Opportunity Information: Apply for EPA G2010 STAR C3
Apply for EPA G2010 STAR C3
- The Environmental Protection Agency in the environment sector is offering a public funding opportunity titled "Computational Toxicology Biologically Based Multi Scale Modeling" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 66.509 Science To Achieve Results (STAR) Research Program.
- This funding opportunity was created on Apr 15, 2010 and posted on Apr 15, 2010.
- Applicants must submit their applications by Jul 15, 2010 Please refer to the full announcement, including Section IV for additional information on submission methods and due dates.. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $3,000,000.00 to eligible and selected applicants.
- Each selected applicant is eligible to receive up to $750,000.00 in funding.
- The number of recipients for this funding is limited to 4 candidate(s).
- Eligible applicants include: Native American tribal governments (Federally recognized) State governments City or township governments County governments Others (see text field entitled Additional Information on Eligibility for clarification) Public and State controlled institutions of higher education Private institutions of higher education.
- See Section III of the announcement for additional eligibility information.
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Opportunity Summary:
The Environmental Protection Agency (EPA) announced this Science to Achieve Results (STAR) research opportunity to push forward computational toxicology methods that can better connect environmental exposures to biological effects in a rigorous, quantitative way. The core focus is on building biologically based, multi-scale models that describe dose-response relationships and explain how an environmental agent interacts with toxicity pathways, starting at lower levels such as molecular or cellular events and linking those effects upward through tissues, organs, and whole-organism outcomes. In practical terms, the EPA was looking for projects that go beyond simple correlation and instead produce models that are mechanistic or biologically grounded enough to improve how scientists and risk assessors predict toxicity from exposure and interpret what a measured biological change actually means for health outcomes.
A second major emphasis of the solicitation is the data foundation behind these models. Because multi-scale modeling depends on pulling together diverse datasets (for example, high-throughput screening results, omics data, pathway information, and in vivo or epidemiological findings), the EPA explicitly called for research on how those underlying data can be managed, organized, documented, and shared so they are easier for other researchers and risk assessors to access and reuse. That means attention not only to model development, but also to practical solutions for data standards, metadata, curation approaches, and sharing mechanisms that reduce barriers to interpretation and enable broader community use. The overall intent is to make these modeling and data systems more interoperable and transparent so that outputs can more readily support environmental decision-making and risk assessment.
Administratively, this was a discretionary funding opportunity offered as grants and cooperative agreements under CFDA 66.509 (Science to Achieve Results (STAR) Research Program). EPA anticipated making about four awards, with an estimated total program funding level of $3,000,000 and a maximum award size (ceiling) of $750,000. There was no cost sharing or matching requirement listed. The opportunity was posted on April 15, 2010, with an application deadline (closing date) of July 15, 2010, and it was archived on August 14, 2010.
Eligible applicants included federally recognized Native American tribal governments, state governments, and local governments such as cities/townships and counties, along with public/state-controlled institutions of higher education and private institutions of higher education. The announcement also indicated that other entities might be eligible depending on the detailed eligibility language in Section III of the full solicitation, which applicants were expected to consult for any additional restrictions or clarifications. For those who could not access the full announcement electronically, the contact listed was Pasky Pascual at 202-343-9710.
Frequently Asked Questions (FAQs)
What is this EPA STAR funding opportunity about?
This Environmental Protection Agency (EPA) Science to Achieve Results (STAR) research opportunity focuses on advancing computational toxicology methods that connect environmental exposures to biological effects in a rigorous, quantitative way. The goal is to improve how toxicity is predicted from exposure and how measured biological changes are interpreted for potential health outcomes.
What kinds of research approaches is EPA emphasizing?
The solicitation emphasizes biologically based, multi-scale modeling. Projects are expected to develop models that describe dose-response relationships and explain how an environmental agent interacts with toxicity pathways, starting from lower-level biological events (such as molecular or cellular changes) and linking those effects up through tissues, organs, and whole-organism outcomes.
What does "multi-scale" mean in this context?
Multi-scale refers to linking biological effects across different levels of biological organization. For example, a model might begin with molecular or cellular events and then connect those to tissue-level changes, organ-level impacts, and ultimately outcomes observed at the whole-organism level.
Does the opportunity prioritize mechanistic models over correlations?
Yes. EPA was looking for projects that go beyond simple correlation and instead produce mechanistic or biologically grounded models. The intent is to create models that are strong enough to support improved toxicity prediction from exposure and clearer interpretation of biological changes in terms of health outcomes.
What is meant by "dose-response" in the solicitation?
Dose-response refers to the relationship between the amount of exposure to an environmental agent and the resulting biological effect. The opportunity calls for models that can quantitatively describe and explain these relationships in a biologically based way.
How does "toxicity pathways" fit into the research focus?
The solicitation highlights explaining how an environmental agent interacts with toxicity pathways. In practice, that means linking exposures to the biological pathways involved in toxicity, starting at early biological events and connecting them to higher-level outcomes.
Is data management part of what EPA wants funded?
Yes. A major emphasis is the data foundation needed for multi-scale modeling. EPA explicitly called for research on how underlying data can be managed, organized, documented, and shared to improve access and reuse by other researchers and risk assessors.
What types of data are implied as relevant for these models?
The solicitation describes pulling together diverse datasets, including examples such as high-throughput screening results, omics data, pathway information, and in vivo or epidemiological findings.
What kinds of data-related solutions does EPA mention?
The opportunity points to practical solutions such as data standards, metadata, curation approaches, and sharing mechanisms. The intent is to reduce barriers to interpretation and enable broader community use of the modeling and data systems.
Why does EPA emphasize interoperability and transparency?
The overall intent is to make modeling and data systems more interoperable and transparent so outputs can more readily support environmental decision-making and risk assessment.
What type of funding mechanism is being used?
This is a discretionary funding opportunity offered as grants and cooperative agreements under CFDA 66.509, the Science to Achieve Results (STAR) Research Program.
How many awards did EPA expect to make?
EPA anticipated making about four awards under this opportunity.
What was the total estimated funding level for the program?
The estimated total program funding level was $3,000,000.
What is the maximum award amount?
The maximum award size (ceiling) listed was $750,000.
Is there a cost-sharing or matching requirement?
No cost sharing or matching requirement was listed in the information provided.
When was the opportunity posted and when was it due?
The opportunity was posted on April 15, 2010, and the application deadline (closing date) was July 15, 2010.
Is the opportunity still open?
No. The opportunity was archived on August 14, 2010.
Who was eligible to apply based on the announcement summary?
Eligible applicants included federally recognized Native American tribal governments, state governments, and local governments (such as cities/townships and counties), along with public/state-controlled institutions of higher education and private institutions of higher education.
Could other organizations be eligible too?
The announcement indicated that other entities might be eligible depending on the detailed eligibility language in Section III of the full solicitation. Applicants were expected to consult the full solicitation for additional restrictions or clarifications.
What should applicants do if they need the detailed eligibility rules?
The summary points applicants to Section III of the full solicitation for detailed eligibility language and any additional restrictions or clarifications.
Who is the contact if the full announcement could not be accessed electronically?
The listed contact was Pasky Pascual at 202-343-9710 for those who could not access the full announcement electronically.
What is the CFDA number associated with this opportunity?
The opportunity is under CFDA 66.509, the Science to Achieve Results (STAR) Research Program.
How does this research relate to risk assessment and decision-making?
The intent is for biologically based models and improved data systems to make outputs more usable in environmental decision-making and risk assessment, including better prediction of toxicity from exposure and better interpretation of biological measurements for health outcomes.
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