ABSTRACT
It was once a fairly random process: scientists would have an idea about a chemical and then see how it worked in living things. The drug development timeline could stretch a decade or longer and the final cost to bring a new drug to market could exceed $1 billion—with no guarantee the drug would be approved or that patients would take it. But identifying and developing new drugs has been revolutionized by the availability of databases based on genomics and computational software that let researchers model how a drug will interact with its target virtually. The result of these new technologies? Drug developers can scan millions of molecules using computers to narrow down potential treatments before even setting foot in a lab and older drugs can be repurposed more quickly for new indications. What’s more, it’s now easier to match data from real patients to the results from drug studies. Scientists can look at the characteristics of millions of patients with diabetes, for instance, to see what their lab results reveal, how their disease progresses, and how they respond to particular treatments. The stakes are high, but the payoff can be even bigger, as some of these new drugs are expected to be huge sellers. Getting from through the R&D process to market launch is still a gamble, but data and technology are reducing some of the uncertainty in the process, as this chapter will describe.
