From idea, to lab, to clinic, to approval — it’s a long and expensive process to bring a drug to market. It also rarely succeeds.
Northeastern University researchers You Wu and Lei Xie are proposing another way: a programmable virtual human that uses artificial intelligence to predict how new drugs will affect not just a targeted gene or protein, but the entire body.
“Basically, we want to use AI and incorporate other techniques to build this kind of human representation where you can test a new compound and see how it works,” says Xie, professor of pharmaceutical sciences at Northeastern. “We want to change the drug discovery paradigm from a one-gene perspective to a systemic view of the human body.”
The proposal, which appeared in the recent edition of the peer-reviewed scientific journal Drug Discovery Today, stems from Wu and Xie’s work integrating AI and other tools to create a new way to develop drugs.
Xie says that the current pharmaceutical development model can take 10 to 15 years to develop a new drug, can cost billions of dollars, and ultimately has a 90% failure rate.
Part of the problem is that early stages of drug testing focus on a new drug’s effect on targeted genes in either in vitro or animal models, Xie says.
But a test tube or mouse is a very different environment than the human body, Xie notes.
