My UMSOP Story: Mathangi Gopalakrishnan, PhD, MS, assistant professor

Written By: Randolph Fillmore

Mathangi Gopalakrishnan, PhD, MS, an assistant professor in the School of Pharmacy’s Department of Practice, Sciences, and Health Outcomes Research and a member of its Center for Translational Medicine, tells an interesting story about her career path. As with many successful people, she followed her interests and passions and always seemed to be in the right place at the right time — perhaps even when she didn’t realize it.

“Following the advice of one of my teachers, and with support from my parents, I joined the pharmacy program at the Birla Institute of Technology and Science in Pilani, Rajasthan, India,” she recalls. “I became very interested in pharmacokinetics and pharmacology and received my bachelor’s and master’s degrees in pharmacy in the late 1990s.”

Gopalakrishnan then accompanied her husband, Atul, to the United States where he entered a postdoctoral program at the University of Florida, Gainesville. Eventually the couple moved to Maryland where her husband went on to work at the U.S. Food and Drug Administration.

While in Maryland, and by chance, Gopalakrishnan had an opportunity to work informally on research projects related to pharmacometrics.

“That work really opened my eyes,” she recalls. “As a result, I realized that fundamental statistical knowledge was essential for pharmacometrics.”

With encouragement all around her, she enrolled at the University of Maryland, Baltimore County where she earned both a master’s degree (2007) and a PhD (2013) in statistics.

A faculty member at the School of Pharmacy since 2013, Gopalakrishnan has worked on several quantitative translational research projects and has contributed to the growth of the MS in Pharmacometrics program since its inception. She is now director of the program.

Bringing expertise in both pharmacy and statistics to a wide range of research, she has authored and co-authored numerous papers using statistical and pharmacometric methods.

In a recently published study, she and her colleagues used pharmacometric and statistical methods to reassess unfractionated heparin dosing for pediatric patients by modeling the pharmacokinetic and pharmacodynamic relationship to identify dose-escalating schemes that can achieve therapeutic targets sooner.

“Questions regarding optimal dosing are important,” she explains. “Forecasting with data can help us find optimal dosing and aid in making clinical decisions.”

Gopalakrishnan and her colleagues also recently investigated how “machine learning” can be used in pharmacometrics. Machine learning, a branch of artificial intelligence and computer science, uses data and algorithms to discover patterns and also imitate how humans learn.

The researchers used this machine learning to identify placebo responders to better inform the inclusion/exclusion criteria for clinical trials and increase the success of binge eating disorder studies as placebo responders had previously represented a high percentage of response.

“We designed algorithms that identified placebo responders with 88 percent sensitivity and 72 percent accuracy, thereby more accurately targeting participants who responded to treatment rather than placebo,” explains Gopalakrishnan.

Outside of work, Gopalakrishnan loves to travel with her family. And, like their parents, her daughters, Nandini, 17, and Vaishnavi, 14, are big fans of the National Football League. The girls like the New England Patriots while mother and father are partial to the Washington Commanders, though they all enjoy attending Baltimore Ravens games.

“I also love cooking,” she says. “I do some of my best thinking about research while I am cooking.”