This 12-year-old is trying to solve one of the biggest problems with taking new medications
Lydia Ramsey
Courtesy Sofia Tomov
When taking a new medication, it's often hard to know if you're going to have a side effect, like nausea or a rash.
And sometimes, these side effects can be a big deal, sometimes even deadly.
That's what seventh-grader Sofia Tomov wants to keep from happening.
Tomov is one of the 10 Discovery Education 3M Young Scientist Challenge finalists for her work with computer algorithms that could pick out people who might not respond well to certain medications.
The competition is for kids in Grades 5 to 8 across the US, with a $25,000 grand prize. This year's finalists have developed everything from biodegradable plastic to energy sources powered by microbes.
Tomov told Business Insider that she was inspired to take on the project after watching pharmaceutical-drug commercials with their long lists of side effects listed at the end. When she looked into it more, she was surprised to find out that negative reactions from taking drugs is considered the fourth-leading cause of death in the US.
That got her thinking about why people might respond differently to certain drugs, and wondering how frequently variations in our genetic makeup might be at fault for the bad reaction.
Her invention
Scientists have determined that there are genetic mutations that are associated with negative reactions for particular drugs.
"However, knowing the mutation only solves half the problem," Tomov explains in a video outlining her project. "Doctors need to know if their patients have particular mutations. They need to find one mutation in a genome of billions bases."
So Tomov went out to find a computer algorithm that would help her sort through genetic code. She settled on one called the Apostolico-Giancarlo algorithm, which she put on multiple processors.
Sofia Tomov/YouTube
Tomov said the hardest part of the project was building out the code for the algorithm. Her next goal is to keep working on this process to make it even faster at determining whether a person has the genetic mutation. She's especially interested in computer science and has been taking online classes to learn more.
http://www.businessinsider.com/3m-y...al&utm_source=twitter.com&utm_campaign=buffer
Lydia Ramsey
- Aug. 4, 2016, 11:52 AM
When taking a new medication, it's often hard to know if you're going to have a side effect, like nausea or a rash.
And sometimes, these side effects can be a big deal, sometimes even deadly.
That's what seventh-grader Sofia Tomov wants to keep from happening.
Tomov is one of the 10 Discovery Education 3M Young Scientist Challenge finalists for her work with computer algorithms that could pick out people who might not respond well to certain medications.
The competition is for kids in Grades 5 to 8 across the US, with a $25,000 grand prize. This year's finalists have developed everything from biodegradable plastic to energy sources powered by microbes.
Tomov told Business Insider that she was inspired to take on the project after watching pharmaceutical-drug commercials with their long lists of side effects listed at the end. When she looked into it more, she was surprised to find out that negative reactions from taking drugs is considered the fourth-leading cause of death in the US.
That got her thinking about why people might respond differently to certain drugs, and wondering how frequently variations in our genetic makeup might be at fault for the bad reaction.
Her invention
Scientists have determined that there are genetic mutations that are associated with negative reactions for particular drugs.
"However, knowing the mutation only solves half the problem," Tomov explains in a video outlining her project. "Doctors need to know if their patients have particular mutations. They need to find one mutation in a genome of billions bases."
So Tomov went out to find a computer algorithm that would help her sort through genetic code. She settled on one called the Apostolico-Giancarlo algorithm, which she put on multiple processors.
Sofia Tomov/YouTube
Tomov said the hardest part of the project was building out the code for the algorithm. Her next goal is to keep working on this process to make it even faster at determining whether a person has the genetic mutation. She's especially interested in computer science and has been taking online classes to learn more.
http://www.businessinsider.com/3m-y...al&utm_source=twitter.com&utm_campaign=buffer
