Next week, 40 of America’s future scientists will head to Washington, D.C. to compete in the finals of the Intel Science Talent Search, a competition often referred to as the “junior Nobel Prize.” They will present the results of their original research projects–a number of which involved the use of Mathematica. Last year, as a senior at Stuyvesant High School, then-17-year-old Varun Narendra was one of those 40 students.

Narendra used Mathematica to create a model that could help treat Gaucher’s disease, a genetic disorder. Patients with Gaucher’s disease need enzyme replacement therapy to properly metabolize fat cells. The therapy is effective in most cases, but it is not a cure. Because the cost of the lifelong treatments can exceed $300,000 per year, Narendra wanted to find a way to determine each person’s optimal enzyme dosage.

Narendra learned to use Mathematica during an after-school program offered to Stuyvesant High School students by Hunter College in New York City. Although the class focused on Mathematica as a computational tool rather than a programming language, Narendra says, “Just from the class, I was able to get a general enough idea of the language so that I could apply it to my work.”

Gaucher’s disease is caused by a mutation in the enzyme that stores fat cells, or glycolipids. This mutation reduces the activity of the enzyme, causing the glycolipids to accumulate in the patients’ macrophage cells, which are a type of white blood cell. When the macrophage cells become engorged, they are called Gaucher cells. In Type 1 Gaucher’s disease, which Narendra studied, Gaucher cells accumulate in body tissues, particularly the spleen, where they cause painful swelling. The spleen irritation can lead to further complications such as swelling of liver and joint tissues, compression of the lungs, bone abnormalities, and anemia. Enzyme replacement therapy works by increasing the amount of enzyme available to metabolize glycolipids. This helps prevent the glycolipids from accumulating in and damaging body tissues.

Narendra analyzed 225 blood samples by studying enzyme activity levels. He allowed the enzyme to react with patient blood serum tagged with fluorescent markers. When the enzyme reacts with the blood serum, the fluorescent markers are separated from the cells. After allowing the reaction to continue for a specific amount of time, Narendra used a fluorometer to measure the amount of released fluorescence. This told him how much of the enzyme was needed to complete the reaction.

By varying the amount of enzyme combined with each patient’s blood sample, with Mathematica Narendra was able to develop a mathematical representation of every relevant reaction occurring within the blood cells. He modeled the reactions in the cells over time by coding loops in his program. Says Narendra, “By studying how the glycolipid levels change over time with varying treatment plans, you get an idea of what plan is most cost-effective.”

Now attending Harvard University, Narendra is planning to major in astronomy and astrophysics. He is seeking research opportunities on campus, saying “I hope to eventually get back into doing work with Gaucher, yet I would also like to explore other interests.”