Myreen Ahsan (8th Grade, Friendswood Junior High)
National competition in Washington
An eighth-grade student from Texas has used artificial intelligence and computer models to screen more than 10 million drug-like molecules in search of possible treatments for frontotemporal dementia. The project earned Ahsan a place as one of 30 national finalists in the 2026 Thermo Fisher Scientific Junior Innovators Challenge, a major science and engineering competition for American middle school students run by Society for Science. Through several filtering steps, her computer-based process reduced the original library of more than 10 million possible molecules to a small group of promising small-molecule candidates. ” Ahsan’s selection among the top 30 finalists in the Thermo Fisher Scientific Junior Innovators Challenge followed a nationwide process that began with thousands of middle school students taking part in local and regional science fairs. After being nominated through the Science and Engineering Fair of Houston, Ahsan was named to the top 300 shortlist announced by Society for Science. She later secured a place among the 30 national finalists. Each finalist receives a $500 cash prize. The top awards at the national competition include more than $100,000 in educational scholarships and prizes.
Where Ahsan had previously competed, her approach focused on finding small molecules that could potentially work through two different mechanisms, according to research summaries released by the Science and Engineering Fair of Houston.
Ahsan named her research project “Millions to Molecules: Dual Mechanism Small-Molecule Discovery via HTVS and Machine Learning-Guided Molecular Dynamics for Frontotemporal Dementia”. “To see a young person so deeply engaged with cutting-edge topics demonstrates the extraordinary potential of the next generation,” Jiang said. Myreen Ahsan, a student at Friendswood Junior High in Friendswood, Texas, carried out the computer-based study as part of an independent research project on neurodegenerative diseases. Her project examined large chemical databases to find compounds that could interact with specific biological targets linked to the condition. Frontotemporal dementia is a group of brain disorders that mainly affect the frontal and temporal parts of the brain. The condition can cause changes in behaviour, language, and the ability to plan and make decisions. Effective treatments that can slow or change the course of the disease remain limited, leading researchers to explore new ways to discover drugs. The study used high-throughput virtual screening (HTVS), a computer-based method that allows scientists to test large collections of chemical structures against biological targets digitally. This can reduce the time and cost involved in physically testing millions of substances in laboratories. Ahsan combined virtual screening with machine learning models and molecular dynamics simulations. This approach allowed her to study how strongly potential drug molecules might bind to target proteins and how stable those interactions could remain over time. The goal was to address more than one disease-related process at the same time. Xiaoqian Jiang, chair of the Department of Health Data Science and AI at UTHealth Houston, praised Ahsan’s interest in advanced medical technology after one of her research presentations. “Her work not only reflects a strong understanding of artificial intelligence in biomedical sciences but also showcases her curiosity and commitment to learning. As a finalist, Ahsan will travel to Washington, DC, for the competition’s Finals Week. During the event, students will present their individual projects and take part in team-based problem-solving challenges judged by panels of scientists and engineers. The finalists are scheduled to present their completed research projects to judges and the public during the Washington event in late October.