Virginia teen uses AI and CRISPR to boost biofuel from microalgae
Fourteen-year-old Millie Pradawong has developed an AI-powered computational tool that predicts how CRISPR gene editing could improve microalgae for biofuel production. Her project, MACRO, aims to increase oil production without reducing algae growth. A finalist in the 2026 3M Young Scientist Challenge, Millie hopes her work will support future research in clean energy and biotechnology.
A 14-year-old U.S. teen named Millie Pradawong has created a computational tool using machine learning and CRISPR gene editing to enhance biofuel production from microalgae. This project, called MACRO (Machine Learning-Augmented CRISPR Reprogramming Optimisation), predicts how gene editing could affect the energy usage of microalgae, aiming to boost oil production while preserving the algae's healthy growth.
Microalgae are rapid-growing organisms that absorb carbon dioxide and naturally produce oil, making them a potential source of sustainable energy. However, increasing oil production often hinders algae growth, posing a challenge to large-scale biofuel production. Millie chose this project as she aimed to transform an idea she had long harbored into a more substantial and impactful endeavor.
Her fascination with microalgae biofuel stems from its potential and the complexity of creating a practical biofuel system. By combining machine learning with CRISPR's gene-editing capabilities, Millie's tool can forecast successful genetic modifications, thereby accelerating the discovery process in the lab. The 14-year-old credits CRISPR, an invention she considers among the most significant of the past century, for changing how scientists interact with DNA.
Originally viewed as mere information, Millie now sees DNA as a substance that can be precisely manipulated. Aspiring to become a physician scientist, Millie envisions a future where her work seamlessly integrates medical practice with scientific research, bridging the gap between patient care and innovative solutions to complex problems.
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