Epilepsy is one of the most common serious neurological conditions in the United States, affecting some 3.4 million people. Treating epilepsy, however, requires an uncommon, highly innovative approach since the types, severity, frequency, and impacts of epilepsy’s characteristic unprovoked seizures vary from person to person.
Just as the flu represents hundreds of different influenza strains, epilepsy—along with asthma, heart disease, cancer, and other common conditions—is heterogeneous, and is comprised of a group of disorders that present uniquely in each patient. Similar to how influenza viruses require targeted vaccines, epilepsy and other heterogeneous diseases are best treated with an individualized therapeutic approach.
In some studies, less than half of newly diagnosed epilepsy patients respond well to the first medicine they are prescribed, and many patients spend years cycling through therapeutic options before finally arriving at what works. In addition, multiple medications fail in about a third of patients because the epilepsy proves to be drug resistant.
Edward Han-Burgess, a researcher at a Georgia-based biopharmaceutical company, is working to take the mystery out of managing epilepsy by developing the targeted treatments patients desperately need. To achieve this goal—which could significantly improve the lives of people with epilepsy—Han-Burgess is attempting to figure out how to leverage the growing volumes of data and knowledge in epilepsy research to help people living with the disease gain control over seizures.
Specifically, Han-Burgess and his team of biopharmaceutical researchers want to get patients at high risk of drug resistance matched to experts sooner―ultimately matching the right treatment to the right patient faster. As part of the emerging scientific field of precision medicine, the research team is seeking to understand how a person’s genetic code and lived healthcare journey affect disease pathology. In the case of epilepsy, the diverse range of pathways and experiential differences that characterize unprovoked seizures remain unclear. So, finding the optimal treatment can take time.
That’s where Han-Burgess and his team come in. Using leading edge machine learning approaches—an application of artificial intelligence giving machines access to data and letting them learn for themselves—the biopharmaceutical researchers are able to process massive datasets with relative ease. This allows them to quickly locate patterns that aid in the understanding of epilepsy and in the potential effect of clinical decisions, such as a new treatment.
Today, some aspects of a potential compound can be modeled and screened out before ever running the first real-world test, saving time, reducing wasted effort, and optimizing the chances of a medicine’s success.
The science and math involved with developing more effective treatments for epilepsy are leading edge, but to Han-Burgess and his fellow biopharmaceutical researchers, the mission is personal. Prominently featured in the team’s lab is a poster of a local Georgia resident with epilepsy whose personal struggle to control her seizures serves as a constant source of inspiration. “She had her first seizure in a grocery store with her daughter,” Han-Burgess explains. “It took her two and a half years to find an epileptologist [a neurologist who specializes in the treatment of epilepsy] and then another two and a half years to find the right treatment that worked for her.”
Han-Burgess believes that today’s scientific advances in biopharmaceutical research will one day eliminate the five-year wait experienced by the Georgia patient, creating a future where people with epilepsy—and a host of other heterogenous conditions—get the right medicine the first time.
Learn more about biopharmaceutical innovation, including treating seizures and epilepsy.
