Researchers at North Carolina State University have received a $3.5 million grant from the National Institute of Allergy and Infectious Disease (NIAID) to develop mathematical and statistical models that will aid in designing new treatment strategies for HIV patients.
The researchers hope that the grant will help them devise a mathematical model that can predict the best course of treatment for “acutely” infected HIV patients, or patients who have recently been infected with the virus.
Dr. Tom Banks, mathematics professor in NC State’s College of Physical and Mathematical Sciences (PAMS) and director of NC State’s Center for Research and Scientific Computation (CRSC); Dr. Marie Davidian, PAMS professor of statistics and member of CRSC; Dr. Eric Rosenberg, clinician at Massachusetts General Hospital, professor at Harvard Medical School, and CRSC member; and Dr. Hien Tran, PAMS professor of mathematics, associate head of the Department of Mathematics, and CRSC member, received the five-year grant on July 1.
“Based on what we know about HIV, there is really no consensus on the best treatment for acutely infected individuals,” Davidian says. “The medical community needs to know how immediate drug therapy may affect the patient’s own ability to cope with the disease and the treatment itself down the line.”
When a patient is first infected with HIV, the amount of virus present in the bloodstream, or viral load, skyrockets. Current drug therapies can quickly bring that viral load down to a “set point,” or stable level. However, even without drug therapy, the patient’s viral load decreases to a set point over time, leading some researchers to wonder whether it’s best to allow a patient’s body to adapt to the virus naturally, or whether allowing the body to cope with acute infection, and thus “learn” the virus, actually damages the immune system beyond repair.
In addition, HIV patients tend to develop drug resistance or reactions to the medications the longer they are treated, necessitating frequent “drug holidays.” So the question becomes not only whether to treat these patients immediately, but also, how long should each treatment interval last.
Fortunately, the researchers exploring these questions have data on their side: more than five years of patient treatment data from Dr. Rosenberg.