Marie Davidian, a statistics professor at North Carolina State University, connected the seemingly unrelated topics of statistics and the Human Genome Project by explaining their role in determining the best possible treatment for medical patients at Elon University Nov. 5.

But she first posed a question to the audience.

“Why is a statistician talking to you about personalized medicine?” Davidian asked.

According to Davidian, the role of statistics in personalized medicine is to examine the broad, sweeping trends of particular treatments in order to determine the types of people for whom they are best suited. Statisticians do not deem certain treatments better than others, but rather which are best suited for specific groups of people.

“The hope is that new treatments be developed to target a sub-group that is likely to be affected,” she said.

Such statistics have enabled the developments of personalized medicine, the emerging practice of tailoring a patient’s medical treatment — including drugs, biologic products, medical devices, and surgical procedures — to his or her genetic predisposition.

Personalized medicine is made possible by the Human Genome Project, a collaborative, 13-year effort coordinated by the U.S. Department of Energy and The National Institute of Health to identify and sequence the genes and chemical case pairs that make up human DNA.

To illustrate the dramatic genetic differences between people, Davidian displayed a graphic featuring Alana Thompson, the "Honey Boo Boo child," alongside rapper Jay-Z. The Human Genome Project has proved the two have different genetic makeups based on their distinct sets of DNA.

“Now, do you really think these two should have identical treatments?” she asked, referencing the screen.

The availability of information on the human genome has allowed doctors to test particular medicines and treatments on patients with certain genes or genetic traits. Statisticians have then analyzed the data to determine which genetic predispositions lend themselves to certain treatment options.

Despite the potential of personalized medicine, Davidian said she believes traditional medical clinics may never be replaced in full.

“You can’t possibly collect all the correct information to make the perfect decision,” Davidian said. “Clinicians have judgments that can never be captured by data.”

But Davidian reiterated the value of statistics.

“I hope I’ve convinced you that we statisticians are good for something,” Davidian said.

Sophomore Danny Wasky needed no further convincing.

“I think it’s going to hugely impact treatments, and it’s going to be very key in helping our future selves stay healthy,” he said.