The success of strategies like environmental enrichment highlights an inherent weakness of the animal research model: An animal’s behavior is often extremely sensitive to its environment, in ways that are difficult if not impossible to control. This raises a perennial issue in biomedical research of just how reliably conclusions drawn based on studies in mice can be faithfully applied to human disease treatment. For instance, rodents are housed in groups as a rule, but certain kinds of experiments and treatments require them to be isolated, triggering a stress response that could significantly affect their immune activation. Studies have shown that mice and rats who live with companions fare better against injury, stroke, and even tumor growth than their lonely counterparts. As a result, when mice studies ask questions about human diseases, the housing status of the mouse is often a confounding factor. Even slight variation in the ambient temperature of a mouse’s housing room can cause stress responses that affect experimental outcomes. This variability is one reason that treatments that seem promising in mice often produce underwhelming outcomes in human clinical trials.

One attractive complement to animal studies that may address some of these shortcomings is in silico, or “on a chip” medicine. In silico models apply computational modeling strategies to genomic data to predict physiological responses to drugs or other stimuli.