Blogging directly from the meeting room is exciting and inspiring but challenging and – not surprisingly! – not fully compatible with engaging in the discussion. Computer at hand, I could at least write down fragments to use when actually composing the remaining posts on the plane back. Here’s what the second session was about:
Friedlieb Pfannkuch, Roche, gave an international perspective on initiatives to promote and implement the 3Rs in regulatory testing. He showed the long list of which are legally required before a new drug can be launched on the market . A powerful illustration of what a challenge it is to make changes here, because so many changes are needed. Essentially, Pfannkuch was arguing for developing increasingly sophisticated approaches in which one looks at how small doses affect critical processes in animals, and for the systematic improvement of the reliability of safety tests (animal and non-animal tests alike) in accurately predicting what will happen in humans.
David Gallacher, Johnson& Johnson, presented one such initiative: the animal model framework. Through a series of teleconferences and sharing of data, several pharmaceutical companies work together to evaluate how good different tests are at making accurate predictions, and how they can be improved in this sense. The first results of this initiative are expected to be published in the beginning of 2011.
Ngaine Dennison from the UK Home Office presented the results of a 15-year preoccupation with reduction and refinement initiatives within one single test: the mouse bioassay for shellfish toxin. An illustrative example of how one can reason in this situation by combining scientific/technical and practical/economical considerations. This means asking questions like
- Can we administer the sample in a way that causes less harm to the animals?
- Can we reduce the duration of the test?
- Can we anaesthetize the animals to reduce suffering?
Joanna Edwards from the not-for-profit organizaton Lhasa limited presented the existing databases and softwares for data sharing in the life sciences. The idea behind this type of initiatives is to bring together existing information about substances into large and sophisticated databases. The more complete and versatile such databases are, the further they can be used to make predictions.