Abstract
Sepsis is a major worldwide healthcare issue with unmet clinical need. Despite extensive
animal research in this area, successful clinical translation has been largely unsuccessful.
We propose one reason for this is that, sometimes, the experimental question is misdirected
or unrealistic expectations are being made of the animal model.
As sepsis models can lead to a rapid and substantial suffering – it is essential that we continually review experimental approaches and undertake a full harm:benefit impact assessment
for each study. In some instances, this may require refinement of existing sepsis models. In
other cases, it may be replacement to a different experimental system altogether, answering a mechanistic question whilst aligning with the principles of reduction, refinement and
replacement (3Rs).
We discuss making better use of patient data to identify potentially useful therapeutic targets
which can subsequently be validated in preclinical systems. This may be achieved through
greater use of construct validity models, from which mechanistic conclusions are drawn. We
argue that such models could provide equally useful scientific data as face validity models,
but with an improved 3Rs impact. Indeed, construct validity models may not require sepsis
to be modelled, per se. We propose that approaches that could support and refine clinical translation of research findings, whilst reducing the overall welfare burden on research
animals
animal research in this area, successful clinical translation has been largely unsuccessful.
We propose one reason for this is that, sometimes, the experimental question is misdirected
or unrealistic expectations are being made of the animal model.
As sepsis models can lead to a rapid and substantial suffering – it is essential that we continually review experimental approaches and undertake a full harm:benefit impact assessment
for each study. In some instances, this may require refinement of existing sepsis models. In
other cases, it may be replacement to a different experimental system altogether, answering a mechanistic question whilst aligning with the principles of reduction, refinement and
replacement (3Rs).
We discuss making better use of patient data to identify potentially useful therapeutic targets
which can subsequently be validated in preclinical systems. This may be achieved through
greater use of construct validity models, from which mechanistic conclusions are drawn. We
argue that such models could provide equally useful scientific data as face validity models,
but with an improved 3Rs impact. Indeed, construct validity models may not require sepsis
to be modelled, per se. We propose that approaches that could support and refine clinical translation of research findings, whilst reducing the overall welfare burden on research
animals
| Original language | English |
|---|---|
| Pages (from-to) | 1715-1734 |
| Number of pages | 20 |
| Journal | Clinical Science |
| Volume | 134 |
| Issue number | 13 |
| DOIs | |
| Publication status | Published - 17 Jul 2020 |
Keywords
- 3Rs
- Clinical translation
- construct validity
- mechanistic
- research animals
- sepsis