Big data study shows unnecessary animal testing can be reduced

At a time when the pharma industry has committed to reducing the number of animal tests that take place, and when safety issues are one of the main reasons drugs fail clinical trials, Elsevier and German pharma major Bayer (BAYN: DE) have conducted a big data study to analyse how ‘predictive’ animal testing is, in relation to humans.

Analysing more than 1.6million adverse events reported in both humans and the five most commonly used animals in US Food and Drug Administration and European Medicines Agency regulatory documents, this is the broadest published study to date.

The main finding is that some animal tests are far more predictive of human response than others, yet this fact is not always considered. This shows that through better data analysis, unnecessary animal tests can be cut out, as researchers can select tests based on the species with the most predictive animal-human relationship for the drug in question.