A new computational tool could help better determine which drugs should move from animal testing to humans. It could also sooner detect a reason why a drug might fail, guiding how a clinical trial should be set up.

Scientists might be able to catch problems like this one earlier in the drug development process, when drugs move from testing in animals to clinical trials, with a new computational model developed by researchers from Purdue University and Massachusetts Institute of Technology.

The researchers call the model «TransComp-R.» In a study published in Science Signaling, they used the model to identify an overlooked biological mechanism possibly responsible for a patient’s resistance to infliximab.

Such a mechanism is hard to catch in preclinical testing of new drugs because animal models of human diseases may have different biological processes driving disease or a response to therapy. This makes it difficult to translate observations from animal experiments to human biological contexts.

«This model could help better determine which drugs should move from animal testing to humans,» said Doug Brubaker, a Purdue assistant professor of biomedical engineering, who led the development and testing of this model as a postdoctoral associate at MIT.

«If there is a reason why the drug would fail, such as a resistance mechanism that wasn’t obvious from the animal studies, then this model would also potentially detect that and help guide how a clinical trial should be set up,» he said.

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Materials provided by Purdue University. Original written by Kayla Wiles. Note: Content may be edited for style and length.