Animal models are vital instruments of the drug discovery process. In addition to assessing the efficacy of
candidate molecules, in vivo disease models also help validate the therapeutic potential of molecular targets. Over recent
years, several molecules that have shown efficacy in preclinical models of respiratory diseases have failed to translate into
new medicines for chronic respiratory conditions such as asthma, chronic obstructive pulmonary disease, and idiopathic
pulmonary fibrosis. As such, many scientists have argued that these systems are of limited value; however, we propose
that a more careful and thorough approach to the characterization of these models and the interpretation of data generated
using these systems would improve their translational utility. Herein, we describe two key elements of our strategy aiming
to improve the predictive nature of these models: 1) Novel bioinformatics methods that can be used to identify animal
models that best represent specific patient populations; and 2) Innovative physiological techniques that will improve our
ability to discover drugs that can restore the functional capacity of lungs damaged during the course of the disease.
Keywords: Animal models, asthma, bioinformatics, COPD, IPF, lung physiology, respiratory disease, translational research.
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