Natalia Sizochenko studies nanomaterials, pesticides, and antibiotic resistance, all with computational tools.
A native of Ukraine, she has explored the toxicity of tiny substances present in drugs, food, and other consumer products like cosmetics. Her approach merges techniques of quantum chemistry with algorithms of machine learning to develop predictive toxicological models — and avoid testing nanomaterials in animals.
“The more I learned, the more I was aware that, OK, computational techniques could fully support experimental studies,” she said.
At Dartmouth, Sizochenko is applying computation techniques to battle antibiotic resistance in people infected with Staphylococcus aureus, a serious problem as our arsenal of small-molecule antibiotics are losing their potency against this bacteria and others. Through computer modeling, she is designing drugs based on enzymes, which are predicted to be as effective as traditional antibiotics but also safer for people. And no animals are involved.
Throughout her career, she has consistently shared her love of science with others.
“The more I learned, the more I was aware that, OK, computational techniques could fully support experimental studies.”
That can mean writing letters to middle-schoolers in a program where scientists and students are paired as pen pals as well as working with high school and college students from communities underrepresented in science.
“I primarily mentor female students and immigrant students so they feel more welcome and secure,” she said.
— STAT Staff
