For as long as she could remember, Soumya Kulkarni wanted to be a doctor. But during her sophomore year at the University of Michigan, she discovered a new passion.
That year, Kulkarni led a research project investigating how the brain keeps blood pressure and blood glucose levels in check. She had always been interested in the brain, but her time in the lab sparked a curiosity for experimentation.
“I realized that I can’t really picture a future for myself where I’m not doing both research and [medical] science,” she said.
Kulkarni is getting the best of both worlds as a first-year student in the Medical Scientist Training Program at UT Southwestern Medical Center. The program allows students like Kulkarni to pursue both medicine and research, graduating with an M.D. from UT Southwestern Medical School and a Ph.D. from UT Southwestern Graduate School of Biomedical Sciences in seven to eight years.
The program received a $50 million donation from the Perot family in November that will allow it to accept more students and expand its research opportunities in computational biology, data science and more. Dr. Andrew Zinn, an alum of the program and its current director, said computer science can greatly benefit doctors and researchers.
“I think it’s going to transform medicine,” Zinn said.
Two degrees in one
Formally called the Perot Family Scholars Medical Scientist Training Program, UTSW’s program is one of 54 across the U.S. that is supported by the National Institutes of Health. It admits 10 to 12 students a year who undergo two years of medical training, complete their graduate research and then finish two last years of medical school.
The skills students gain from each degree are transferable, Zinn said. Students who want to treat cancer patients, for example, might focus their graduate research on cancer cells, gaining an in-depth understanding of how the disease develops.
On the other hand, students with different interests in research and medicine still gain valuable experience, improving patients’ lives in the short term and conducting research that may lead to medical advancements down the line.
“When you’re working in the laboratory, discoveries can take months to years,” Zinn said. “When you’re in the clinic, taking care of a patient, you can improve somebody’s health in hours to days.”
Tech in medicine
The Perot family’s donation will allow the program to accept more students who want to pursue research in fields like computational biology and data science.
Technology and computer science are starting to play larger roles in medicine, Zinn said. People can track their steps and heart rate on their phones, and scientists are using artificial intelligence to understand processes too complicated for traditional statistics — for example, the trillions of connections between brain cells.
Cooper Mellema, a seventh-year student in the program, recently completed his graduate research in computational biology. Mellema studied Parkinson’s disease, a brain disorder that affects movement. His advisor was Albert Montillo, a professor in UTSW’s bioinformatics department.
Mellema considered how different brain areas might vary their signals to each other in Parkinson’s patients, aiming to predict how severe their Parkinson’s might get over the next one to two years.
“We know the entire brain is affected, but we don’t know which specific pieces of the brain being affected will lead to worse outcomes,” he said.
Using fMRI data from Parkinson’s patients — essentially 3D movies of their brains — Mellema calculated how often different brain areas communicated with each other. He then created a model using machine learning to predict which of those connections were important in determining a person’s Parkinson’s progression over the next few years.
Computer programs, he said, can help sift through large amounts of data, teasing out patterns that humans might not know to look for.
“If we have 10,000 pieces of data per subject, and 100 subjects, we don’t know ahead of time which of those 10,000 pieces of data for that subject are important,” Mellema said. “These machine learning models are particularly adept at selecting out which of these pieces might be important for making this prediction.”
A long-term commitment
It can be daunting to commit to the program, particularly for first-year students like Kulkarni.
“Sometimes you get caught up in being like, ‘Oh my gosh, I’m going to be here until 2030,’” she said. “And it can be intimidating when you look at it from the perspective of how much training you have to do.”
James Elder, a fifth-year student in the program, said the program demands endurance. He said the initial transition from two years of medical training to the graduate degree can feel like “going back to scratch.”
“After the first year of medical school … you hold on to a lot of clinical knowledge,” he said. “Then, you start in the Ph.D. program where a lot of that certainly isn’t relevant day to day, and so you have to readjust your thinking of what knowledge you’re accessing.”
Due to the COVID-19 pandemic, Elder went through the transition virtually. He said it was difficult settling in without in-person classes or lab sessions, but faculty members and his peers helped him through it. Since the program accepts only around 10 to 12 students per class year, the cohort gets close, bonding over shared experience.
“These are people who are going to be with you, largely every step of the way, for years,” Elder said.
After graduation, most students complete a medical residency. Many look for “research residencies” that allow them to pursue research alongside their clinical training.
Once Elder graduates, he said he hopes to pursue a residency in psychiatry where he could also pursue his interests in computational research. Mellema wants to work in an Intensive Care Unit, delivering life-saving treatment and using machine learning to analyze whether data like heart rate and brain activity provide early signs of a patient’s condition.
In a few cases, students transition directly to research positions or to jobs in biotech or pharmaceutical industries.
The program attracts a wide range of minds: future doctors, aspiring researchers and a blend of both. Its length and rigor are not for everyone. But for students like Kulkarni, Elder and Mellema, it can be the perfect fit.
Adithi Ramakrishnan is a science reporting fellow at The Dallas Morning News. Her fellowship is supported by the University of Texas at Dallas. The News makes all editorial decisions.
