This project aims to develop a predicted reaction network using experimental and computational data generated by the work to describe the environmental lifecycle of persistent biological…

Carnegie Mellon University received a $157,667 Project Grant from the Environmental Protection Agency (EPA) Office of Research and Development under the Science to Achieve Results (STAR) Research Program (CFDA 66.509), awarded March 1, 2025, with a completion date of May 1, 2025. The award funds development of a predicted reaction network to characterize the environmental lifecycle of persistent biological transformation products of chemicals. Carnegie Mellon will integrate new approach methodologies with experimental and computational data using CloudLab infrastructure and machine learning techniques to identify critical and stable biological transformation products and assess environmental fate and bioaccumulation potential of transformed chemicals at different lifecycle stages.

The primary deliverable is a predictive tool designed to evaluate the sustainability of alternative chemical products and identify potential biological transformation products of concern. The tool will leverage open-access chemical databases and user-friendly web interfaces to provide actionable information for multiple stakeholder groups, including the chemicals and waste management industries, environmental and public health decision-makers, and communities affected by environmental pollution. No subawards are included in this assistance agreement, and all work will be performed at Carnegie Mellon's Pittsburgh, Pennsylvania location.

This project aims to develop a predicted reaction network using experimental and computational data generated by the work to describe the environmental lifecycle of persistent biological transformation products (TP) of chemicals. The purpose of this award is to improve the chemical products manufacturing industry and improve understanding of biological transformation products and how chemicals act at different stages of their lifecycle.activities:the activities to be performed in this project will integrate new approach methodologies and supplement experimental data with computational techniques leveraging carnegie mellon's cloudlab and machine learning methods. Using these processes, the projects will select critical and stable biological transformation products and develop reaction network to better assess the environmental fate and bioaccumulation potential of transformed chemicals or chemical products at different stages of their lifecycles. Subrecipient:no subawards are included in this assistance agreement.outcomes:the project will utilize experimental and computational data to develop predicted reaction networks for chemical products, and their subsequent biological transformation products. The work seeks to utilize existing chemical alternatives that do not result in harmful or environmental accumulative biological transformation products. This information can be leveraged for use in open-access chemical databases and user-friendly web tools. Anticipated deliverable of this project is a predictive tool that will evaluate the sustainability of alternative chemical products and identify potential biological transformation products of concern relevant to that chemical product. The intended beneficiaries of this project include chemicals industry, waste management industry, the general public, public and environmental health decision makers, and communities affected by environmental pollution.