Newsweek: By Targeting Each Patient’s Unique Tumor, Precision Medicine Is Crushing Once-Untreatable Cancers. But Only a Fraction of Patients Currently Benefit. Can Medicine Close the Gap?

Medicine is of no use if patients don't have access to it. To get new drugs out faster, researchers are using AI to speed the process of drug development. One of the biggest causes of delay in testing new drugs is recruiting enough patients for a trial. Researchers not only need a group to try the new drug, but another "control" group to get the standard treatment, for purposes of comparison. Even when a new precision drug is promising, it can take years to run the trials that demonstrate the drug actually works for an identifiable group of patients.

To speed things along, researchers are starting to use high-powered statistics and computer models to avoid having to recruit a control group at all. Instead, they use a mashup of data from past studies to predict how a real control group would fare. "The results you get from a synthetic control arm are as reliable as if you had actually enrolled control-group patients in the trial with the same physicians and protocols," says Glen de Vries, president of Medidata Solutions, which has designed the statistical tools.