal Studies in Anti-cancer Drug Development
1.5 Toward Relevant Animal Data
1.6 Aim of the Book
References

Chapter 2: Ethical Aspects of the Use of Animals in Translational Research

2.1 Introduction
2.2 Today's R&D Environment
2.3 “Do No Harm”: the Essential Dilemma of Animal Research
2.4 Man and Animals in Philosophy: an Overview of Key Concepts
2.5 Conclusions: Solving the Dilemma
References

Chapter 3: Study Design

3.1 Introduction
3.2 Design Principles
3.3 Experimental Design
3.4 Conclusion
References

Chapter 4: Improving External Validity of Experimental Animal Data

4.1 Introduction
4.2 Variation in the Laboratory
4.3 The Fallacies
4.4 Future Perspectives: an Experimental Strategy Integrating Adaptive Plasticity and Fundamental Methodology
References

Chapter 5: How to End Selective Reporting in Animal Research

5.1 Introduction
5.2 Definition and Different Manifestations of Reporting Bias
5.3 Magnitude of Reporting Biases
5.4 Consequences
5.5 Causes of Reporting Bias
5.6 Solutions
References

Chapter 6: A Comprehensive Overview of Mouse Models in Oncology

6.1 Introduction
6.2 Xenograft Mouse Models
6.3 Genetically Engineered Mouse Models
6.4 Applications for GEMMs in Compound Development
6.5 Humanized Mouse Models: toward a More Predictive Preclinical Mouse Model
6.6 Conclusions: Potentials, Limitations, and Future Directions for Mouse Models in Cancer Drug Development
References

Chapter 7: Mouse Models of Advanced Spontaneous Metastasis for Experimental Therapeutics

7.1 Mouse Tumor Models in Cancer Research
7.2 The Evolution of Metronomic Chemotherapy
7.3 Development of Highly Aggressive and Spontaneously Metastatic Breast Cancer Models
7.4 Is There Any Evidence that Models of Advanced Metastatic Disease Have the Potential to Improve Predicting Future Outcomes of a Given Therapy in Patients?
7.5 Metronomic Chemotherapy Evaluation in Preclinical Metastasis Models
7.6 Experimental Therapeutics Using Metastatic Her-2 Positive Breast Cancer Xenografts Models
7.7 Examples of Recently Developed Orthotopic Models of Human Cancers
7.8 Factors that Can Affect the Usefulness of Preclinical Models in Evaluating New Therapies
7.9 Monitoring Metastatic Disease Progression in Preclinical Models
7.10 Alternative Preclinical Models: PDX and GEMMs
7.11 Recommendations for the Evaluation of Anti-cancer Drugs Using Preclinical Models
7.12 Summary
References

Chapter 8: Spontaneous Animal Tumor Models

8.1 Introduction
8.2 Advantages of Spontaneous Canine/Feline Cancer Registries
8.3 Spontaneous Animal Tumors as Suitable Models for Human Cancers
8.4 The Swiss Canine/Feline Cancer Registry 1955–2008
References

Chapter 9: Dog Models of Naturally Occurring Cancer

9.1 Introduction
9.2 Advantages of Spontaneous Cancer Models in Dogs
9.3 Dog Cancer Models
9.4 Preclinical and Veterinary Translational Investigations in Dogs with Cancer
9.5 Necessary Developments for Realizing the Potential of Canine Models
9.6 Key Challenges and Recommendations for Using Canine Models
9.7 Conclusions
References

Chapter 10: Improving Preclinical Cancer Models: Lessons from Human and Canine Clinical Trials of Metronomic Chemotherapy

10.1 Introduction: Low-dose Metronomic Chemotherapy
10.2 Clinical Trials of Metronomic Chemotherapy
10.3 Veterinary Metronomic Trials in Pet Dogs with Cancer
10.4 Lessons Learned from Clinical Trials: Improving the Predictability of Preclinical Models
10.5 Conclusions
Acknowledgements
References

Index

End User License Agreement

List of Illustrations

Chapter 3: Study Design

Figure 3.1 The sample size needed per group as a function of the standardized effect size (SES, or signal–noise ratio) for 80% (triangles) or 90% (circles) power assuming a two-sample -test with a two-sided alternative hypothesis and a significance level of 0.05. In the text example the SES was 1.5, so such an experiment would need about eight mice/group for an 80% power or about 10 mice/group for a 90% power.

Chapter 4: Improving External Validity of Experimental Animal Data

Figure 4.1 (a) The concept of standardization. First, by reducing variation in the data, standardization within experiments increases test sensitivity. Because higher test sensitivity allows a reduction of sample size, standardization is also promoted for ethical reasons with a view to reducing animal use. Second, standardization between experiments is believed to reduce between-experiment variation, thereby improving the comparability and reproducibility of results between laboratories. (b) Example of a standardized laboratory environment.
Figure 4.2 Blocking and systematic variation in animal experiments. (a) Example of an experimental design consisting of three blocks (red, blue, green) to compare three treatments (A, B, C). Within each block, experimental subjects are as homogeneous as possible, but between blocks there are differences. (b) Example of a block design for an experiment with mouse genotype (−/−, +/−, +/+) as treatment and three different experimental blocks (red, blue, green) to introduce systematic experimental variation. Blocks (e.g., cages) may differ in, for example, age of animals and/or housing condition (with or without shelter, nesting material or running wheel (RW)). In principle, each block might represent a slightly different experimental setting. Including block as factor in the statistical analysis controls for the environmental variation between the blocks and increases the generalizability of the results without inflating sample size.
Figure 4.3 Hypothetical integrative approach combining heterogenization of experimental variables and adaptive plasticity. Example of an experimental design aimed at addressing the effects of a novel compound. We propose combining heterogenization of rearing conditions (e.g., non-challenging vs. challenging neonatal environments) with phenotypic plasticity considerations: in our proposal, subjects reared in a non-challenging environment should be tested under non-challenging adult conditions (home-cage automated testing) and subjects reared in a challenging environment should be tested under challenging adult conditions (traditional testing involving removal from the cage and testing in unfamiliar environments).

Chapter 5: How to End Selective Reporting in Animal Research

Figure 5.1 Forest plot showing that contradiction of two trial results in terms of statistical significance is fully compatible with exact agreement of their estimated effect size. Here the trials by Smith and Jones both measured a preventive treatment effect of 0.778 relative to control. A huge sample size difference explains the seeming contradiction when a rigid significance testing paradigm is applied.
Figure 5.2 Flow chart depicting a system designed to reduce research waste and reporting bias. Note that animalresearch.gov is a non-existing website used to illustrate preregistration of all animal studies. Its name was inspired by clinicaltrials.gov, the US-based website for preregistration of (randomized) clinical trials.

Chapter 7: Mouse Models of Advanced Spontaneous Metastasis for Experimental Therapeutics

Figure 7.1 (a) Schematic of a series of experiment testing metronomic vinblastine chemotherapy on human tumor cell lines growing in immunodeficient mice as either primary tumors of metastases. In some experiments we noted that primary tumors would respond poorly to a given therapy, such as metronomic vinblastine (b), that would effectively cure mice that had the same tumor cell line growing as established metastatic disease [8].
Figure 7.2 Selection of metastatically aggressive subpopulations of tumor cells often requires rounds of in vivo selection. For example, a primary tumor of the human melanoma cell line WM239A was established subdermally (orthotopically) in SCID mice, allowed to grow and establish itself, and then was surgically removed. Months later the mice showed evidence of lung metastases—from which the subline 113/6-4L was isolated. In some studies, these cells are re-implanted into a new host for an additional round of selection. A similar approach using orthotopic implantation (into the mammary fat pad) was also used to derive, the highly metastatic 231/LM2-4 variant of the human breast cancer cell line MDA-MB-231, and the H2N.met2.hCG metastatic variant was derived from Her-2 expressing MDA-MB-231 cells. H2N.met2.hCG were then transfected to express and secrete the β-subunit of human chorionic gonadotropin (hCG) protein, which can be used as a surrogate molecular marker of disease burden.
Figure 7.3 Schematic of the selection of H2N.met2.hCG metastatic variants in immunodeficient SCID mice.
Figure 7.4 A comparison of the effects of daily sunitinib (SU) therapy in separate experiments on the growth of orthotopic primary breast cancers (a) versus advanced metastatic disease, after the primary tumor was resected (at Day 20). Therapy started on Day 41 (b). The tumor line used for the study was a variant (called LM2-4) of the MDA-MB-231 human breast cancer line, isolated by Munoz et al. [12] having aggressive spontaneous metastatic potential from established but resected primary (orthotopic) tumors.
Figure 7.5 A disparity between primary tumors and metastasis in terms of response to therapy was observed with the human breast cancer model 231/LM2-4 treated with the combination of metronomic daily cyclophosphamide and the 5-fluorouracil oral prodrug, UFT (tegafur + uracil). Primary tumor growth curves (a) showed no anti-tumor effect by combining UFT with CTX, and did not foreshadow the remarkable survival results obtained when treating mice with established spontaneous metastases of the same line treated with the identical UFT/CTX doublet metronomic therapy (b).
Figure 7.6 (a,b) Differential response of advanced metastases and primary tumors to therapy. Contrasting outcomes when H2N.met2.hCG tumor-bearing mice are treated with trastuzumab monotherapy, either as localized single primary tumors or established multiple spontaneous visceral metastases. Trastuzumab monotherapy (red) inhibits the growth of tumors compared with controls (black) but had no appreciable impact on the growth of advanced visceral metastases (as assessed by the hCG secreted by the tumor cells, which was subsequently measured in the mouse urine).

Chapter 8: Spontaneous Animal Tumor Models

Figure 8.1 Tumor location and diagnoses. n = number of tumors found in a location; % = proportion of the location compared with the total of locations. Figure in and around the slices = relative proportion of tumor diagnoses/location. Tumor diagnoses lower than 1% were added into “Other tumors”; locations lower than 1% and unclassified location were not listed. With the exception of “male sexual organs” the listed locations are not sex specific.
Figure 8.2 The risk (OR) of developing a tumor by sex and castration status subclassified by examination methods.
Figure 8.3 Risk to develop a malignant tumor vs. no tumor – pure breeds compared to crossbreeds. Observations: n = 90 085.
Figure 8.4 Geographic distribution of canine patients with tumors and ratio of benign to malignant tumors in Switzerland.
Figure 8.5 Number of samples of the most common tumor diagnoses an their malignancy.
Figure 8.6 Risk (OR) of different breeds to develop a tumor compared with European shorthair cats.
Figure 8.7 The risk (OR) of cats developing a tumor according to their sex or castration status, subclassified by examination methods.
Figure 8.8 Tumor location and diagnoses in feline patients. n = number of tumors found in a location; % = proportion of the location compared to the total of locations. Figure in and around the slices = relative proportion of tumor diagnoses/location.
Figure 8.9 Geographic distribution of feline patients with tumors and ratio of benign to malignant tumors in Switzerland.

Chapter 9: Dog Models of Naturally Occurring Cancer

Figure 9.1 Popular breeds and the percent of deaths from cancer. On the Y-axis, breeds are ordered according to percent of deaths due to cancer. (Data from [24].) Next to breed name on X-axis in parenthesis is the popularity of breed rank-ordered for 2013 according to the AKC (https://www.akc.org/reg/dogreg_stats.cfm). All pictures used from (www.akc.org/breeds/).
Figure 9.2 Estimated new cases and deaths for common cancers in the USA. According to Centers for Disease Control (CDC), cancer is narrowly second only to heart disease for the leading causes of death. In 2011, heart disease claimed 596 577 lives, while cancer took only slightly less at 576 691 lives (http://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm). Coupled with loss of life is also the financial burden. In 2010, cancer prevelance cost have been estimated between 124.5 and 216.6 billion USD (http://www.cancer.org/cancer/cancerbasics/economic-impact-of-cancer, [26]). This suggests that landmark revolutions are needed in treatment and care of cancer patients. No animal model completely recapitulates the humans cancers perfectly, but the naturally occurring cancers in dogs more closely resemble the disease then do other animal models. Data for Figure taken from “How Common is Cancer,” http://seer.cancer.gov/statfacts/html/all.html.
Figure 9.3 Number of publications related to dogs and cancer. We performed a search using the PubMed database (http://www.ncbi.nlm.nih.gov/pubmed) for publications related to dogs and cancer. We used the following search terms: “dog OR dogs OR canine OR dogs AND cancer.” Years were grouped and average publications for years calculated. From this, we calculated the annual growth rate and total percent change (percent growth rate = percent change/number of years; http://www.miniwebtool.com/percent-growth-ratecalculator/?present_value=391&future_value=773&num=12).
Figure 9.4 Germinal center of DLBCL. Antigen-activated B-cells differentiate into centroblasts that undergo clonal expansion in the dark zone of the germinal center. During proliferation, the process of somatic hypermutation introduces base-pair changes that can lead to changes in the amino acid sequence. Centroblasts then differentiate into centrocytes and move to the light zone, where the modified antigen receptor, with help from other immune cells, is selected for improved binding to the immunizing antigen. Newly generated centrocytes that produce an unfavorable antibody are removed. Cycling of centroblasts and centrocytes between dark and light zones appears to be mediated by a chemokine gradient. Antigen-selected centrocytes eventually differentiate into memory B cells or plasma cells. Centroblasts with genetic alterations that do not undergo apoptosis as expected can become GBC DLBCL. Likewise, plasma cells can become ABC DLBCL. Not shown: Thymic cell that leads to PMBL. Listed are several known malignant transformations. Adapted from [163, 207, 208].
Figure 9.5 Integration of pet dogs with cancer into translational drug development studies. Canine cancer models compliment the use of both conventional preclinical models (mouse, research-bred dog, and non-human primate) and human clinical trials and their inclusion in preclinical and translational studies will facilitate the rapid intermediate evaluation of agents prior to or after early human trials. Translational drug development studies in dogs may answer important questions about a new drug candidate such as toxicity, biological activity, and establish pharmacokinetic pharmacodynamic relationships for an agent before it enters human studies. Importantly, the comparative approach may answer questions that emerge in early phase human trials such as optimized dosing schedules, combination therapies, and the establishment of surrogate biomarkers or molecular imaging endpoints that will inform the evaluation of these agents as they move into later stages of development. Importantly, the totality of information generated from this comparative and integrative approach will likely reduce the late attrition rate of new cancer therapeutics and contribute to the identification of agents most likely to succeed in human clinical trials. Reprinted from [117] with permission from Macmillan Publishers Ltd: Nature Rev Cancer, copyright 2008.
Figure 9.6 Comparative imaging study in dogs with sinonasal tumors investigating the spatiotemporal stability of Copper(II)-diacetyl-bis(N⁴-methylthiosemicarbazone) (Cu-ATSM) and 3′-deoxy-3′-¹⁸F-fluorothymidine (FLT) positron emission tomography distributions in during radiation therapy. (a) Sagittal positron emission tomography/computed tomography (PET/CT) slices are shown from a dog with sinonasal carcinoma pretreatment (pre) and mid-treatment (mid) with intensity modulated radiation therapy. Cu-ATSM (middle) and FLT (bottom) scans demonstrate stable spatial distributions of both radiotracers during therapy. (b) Voxel-based scatter plots comparing pretreatment (pre) and mid-treatment (mid) Cu-ATSM and FLT standardized uptake value (SUV) distributions and Spearman rank correlation coefficients (upper left) for dogs with nasal carcinoma or sarcoma. Spatial distributions and uptake of dose painting targets Cu-ATSM and FLT remain stable through mid-treatment, regardless of histology. Reprinted from [305] with permission © 2014 Elsevier.

Chapter 10: Improving Preclinical Cancer Models: Lessons from Human and Canine Clinical Trials of Metronomic Chemotherapy

Figure 10.1 (a) Study characteristics, (b) treatment settings, (c) types of cancer studied, and (d) ranges of performance status of eligible patients of 80 metronomic chemotherapy trials in adults recently reviewed by Lien et al. [10].
Figure 10.2 Possible different approaches to the discovery of new biomarkers of metronomic chemotherapy. IL-8, interleukin-8; VEGF, vascular endothelial growth factor; and SNPs, single nucleotide polymorphisms.

List of Tables

Chapter 3: Study Design

Table 3.1 The use of a spreadsheet to assign treatments to experimental subjects at random.
Table 3.2 Block randomization.

Chapter 5: How to End Selective Reporting in Animal Research

Table 5.1 Additional administrative steps for editors in a system in which the initial submission contains no results

Chapter 8: Spontaneous Animal Tumor Models

Table 8.1 Canine tumor entities used as models for human tumors
Table 8.2 Feline tumor entities as models for human tumors
Table 8.3 Relative and absolute breed distribution of feline patients with and without tumors
Table 8.4 Comparative numerical ranking of tumors diagnosed in different organs/organ systems of humans, dogs, and cats in Switzerland

Chapter 9: Dog Models of Naturally Occurring Cancer

Table 9.1 Proportional mortality due to tumors/neoplasm over years by breed
Table 9.2 Breed cancer-specific mortality for OS and mammary tumors
Table 9.3 Over-representation of specific cancers in specific breeds
Table 9.4 Comparative aspects of spontaneous cancers in humans and dogs

Chapter 10: Improving Preclinical Cancer Models: Lessons from Human and Canine Clinical Trials of Metronomic Chemotherapy

Table 10.1 Clinical trials of metronomic chemotherapy in pet dogs

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List of Contributors

Carlos E. Alvarez
The Ohio State University
Medicine and Veterinary Medicine
700 Children's Drive, W431
Columbus, OH 43205
USA

Karin Blumer
Novartis International AG
Fabrikstr. 6
4002 Basel
Switzerland

Guido Bocci
University of Pisa
Clinical and Experimental Medicine
Via Roma 55
56126 Pisa
Italy

Gianluca Boo
Collegium Helveticum
ETH Zürich
Schmelzbergstr. 25
8092 Zürich
Switzerland

Lex M. Bouter
VU University Medical Center
Department of Epidemiology and Biostatistics
De Boelelaan 1117
1081 HV Amsterdam
The Netherlands

Urban Emmenegger
University of Toronto
Sunnybrook Health Sciences Centre
2075 Bayview Avenue
Toronto, ON M4N3M5
Canada

Joelle M. Fenger
Department of Veterinary Clinical Sciences
The Ohio State University
Veterinary Medical Center
601 Vernon Tharp Street
Columbus, OH 43210
USA

Michael F.W. Festing
University of Leicester
MRC Toxicology Unit
Lancaster Road
Leicester LEI 9HN
UK

Giulio Francia
The University of Texas at El Paso
Department of Biological Sciences,
Border Biomedical Research Center
El Paso, TX 79902
USA

Ramona Graf
Collegium Helveticum
ETH Zürich
Schmelzbergstr. 25
8092 Zürich
Switzerland

Katrin Grüntzig
Collegium Helveticum
ETH Zürich
Schmelzbergstr. 25
8092 Zürich
Switzerland

Robert S. Kerbel
University of Toronto
Biological Sciences Platform
Sunnybrook Research Institute
S-217, 2075 Bayview Avenue
Toronto, ON M4N 3M5
Canada

William C. Kisseberth
The Ohio State University
Department of Veterinary Clinical Sciences
448 VMAB
1900 Coffey Rd.
Columbus, OH 43210
USA

Esther K. Lee
University of Toronto
Sunnybrook Health Sciences Centre
2075 Bayview Avenue
Toronto, ON M4N3M5
Canada

Cheryl A. London
Department of Veterinary Biosciences
The Ohio State University
454 VMAB
1900 Coffey Rd.
Columbus, OH 43210
USA

Simone Macri
Istituto Superiore di Sanità
Department of Cell Biology and Neuroscience
Viale Regina Elena 299
00161 Roma
Italy

Marianne I. Martic-Kehl
Collegium Helveticum
STW/ETH-Zentrum
Schmelzbergstr. 25
8092 Zürich
Switzerland

Irving Miramontes
The University of Texas at El Paso
Department of Biological Sciences
Border Biomedical Research Center
500 W. University Avenue
El Paso, TX 79902
USA

Anthony J. Mutsaers
Department of Clinical Studies
Department of Biomedical Sciences
Ontario Veterinary College
University of Guelph
50 Stone Road
Guelph, ON N1G2W1
Canada

Karla Parra
The University of Texas at El Paso
Department of Biological Sciences
Border Biomedical Research Center
500 W. University Avenue
El Paso, TX 79902
USA

Andreas Pospischil
Collegium Helveticum
ETH Zürich
Schmelzbergstr. 25
8092 Zürich
Switzerland

Gerben ter Riet
University of Amsterdam
Academic Medical Center, J2-116
Meibergdreef 9
1105 AZ Amsterdam
The Netherlands

S. Helene Richter
University of Münster
Department of Behavioural Biology
Badestraße 13
48149 Münster
Germany

Jennie L. Rowell
Center of Excellence in Critical and Complex Care
College of Nursing
The Ohio State University
390 Newton Hall
1585 Neil Ave.
Columbus, OH 43210
USA

Chiara Spinello
Istituto Superiore di Sanità
Department of Cell Biology and Neuroscience
Viale Regina Elena 299
00161 Roma
Italy

P. August Schubiger
Collegium Helveticum
ETH Zürich
Schmelzbergstr. 25
8092 Zürich
Switzerland

Divya Vats
ETH Zürich
Institute for Biomedical Engineering
Wolfgang-Pauli-Str. 27
8093 Zürich
Switzerland

Isain Zapata
Center for Molecular and Human Genetics
The Research Institute at Nationwide Children's Hospital
700 Children's Drive
Columbus, OH 43205
USA

Preface

The second demand of The Three R guiding principles for more ethical use of animals in testing (already established in 1959 [1]) reads:

Reduction: use of methods that enable researchers to obtain comparable levels of information from fewer animals, or to obtain more information from the same number of animals.

Quoted from Wikipedia July 2015

The present volume on Animal Models for Human Cancer: Discovery and Development of Novel Therapeutics by Marianne Martic-Kehl and P. August Schubiger focuses in essence on the design and numerical evaluation of animal tests in cancer drug development. This field of research needs special attention because of various reasons. The most challenging one being the quality and validity of human tumor model in rodents, the most frequent used animal in cancer drug development. Since mice do not develop spontaneous human cancer, genetically modified organisms are the standard. Higher animals, like cats and dogs, would be the choice then, implicating an ethical conflict that is also at a “higher” level, besides the cost.

The volume editors have been able to invite distinguished experts from leading institutions and research organizations to reason about the current situation, to analyze pros and cons, and to come up with new suggestions to improve the situation. While this is definitely difficult to do for the animal experiment itself, much neglect can be detected in its statistical evaluation. How can it be that good experimental practice is violated in so many papers that have all passed peer review. Randomization, multiple use of the animals, clear and validated endpoints, and sufficient numbers are very often omitted or not commented on, as a meta-study of several hundred of recent publications in the field has revealed. Here, the second demand of the 3Rs is affected to a considerable extent, and at the same time could easily be followed by a more rigorous peer review system.

Marianne Martic-Kehl and P. August Schubiger deserve deep respect for tackling problems, which have been of concern for several decennia, but have always been and still are a kind of taboo. You don't make friends in the scientific community by asking those nasty questions. Hence, the scientific community should be grateful for the researchers having the “guts” to point to neglect and suggest alternatives and improvements.

In addition, we are very much indebted to Frank Weinreich and Waltraud Wüst, both at Wiley-VCH. Their support and ongoing engagement, not only for this book but for the whole series Methods and Principles in Medicinal Chemistry adds to the success of this excellent collection of monographs on various topics, all related to drug research.

Düsseldorf

Weisenheim am Sand

Zürich

Raimund Mannhold
Hugo Kubinyi
Gerd Folkers

January 2016

Reference

1. Russell, W.M.S. and Burch, R.L. (1959). The Principles of Humane Experimental Technique, London: Methuen.

A Personal Foreword

As animal well being is a prerequisite for reliable experimental results, it is of utmost importance to seek for methods and procedures that can reduce suffering of the animals and improve their welfare.

This sentence, closing Vera Baumans' conclusion in a 2004 paper on ethical dilemmas in animal research [1], unfolds the dilemma of what suffering means for animals. What is the perspective to be taken, where to position the borderline between objectivity and subjectivity? Are anthropocentric views the good or the flipside of the coin?

While it is uncontested that animals feel pain, the question remains of which kind it is. The McGill pain questionnaire will not apply to rodents. This question has been around in the literature for almost 4000 years. Animals as “tools” for research are ascribed to the times of Hippocrates, which is still under dispute. The famous Roman physician Galenus, however, became known as the Father of Vivisection. The debate probably flared up for the first time in the seventeenth century. One of the founding fathers of the enlightenment, the Dutch philosopher Baruch de Spinoza, “admitted that animals suffer, but we are within our moral rights to use them, as we please, treating them in the way which best suits us; for their nature is not like ours, and their emotions are naturally different from human emotions” [2]. This view seems to be enforced by what is widely known as the “Cartesian Gap,” assuming that Descartes categorized animals as “meaty machines” or as automata. However, when it comes to emotions I get the impression that Descartes – at least for the human being – is somewhat conciliating: Ainsi que souuent vne mesme action, qui nous est agreable lors que nous sommes en bonne humeur, nous peut déplaire lors que nous sommes tristes & chagrins.¹ It has been more than 100 years later that Jeremy Bentham fiercely and provokingly opposed the Cartesian perspective:

The French have already discovered that the blackness of the skin is no reason why a human being should be abandoned without redress to the caprice of a tormentor. It may one day come to be recognized that the number of the legs, the villosity of the skin, or the termination of the os sacrum [tailbone),are reasons equally insufficient for abandoning a sensitive being to the same fate. What else is it that should trace the insuperable line? Is it the faculty of reason, or perhaps the faculty of discourse? But a full grown horse or dog is beyond comparison a more rational as well as more conversable animal, than an infant of a day, or even, a month old. But suppose they were otherwise, what would it avail? The question is not, Can they reason? nor Can they talk? but Can they suffer? [3]

Bentham is regarded among the first to foster animal rights, the ability to suffer being the benchmark, the insuperable line, instead of the ability to reason. Again approximately after a century Darwin established the biological similarities between man and animal. Not surprisingly, however, his seminal scientific findings led to an increase in animal experimentation [1], since they paved the ground for a rationale to use animals as a model for human physiology and biological function.

It was Darwin's contemporary, the great physiologist Claude Bernard, who established this similarity between man and animal as a scientific method and became the founding father of modern experimental medicine [4]. His key message precisely describes the contemporary paradigm of biomedical research:

Le médecin qui est jaloux de mériter ce nom dans le sens scientifique doit, en sortant de l'hôpital, aller dans son laboratoire, et c'est là qu'il cherchera par des expériences sur les animaux à se rendre compte de ce qu'il a observé chez ses malades, soit relativement au mécanisme des maladies, soit relativement à l'action des médicaments, soit relativement à l'origine des lésions morbides des organes ou des tissus. C'est là, en un mot, qu'il fera la vraie science médicale.²

Claude Bernard incorporated the principles of “hard science,” in particular physics and chemistry, into the realm of medical research and made them the cornerstones of his scientific method [4]. Since (physical or chemical) experiments in humans are clearly beyond any moral or legal acceptance, animal “deputies” became the scientific object to serve as the mere substance in modeling a human disease.

With the advent of genetic modification techniques in the 1980s, transgenic animals and in particular rodents—mice being the working horses of modern biomedical animal experimentation—opened a new era in disease modeling. Single gene function, genetic components, and regulatory networks could be correlated with diseased conditions in humans. Still, we are facing the problem of “bridging the gap” in between mouse genomics and the disease phenomenon in the individual human being. Hence, the front edge research in biomedical is focusing on non-human primates (NHPs).

Due to physiologic differences between rodents and higher primates, such as life span, brain size and complexity and motor repertoire, as well as the availability of cognitive behavioral testing, NHPs are considered one of the best animal models; especially for complex disorders that correlate with aging, cognitive behavioral function, mental development, and psychiatric dysfunctions. In addition to neural psychiatric related disorders, metabolic function, reproductive physiology, and immunology are other areas of research where the NHP model has been widely used. [5]

Given the complexity of a disease or illness, the causality of which is, as we increasingly understand, far from a simple “one gene, one disease” situation that can be reduced to a single biochemical step in the cell only in a few cases. Many more parameters in animal experimentation have to be considered than just measurement of the chemistry and physics, often termed “surrogate parameters.” Referring back to the opening quotation, environmental conditions play a crucial role in obtaining reliable scientific results from the models. Overcoming structuralistic views and granting animals a body–mind relation too, probably very similar to humans, does not facilitate animal experimentation and its interpretation. The human–animal boundary is closer.

But besides ethical and moral concerns in general, there are good scientific and economical reasons to scrutinize and carefully optimize laboratory experimentation with animals. Those experiments are costly, need special infrastructure, lots of paperwork and hence quite a number of laboratory staff; each outcome of the experiments should contribute to our knowledge. The battle between hypothesis-driven or explorative research can already be found in the musings of Claude Bernard.² The demand for both is to extract the maximum of information. Scanning current scientific papers seems, provocatively, to be rather the exception than the rule as the editors and their distinguished invited authors of the present volume show in their contributions. Good laboratory practice as randomization, clear endpoints, sound statistics, selective reporting, and publication bias are at stake and are often ruthlessly abandoned. There seems to be much room for improvement.

Emerging from a fellowship at the Collegium Helveticum, Marianne Martic-Kehl and P. August Schubiger, with their background of active researchers in life sciences, focused for several years on getting hard data about the practice of animal experiments, mostly in rodents, with importance placed on cancer research. Over the years they have continuously confronted their colleagues with their findings and elicited fierce debates in the interdisciplinary environment of the Collegium. The project culminated in a final symposium, the results of which yielded the contents of this book. The author is extremely grateful to both of the editors to have picked up a kind of taboo topic in biomedical research and sometimes stubbornly to follow its traces in the vast universe of biomedical publications.

The book deserves a wide readership the scientific community and beyond.

Gerd Folkers

January 2016

References

1. Baumans, V. (2004) Use of animals in experimental research: an ethical dilemma? Gene Ther., 11, 64–66.
2. Soccio, D.J. (2009) Archetypes of Wisdom. 9th edn, Boston, MA: Cengage Learning, p. 55f.
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