Student researcher Lynijah Russell is designing virtual environments that act and react like human organs in order to simulate diseases and treatments. Now a sophomore at St. Mary’s College of Maryland, Russell says her love for science was jump-started at the University of Maryland, Baltimore (UMB), where she participated in the UMB CURE Scholars Program.
“So, I started with UMB when I was in sixth grade and that gave me a big advantage, I'd say, when it comes to science and medicine,” Russell says. CURE scholars work directly with student and faculty mentors, spending weekends and many evenings in hands-on learning spanning the health sciences.
Soon after enrolling at St. Mary’s, though, Russell discovered a new academic love: computer science. Her aptitude with computers, coupled with her solid grounding in health sciences, made Russell a perfect candidate for summer study and research performing computational analysis at the Institute for Genome Sciences at the University of Maryland School of Medicine.
Her goal has been to test biological interactions in a simulated environment to advance prospects for early diagnosis of pancreatic cancer.
“In 2025, it is predicted that 67,000 people are going to be diagnosed with pancreatic cancer and 80 percent of those people are expected to die this year. What if a computer program, a simulation, could lessen that number drastically?” Russell asks.
Working with simulation software PhysiCell, she soon found the processes intolerably slow. So, Russell did what any talented computer scientist would. She taught herself an advanced programming language called Python and used it to modify and greatly speed up the PhysiCell process.
“These simulations allow us to accurately grow tumors in a computer so that we're able to model them faster than we would in an incubator. So, usually when you have a tissue sample it takes about five days to grow. We can grow it in two minutes,” she says.
Speed is critical, Russell adds, because diagnostic tools like CT and MRI scans generally only spot pancreatic cancer in stage 3 or 4, when it is often untreatable.
“This simulation would allow us to sometimes even backtrack so we can compare what our simulation looked like in the beginning stages to what tissue should look like in the beginning stages, and now we have an idea what to look for,” she says. “And we can make therapies to tackle it sooner and faster and save a lot more people's lives.”