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FELASA Module 9. Animal Models and Experimental Design
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Module 9 of the FELASA ABD function course covering Animal Models and Experimental Design.
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FELASA Module 9: Animal Models and Experimental Design When using an animal model you have to consider whether you have a model of
high fidelity or high discrimination
In a model where young seagulls are responding to a model that looks like their
mother, they are more likely to respond to a sick with a red spot on it than a
realistic model
The only clue the animals have that something is their mother is the contrast
between the spot and the white beak/stick and this contrast is higher on the
stick
The lookalike model is a high fidelity model, whereas the stick is a high
discrimination model
Most animal models are models of high discrimination
US NIH defines a model as a living organism in which normative biology or
behaviour can be studied, or in which a spontaneous or induced pathological
process can be investigated, and in which the phenomenon in one or more
respects resembles he same phenomenon in humans or other species of animal
This means we select one phenomenon in the animal which is comparable to
humans that we want to model
In spontaneous models this phenomenon occurs spontaneously
In induced models the phenomenon is induced chemically or surgically
For example by causing an animal to have type 1 diabetes by removing the
pancreas
A negative model is where the phenomenon never occurs
For example if you study why a pig never activates coagulation factor VII
when fed a high fat diet
An orphan model is where a veterinary patient develops a disease which looks
like a human disease
E.g. when a cat develops obesity and type 2 diabetes
Models monitor various parameters
E.g. blood pressure, blood values and weight
You need to determine the most important parameter (your primary readout)
Other parameters are secondary readouts- these are good to use for
mechanistic explanations of changes in your primary readout
Animal models are used to obtain information about disease and its prevention,
diagnosis and treatment
They are essential for drug discovery and testing medicine
Using animal models allows us to perform experiments that would be
impractical or prohibited in humans
If drugs are tested in a poor model they may not have the same result in humans
Therefore drugs should be tested in multiple high discrimination models for
different aspects of the disease
Example of a high fidelity vs high discrimination model in human health
Chimpanzees have a high fidelity to humans but infecting them with HIV isn’t
useful because they don’t develop signs of infection
It is better to infect cats, which have a low fidelity to humans because they can
be infected with feline immunodeficiency virus disease (from the same family as
HIV) and they will develop similar symptoms
External validity (how well a model translates to the species it is modelling) is split
into three criteria
, Construct validity: The extent both human and the model phenomenon studies
can be explained by the same theory
E.g. the cause of the disease is the same
Face validity- the similarity of the appearance of the phenomenon between
animals and humans
E.g. The symptoms of feline immunodeficiency virus are the same as HIV
Predictive validity- a measure of how much a drug has the same effect in
humans and animal models
Rats with their pancreas removed have low construct validity as a diabetes model
as humans don’t develop diabetes from a missing pancreas
The model has low face validity because the rats will develop extra symptoms
If you want to test the effect of insulin to alleviate diabetes it has high predictive
validity
For validation of an animal model it is important to consider the cause and effect
relationship between an intervention and an outcome- this is the internal validity
Internal validity is dependent on experimental design, randomization, proper
controls and the ability to reproduce research
Reproducibility crisis- up to half of all studies can’t be replicated
This includes cherry-picking data, publication bias for positive results and
insufficient reporting of experimental settings
Using animal models allows us to standardize experimental environments which
decreases variance and increases power
This reduces group size (reduction in the 3Rs
High variance means high reproducibility but low power and also more animals
needed
To reduce variation pathogen free mice have been bred
These mice have little diversity in gut microbiota
Gut microbiota can play an important role in rodents
This means that the breeder the animals are purchased from can influence
results
In an experiment with uncontrolled variation positive results in a heterogenous
animal are more reproducible and have less type I errors (i.e false positives)
Negative results in a heterogenous group are more likely to be wrong so more
type II errors should be expected
Controlling variation helps this- this can be done by performing experiments on
smaller groups of mice from multiple vendors
The more complex a model is the higher the variability and frequency of
unexpected results
Test tube experiments have complexities in molecular interactions
Cell cultures experiments have complexities in how molecules interact inside
and between cells
Ex vivo experiments have complexities in how cell populations interact in an
organ
In vivo experiments have all the listed complexities in a diverse population
There are two types of variability
Technical variability
Comes from inaccurate instruments/tools, inexperienced experimenters and
poor planning
Reduced through better methods, instruments, planning, training and
experience
Reducing technical variability improves the accuracy of an experiment
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