Identifying Endocrine-Disrupting Plastic Additives using Machine Learning
NIEHS - National Institute of Environmental Health Sciences
About This Grant
ABSTRACT Plastic additives are widely used in consumer products, yet thousands of plastic additives remain uncharacterized for their potential to disrupt endocrine function - posing significant public health risks. This project aims to develop an integrated computational (Aim 1) and experimental (Aim 2) workflow to systematically predict and validate the endocrine-disrupting potential of plastic additives. In Aim 1, we will design novel machine learning models trained on publicly available datasets to predict AR and ERα modulating activity of plastic additives and then used to predict the potential effects of all plastic additives to select the most promising based on novelty and predictive uncertainty for further in vitro and in vivo testing. In Aim 2, we will validate our predictions through a multi-step experimental characterization approach using our in-house AR and ERα assays, followed by dose-response studies in AR- and ERα-responsive cell lines to measure target gene activation and cell proliferation. The top three plastic additives with the strongest in vitro effects will be further evaluated in vivo using mice to assess systemic hormonal changes caused by the plastic additives. This work will have a substantial positive societal impact by establishing a first-in-kind machine learning-assisted predictive toxicological model to pinpoint plastic additives of highest concern to induce adverse health effects as well as generate a large dataset of plastic additive effects on endocrine function. Taken together, this work can serve to provide policy guidance on plastic additives to ban or remove from products, with potentially beneficial health outcomes for billions of consumers.
Grant Summary
Identifying Endocrine-Disrupting Plastic Additives using Machine Learning is a NIEHS - National Institute of Environmental Health Sciences grant providing up to $444K for university, nonprofit, healthcare org. Applications are due 2028-02-16 (open). Check eligibility and apply with FindGrants.
Focus Areas
Eligibility
How to Apply
Up to $444K
2028-02-16
- 1Confirm your organization is eligible for Identifying Endocrine-Disrupting Plastic Additives using Machine Learning from NIEHS - National Institute of Environmental Health Sciences, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NIEHS - National Institute of Environmental Health Sciences before the deadline.
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Identifying Endocrine-Disrupting Plastic Additives using Machine Learning: Frequently Asked Questions
Who is eligible for the Identifying Endocrine-Disrupting Plastic Additives using Machine Learning?
Identifying Endocrine-Disrupting Plastic Additives using Machine Learning is offered by NIEHS - National Institute of Environmental Health Sciences and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the Identifying Endocrine-Disrupting Plastic Additives using Machine Learning provide?
Identifying Endocrine-Disrupting Plastic Additives using Machine Learning provides up to $444K per award from NIEHS - National Institute of Environmental Health Sciences. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the Identifying Endocrine-Disrupting Plastic Additives using Machine Learning deadline?
Applications for Identifying Endocrine-Disrupting Plastic Additives using Machine Learning are due 2028-02-16 (open). Because deadlines can change, verify the date with the funder, NIEHS - National Institute of Environmental Health Sciences, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the Identifying Endocrine-Disrupting Plastic Additives using Machine Learning?
To apply for Identifying Endocrine-Disrupting Plastic Additives using Machine Learning, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NIEHS - National Institute of Environmental Health Sciences.