Drivers and ethical impacts of insufficient validation of antibodies in research
Biddle, M.; Cooper, J.; Blades, K.; Ruddy, D.; Krockow, E. M.; Virk, H.
Show abstract
Lack of antibody validation by researchers frequently misdirects biomedical research, yet the ethical consequences -- particularly avoidable use of animal and human biological materials -- remain unquantified. Using focus groups (n=12), surveys (n=107), and systematic analysis of 785 publications, we examined how researchers select and validate antibodies, and quantified the downstream ethical costs. Antibody selection is substantially influenced by social factors such as previous laboratory use and peer recommendations, while systematic evaluation of performance characteristics remains limited. From a dataset of 614 antibodies subjected to rigorous characterisation using knockout controls, 97 (15.8%) failed across all tested applications; we systematically searched for publications linked to these antibodies. Within the 760 publications (those where validation status could be confirmed), only 120 (15.8%) presented any validation evidence -- despite 72.0% of surveyed researchers reporting having used at least one recommended validation method. The remaining 640 papers consumed a minimum of 8,064 animal samples and 4,424 human tissue samples using antibodies with demonstrated poor performance, without any evidence confirming fitness for the specific experimental purpose used. Conservative extrapolation suggests millions of animal and human tissue samples have been consumed globally in experiments using antibodies that would fail independent testing. Researchers identified time, cost, and lack of supervisor support as primary barriers, whilst strongly supporting open data sharing, dedicated validation funding, and publisher requirements as solutions. These findings quantify for the first time the ethical costs of inadequate antibody validation and highlight the need for coordinated stakeholder interventions to reduce avoidable biological sample waste in biomedical research.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.