MIT-led team receives funding to develop next-generation alternatives to modern weed killers

What happened

A team led by MIT has received up to $53 million from the U.S. Advanced Research Projects Agency for Health (ARPA-H) to develop new herbicides using generative AI. The project, called Precision Learning for On-target Weed control (PLOW), brings together researchers from several universities and organizations. Their goal is to find alternatives to current weed killers like glyphosate, which are facing problems with weed resistance and health concerns. The research will also look at ways to reduce reliance on imported ingredients and minimize environmental and human exposure to harmful chemicals.

Key details

• Funding amount: up to $53 million from ARPA-H under the STREAM program.
• Project name: Precision Learning for On-target Weed control (PLOW).
• Participating institutions include MIT, Broad Institute, University of North Carolina at Chapel Hill, University of Tennessee at Knoxville, University of Illinois at Urbana-Champaign, and Robigo.
• Generative AI models will be used to design molecules that target plant enzymes and reduce the risk of resistance and health impacts.
• First greenhouse tests of new candidates are expected by the end of the first year.

Why it matters

Farmers, agricultural workers, and consumers are affected by this project because it aims to provide safer and more effective weed control options. The effort could reduce health risks linked to exposure from current herbicides and address the problem of weeds becoming resistant to existing chemicals. The project also seeks to strengthen the supply chain by reducing dependence on imported ingredients used in major herbicides.