Grantee Research Project Results
U.S. Environmental Protection Agency
Office of Research and Development
National Center for Environmental Research
Science to Achieve Results (STAR) Program
Computational Toxicology: Biologically-Based Multi-Scale Modeling
CLOSED: FOR REFERENCE PURPOSES ONLY
This is the initial announcement of this funding opportunity.
Funding Opportunity Number:
| Model Development and Evaluation for Computational Toxicology | EPA-G2010-STAR-C1 |
| Data Management for Computational Toxicology | EPA-G2010-STAR-C2 |
| Early Career Projects: Model Development and Evaluation for Computational Toxicology | EPA-G2010-STAR-C3 |
| Early Career Projects: Data Management for Computational Toxicology | EPA-G2010-STAR-C4 |
Catalog of Federal Domestic Assistance (CFDA) Number: 66.509
Solicitation Opening Date: April 15, 2010
Solicitation Closing Date: July 15, 2010: 11:59:59 pm Eastern Time
Eligibility Contact: William Stelz (stelz.william@epa.gov); phone: 202-343-9802
Electronic Submissions: Ron Josephson (josephson.ron@epa.gov); phone: 202-343-9643
Technical Contact: Pasky Pascual (pascual.pasky@epa.gov); phone: 202-343-9710
Access Standard STAR Forms (https://www.epa.gov/research-grants/funding-opportunities-how-apply-and-required-forms)
View research awarded under previous solicitations (https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/recipients.archive/)
SUMMARY OF PROGRAM REQUIREMENTS
Synopsis of Program:
The U.S. Environmental Protection Agency (EPA), as part of its Science to Achieve Results (STAR) program, is seeking applications for research in developing quantitative, dose-response models to elucidate the associations between environmental agents and toxicity pathways across multiple scales of biological organization. Additionally, this solicitation calls for research into ways in which the data underlying these models can be managed and shared for easier access, interpretation and use by the broader community of researchers and risk assessors.
Award Information:
Anticipated Type of Award: Grant or cooperative agreement.
Estimated Number of Awards: Approximately four awards, including one early career award.
Anticipated Funding Amount: Approximately $3 million total for all awards.
This solicitation covers two research areas: (1) Model Development and Evaluation for Computational Toxicology and (2) Data Management for Computational Toxicology.
Potential Funding per Award: Up to a total of $750,000, including direct and indirect costs, with a maximum duration of four years.
Cost-sharing is not required. Proposals with budgets exceeding the total award limits will not be considered.
Eligibility Information:
Public nonprofit institutions/organizations (includes public institutions of higher education and hospitals) and private nonprofit institutions/organizations (includes private institutions of higher education and hospitals) located in the U.S., state and local governments, Federally Recognized Indian Tribal Governments, and U.S. territories or possessions are eligible to apply. See full announcement for more details.
Special eligibility criteria apply to the early career project portion of this RFA. See full announcement for more details.
Application Materials:
The necessary forms for submitting a STAR application will be found on the National Center for Environmental Research (NCER) web site, http://epa.govhttps://www.epa.gov/research-grants/funding-opportunities-how-apply-and-required-forms. Electronic submission of your application must be performed by an authorized representative of your organization.
If you do not have the technical capability to utilize the Grants.gov application submission process for this solicitation, call 1-800-490-9194 or send a webmail message to 'Contact Us' at least 15 calendar working days before the submission deadline to assure timely receipt of alternate submission instructions. In your message provide the funding opportunity number and title of the program, specify that you are requesting alternate submission instructions, and provide a telephone number, fax number, and an email address, if available. Alternate instructions will be e-mailed whenever possible. Any applications submitted through alternate submission methods must comply with all the provisions of this Request for Applications (RFA), including Section IV, and be received by the solicitation closing date identified above.
Agency Contacts:
Eligibility Contact: William Stelz (stelz.william@epa.gov); phone: 202-343-9802
Electronic Submissions: Ron Josephson (josephson.ron@epa.gov); phone: 202-343-9643
Technical Contact: Pasky Pascual (pascual.pasky@epa.gov); phone: 202-343-97101
I. FUNDING OPPORTUNITY DESCRIPTION
A. Introduction
The National Research Council of the National Academy of Sciences, in its report, Toxicity Testing in the 21st Century: a Vision and a Strategy, proposed that toxicity testing should become less reliant on apical endpoints from whole animal tests (e.g. cancer incidence, impaired reproduction, and developmental anomalies) and eventually rely instead on quantitative, dose-response models based on information from in vitro assays and in vivo biomarkers, which can be used to screen large numbers of chemicals (NRC, 2007A). This approach to toxicity testing is based on the understanding that traditional endpoints are the ultimate result of a series of cellular and sub-cellular responses to toxic chemicals. As depicted graphically in Figure 1 (taken from US EPA, 2009), toxic chemicals trigger toxicity pathways,1 which trigger a chain of biological events at multiple scales that ultimately lead to adverse human health effects. For this approach to be successful however, it must build on advances in multiple disciplines to extend toxicity testing beyond whole-animal testing towards a more holistic and systematic understanding of human health effects at multiple scales of biological organization—from gene to cell to tissue to organ to the entire human body.
Figure 1. Toxicity pathways across multiple scales of biological organization.
Because of advances in experimental biology, some of the physiological and metabolic changes linking these toxicity pathways with adverse outcomes in humans are now directly observable and measureable through in vivo biomarkers and in vivo or in vitro bioassays. At the same time, advances in quantitative techniques now make it possible to analyze and synthesize data from multiple scales to generate credible and robust inferences about toxicity pathways. Computational toxicology has been defined as the “integration of modern computing and information technology with molecular biology to improve … prioritization of data requirements and risk assessment of chemicals” (Kavlock et al, 2008). This solicitation is intended to spur advances in computational toxicology by calling for research in developing quantitative, dose-response models to elucidate the associations between environmental agents and toxicity pathways across multiple scales of biological organization. Additionally, this solicitation calls for research into ways in which the data underlying these models can be managed and shared for easier access, interpretation and use by the broader community of researchers and risk assessors.
In addition to regular awards, this solicitation includes the opportunity for early career projects. Please see Section III of this RFA for details on the early career eligibility criteria.
- Envisioning the future of toxicity testing and computational toxicology
“Toxicity testing is approaching a scientific pivot point,” states a recent report from the National Research Council (NRC) of the National Academy of Sciences (NRC, 2007A). This pivot point builds on advances in multiple disciplines to extend toxicity testing beyond whole-animal testing towards a more holistic and systematic understanding of human health effects at multiple scales of human biological organization—from gene to cell to tissue to organ to the entire human body. The NRC report noted the limitations of traditional toxicity testing that relies primarily on adverse biologic responses in homogeneous groups of animals exposed to high doses of a test agent. It questioned the relevance of such animal studies for the assessment of risks to heterogeneous human populations exposed at much lower concentrations. It further suggested that traditional toxicity tests are not only expensive and time-consuming, but that they also require large numbers of animals.
The NRC report proposed that toxicity testing should instead take advantage of developments in genomics, cellular biology, bioinformatics and other fields in order to enable risk assessment based upon toxicity pathways, which can be monitored via in vitro and in vivo high throughput screening. Such an approach would accomplish the following objectives:
- Provide broader coverage of chemicals and their mixtures, end points, and life-stage vulnerabilities.
- Reduce the cost and time of testing.
- Use fewer animals and cause minimal suffering to animals that are used.
- Establish a more robust scientific basis for risk assessment by providing more comprehensive mechanistic and dosimetry information and by integrating toxicologic and population-based data.
This solicitation is intended to spur development of quantitative, dose-response models that show how toxic chemicals influence human health at multiple scales of biological organization. It calls for researchers to take data about toxicity pathways across the multiple scales of biological organization shown in Figure 1 and to develop quantitative models that relate toxic endpoints with their causal factors (see Figure 2).
These models could provide several advantages over current approaches to toxicity testing. First, the models could capture the synergistic biological effects of chemical mixtures, thereby approximating actual conditions faced by the public, as opposed to the single chemical paradigm of traditional risk assessments.
Figure 2. Quantitative, dose-response models explain toxic endpoints as a mathematical function of various causal factors.
Secondly, data on toxicity pathways can be collected before the traditional, organism-scale end-points begin to manifest themselves, thereby providing a means to monitor public health before the onset of actual, and perhaps irreversible, physical harm. Third, the models could take advantage of advances in quantitative techniques that can analyze and synthesize data from multiple scales to generate inferences that are credible and robust. For the purposes of this solicitation, it is important to recognize that some of the analytical approaches that enable researchers to combine data across multiple scales (see Ryan, 2008; Gelman and Hill, 2007) can also be used to synthesize data from different studies or investigations.
- Computational toxicology and model evaluation
Even as newer analytical methods facilitate the development of more sophisticated models based on more comprehensive data, the complexities and uncertainties of science continue to plague decisions based on these models. Default assumptions underlying risk assessments must continually be refined and updated in order to incorporate emerging information. Variability in the data and uncertainty in scientific hypotheses must be investigated and explained (NRC, 2008). The emerging consensus regarding models is that there is no such thing as the completely “valid” model; models are not “validated” but “evaluated” (NRC, 2007B).
Under the traditional experimental paradigm, questions about whether a model is supported by the data have been addressed through quantitative techniques that rely on a researcher’s ability to control sources of variability. But these techniques are inadequate for computational toxicology models, which are based on data drawn from multiple scales and multiple studies. For these reasons, this solicitation also focuses on research to evaluate model performance. The research should provide a basis to be able to explain why one model or set of models provide a better indication of the strength of evidence supporting a hypothesis. Additionally, this solicitation also focuses on managing data and model information such that information across multiple investigations can be pooled and synthesized to generate models of greater evidential strength.
- Enhancing computational toxicology through data integration
Before one can integrate data on toxicology pathways from across multiple scales and studies, these data must first be organized in a way that provides the researcher with sufficient information to facilitate the modeling process. For example, measurements taken from bioassays performed according to two different experimental protocols can be integrated into a model only by taking into account the systematic variability generated by the two protocols.
Moreover, advanced approaches to managing scientific data, such as semantic web technologies, now exist that facilitate data management with the following attributes (Berners-Lee and Hendler, 2001): the data can be decentralized and managed in different data repositories; and the data can be seamlessly aggregated in real-time from across multiple sites on the World Wide Web according to formal search syntax. This capability depends on a shared ontology, i.e. a shared understanding of how the data across institutions are related, how they can be structured, and how they can be defined and formatted so that different terminologies for the same concepts or objects might be mapped to each other.
A portion of this solicitation focuses on research to manage computational toxicology data so that the data generated by the multiple investigations funded under this solicitation can eventually be combined and integrated.
Figure 3 depicts the types of analyses that would be facilitated if data were to be managed using semantic web technologies. Newer analytical techniques can be used to synthesize information across multiple models generated by multiple investigations. Such syntheses have two-fold value. First, the syntheses can better approximate reality by combining information that reflects both the common mechanisms and the heterogeneity of the biological system being modeled (Pascual, 2009). Secondly, through such techniques as “value of information” analyses, the syntheses facilitate a more formal evaluation of the future investigations needed to fill research gaps and missing information (Yokota and Thompson, 2004). To be clear: this RFA does not ask for these additional analyses, but only that the data be managed to facilitate future analyses.
Figure 3. Possible analyses if information from each PI is managed appropriately.
- Focus on toxicity pathways involving the liver
The task of integrating data across multiple scales and studies can be a difficult one, particularly when the systems being modeled are completely disparate. In order to facilitate data and model integration across multiple scales and studies, this solicitation focuses on the liver. The liver is highly sensitive to environmental toxicants, whether as the ultimate target organ of disease (see, e.g., Cogliano, 1998) or as a mediator along the toxicity pathway from exposure to the ultimate harmful end-point (O’Farrelly and Doherty, 2007).
The specific Strategic Goal and Objective from the EPA’s Strategic Plan that relate to this solicitation are:
- Goal 4: Healthy Communities and Ecosystems, Objective 4.4: Enhance Science and Research.
The EPA’s Strategic Plan can be found at: https://www.epa.gov/ocfo/plan/2006/entire_report.pdf (PDF) (184 pp, 9.87 MB)
C. Authority and Regulations
The authority for this RFA and resulting awards is contained in the Toxic Substances Control Act, Section 10, 15 U.S.C. 2609; the Federal Insecticide, Fungicide, and Rodenticide Act, Section 20, 7 U.S.C. 136r; the Clean Air Act, Section 103, 42 U.S.C. 7403; the Safe Drinking Water Act, Section 1442, 42 U.S.C. 300j-1; the Clean Water Act, Section 104, 33 U.S.C. 1254; and the Solid Waste Disposal Act, Section 8001, 42 U.S.C. 6981.
For research with an international aspect, the above statutes are supplemented, as appropriate, by the National Environmental Policy Act, Section 102(2)(F).
Applicable regulations include: 40 CFR Part 30 (Uniform Administrative Requirements for Grants and Agreements with Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations), 40 CFR Part 31 (Uniform Administrative Requirements for Grants and Cooperative Agreements to State and Local Governments) and 40 CFR Part 40 (Research and Demonstration Grants). Applicable OMB Circulars include: OMB Circular A-21 (Cost Principles for Educational Institutions) relocated to 2 CFR Part 220, OMB Circular A-87 (Cost Principles for State, Local and Indian Tribal Governments) relocated to 2 CFR Part 225, OMB Circular A-102 (Grants and Cooperative Agreements With State and Local Governments), OMB Circular A-110 (Uniform Administrative Requirements for Grants and Other Agreements with Institutions of Higher Education, Hospitals and Other Non-Profit Organizations) relocated to 2 CFR Part 215, and OMB Circular A-122, (Cost Principles for Non-Profit Organizations) relocated to 2 CFR Part 230.
D. Specific Research Areas of Interest/Expected Outputs and Outcomes
Note to applicant: The term “output” means an environmental activity or effort, and associated work products, related to a specific environmental goal(s), (e.g., testing a new methodology), that will be produced or developed over a period of time under the agreement. The term “outcome” means the result, effect, or consequence that will occur from the above activit(ies) that is related to an environmental, behavioral, or health-related objective.
There are two distinct Research Areas covered by this solicitation: (1) Model Development and Model Evaluation; and (2) Data Management. Applications must propose research in one of these research areas to be eligible for funding. These two areas of research shall be conducted concurrently in the following way: the research team funded under the second research area shall collaborate with the research teams funded under the first research area to ensure that the latter conform their modeling data to a shared ontology.
- Data Analysis, Model Development, and Model Evaluation.
Applications submitted in response to this solicitation must propose developing quantitative, dose-response models that elucidate toxicity pathways in which the human liver manifests an adverse health effect (e.g. liver cancer) and/or provides a mediating role in the human response to toxic chemicals (e.g. the liver’s contribution to innate immune mechanisms). (The focus on the human liver will ease efforts under the second research area to integrate data into a shared ontology.) These models must be based on data drawn from multiple scales of biological organization and must indicate the effect of different dose levels of the toxic chemical(s).
Research responsive to this solicitation may develop models that simulate the sequence of events linking toxicity pathways perturbations by toxic chemicals to the human response, from receptor site to genomic response to cellular modifications to tissue and organ response (including any intracellular/inter-tissue/inter-organ signaling). Of particular interest are models that draw from human data; that address multiple adverse health end-points; that explain toxicity pathways triggered from cumulative exposures to multiple chemicals; and that incorporate the influence of human life stages on toxicity pathways. Also of particular interest are models that are developed using non-proprietary software. Applications may propose targeted testing (either in vivo or in vitro experiments) or collecting data on human biomarkers in order to supplement existing information with new data.
Applications submitted in response to this solicitation must also propose formal model evaluation methods that explain how the researchers will document data provenance, analyze sources of uncertainty and variability, and evaluate alternative model forms (such as alternative probability distributions and parameter values).
Applications submitted in response to this solicitation must indicate that the Principal Investigators funded under this first research area are willing to work with the Principal Investigators funded under the second research area by providing their data and information about their data, excluding confidential or private information.
- Data Management.
Applications submitted in response to this solicitation must propose developing a web-accessible database using semantic web technologies in order to integrate data and meta-information on toxicity pathways on multiple scales of biological organization. Applications should indicate the knowledge and experience of the Principal Investigator(s) with existing ontologies for human systems biology (e.g. Noy, N.F. et al., 2009). Of particular interest are data management schemes that would enable data owners to maintain their data on web sites managed by their respective institutions, while also allowing other researchers to find and to seamlessly access and download these data from these multiple sites using a semantic web-enabled engine.
Research responsive to this solicitation may also describe a data management plan that discusses how the distributed data will be managed throughout their life cycle, including issues related to data ownership/oversight, ongoing care/maintenance, periodic review cycles for data retention/deletion, version and change control, file naming conventions, retention periods, storage, and accessibility/usability/awareness.
Outputs of this research include quantitative, dose response models that will elucidate associations between environmental agents and toxicity pathways as well as web-accessible databases using semantic web technologies that will integrate data and meta-information on toxicity pathways on multiple scales of biological organization. Outcomes include furthering the field of toxicity testing by capturing the synergistic biological effects of chemical mixtures, thereby approximating actual conditions faced by the public, as opposed to the single chemical paradigm of traditional risk assessments. The field of computational toxicology will also be enhanced through data integration.
- Berners-Lee, T. and Hendler, J. (2001) ‘Publishing on the semantic web’, Nature, Vol. 410, pp.1023–1024.
- Cogliano, V.J. (1998). Assessing the cancer risk from environmental PCBs. Environ.Health Perspect. 106, 317-23.
- Kavlock RJ, Ankley G, Blancato J, Breen M, Conolly R, Dix D, Houck K, Hubal E, Judson R, Rabinowitz J, Richard A, Setzer RW, Shah I, Villeneuve D, Weber E. Computational toxicology—A state of the science mini review. Toxicological Science, 2008; 103:14-27
- Noy, N.F. et al., 2009. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucl. Acids Res., 37(suppl_2), W170-173)
- O’Farrelly, C. and Doherty, D.G. (2007) “Innate Immune Mechanisms in the Liver”, in Liver Immunology: Principles and Practice (Gershwin, M.E; Vierling, J.M.; Manns, M.P., eds., Humana Press, Totowa, New Jersey.
- Pascual, P. (2009), “Evidence-based decisions for the wiki world”, Int.J.Metadata, Semantics and Ontologies, Vol. 3, No. 4, pp. 287-294.
- Ryan, L. (2008) ‘Combining data from multiple sources, with applications to environmental risk assessment’, Statistics in Medicine, Vol. 27, pp.698–710.
- Yokota, F. & K.M. Thompson, 2004. Value of information analysis in environmental health risk management decisions: Past, present, and future. Risk Anal. 24(3), 635–650.
[Reports]
- NRC (National Research Council) (2008). Science and Decisions: Advancing Risk Assessment. Washington, DC, National Academies Press.
- NRC (National Research Council) (2007A). Toxicity Testing in the 21st Century: A Vision and a Strategy. Washington, DC, National Academies Press.
- NRC (National Research Council) (2007B) ‘Models in environmental regulatory decision-making’, The National Academies Press, Washington, D.C.
- U.S. EPA. 2009. The U.S. Environmental Protection Agency’s Strategic Plan for Evaluating the Toxicity of Chemicals. EPA100/K-09/001. Washington, DC: U.S. Environmental Protection Agency.
[Books]
- Gelman, A., and Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.
F. Special Requirements
Agency policy and ethical considerations prevent EPA technical staff and managers from providing applicants with information that may create an unfair competitive advantage. Consequently, EPA employees will not review, comment, advise, and/or provide technical assistance to applicants preparing applications in response to EPA RFAs. EPA employees cannot endorse any particular application.
Multiple Investigator applications may be submitted as: (1) a single Lead Principal Investigator (PI) application with Co-PI(s) or (2) a Multiple PI application (with a single Contact PI). If you choose to submit a Multiple PI application, you must follow the specific instructions provided in Sections IV. and V. of this RFA. For further information, please see the EPA Implementation Plan for Policy on Multiple Principal Investigators (http://rbm.nih.gov/toolkit.htm).
Please note: Early career projects will not accommodate a Multiple PI application. Early career projects shall be submitted as a single Lead PI application. Special eligibility criteria apply to the early career portion of this RFA. Please see Section III of this RFA for details on the early career eligibility criteria.
The application must include a plan (see “Data Plan” in section IV.B.5.c.) to make available to the public all data generated from observations, analyses, or model development (primary data) and any secondary (or existing) data used under an agreement awarded from this RFA. The data must be available in a format and with documentation such that they may be used by others in the scientific community.
It is anticipated that a total of approximately $3 million will be awarded under this announcement, depending on the availability of funds and quality of applications received. The EPA anticipates funding approximately four awards, including one early career award. Requests for amounts in excess of a total of $750,000, including direct and indirect costs, will not be considered. The total project period requested in an application submitted for this RFA may not exceed four years. The EPA reserves the right to reject all applications and make no awards, or make fewer awards than anticipated, under this RFA. The EPA reserves the right to make additional awards under this announcement, consistent with Agency policy, if additional funding becomes available after the original selections are made. Any additional selections for awards will be made no later than six months after the original selection decisions.
EPA may award both grants and cooperative agreements under this announcement.
Under a grant, EPA scientists and engineers are not permitted to be substantially involved in the execution of the research. However, EPA encourages interaction between its own laboratory scientists and grant Principal Investigators after the award of an EPA grant for the sole purpose of exchanging information in research areas of common interest that may add value to their respective research activities. This interaction must be incidental to achieving the goals of the research under a grant. Interaction that is “incidental” does not involve resource commitments.
Where appropriate, based on consideration of the nature of the proposed project relative to the EPA’s intramural research program and available resources, the EPA may award cooperative agreements under this announcement. When addressing a research question/problem of common interest, collaborations between scientists and the institution’s principal investigators are permitted under a cooperative agreement. These collaborations may include data and information exchange, providing technical input to experimental design and theoretical development, coordinating extramural research with in-house activities, the refinement of valuation endpoints, and joint authorship of journal articles on these activities. Proposals may not identify EPA cooperators or interactions; specific interactions between EPA’s investigators and those of the prospective recipient for cooperative agreements will be negotiated at the time of award.
A. Eligible Applicants
Public nonprofit institutions/organizations (includes public institutions of higher education and hospitals) and private nonprofit institutions/organizations (includes private institutions of higher education and hospitals) located in the U.S., state and local governments, Federally Recognized Indian Tribal Governments, and U.S. territories or possessions are eligible to apply. Profit-making firms are not eligible to receive assistance agreements from the EPA under this program.
Eligible nonprofit organizations include any organizations that meet the definition of nonprofit in OMB Circular A-122, located at 2 CFR Part 230. However, nonprofit organizations described in Section 501(c) (4) of the Internal Revenue Code that lobby are not eligible to apply.
National laboratories funded by Federal Agencies (Federally-Funded Research and Development Centers, “FFRDCs”) may not apply. FFRDC employees may cooperate or collaborate with eligible applicants within the limits imposed by applicable legislation and regulations. They may participate in planning, conducting, and analyzing the research directed by the applicant, but may not direct projects on behalf of the applicant organization. The institution, organization, or governance receiving the award may provide funds through its assistance agreement from the EPA to an FFRDC for research personnel, supplies, equipment, and other expenses directly related to the research. However, salaries for permanent FFRDC employees may not be provided through this mechanism.
Federal Agencies may not apply. Federal employees are not eligible to serve in a principal leadership role on an assistance agreement, and may not receive salaries or augment their Agency’s appropriations in other ways through awards made under this program.
The applicant institution may enter into an agreement with a Federal Agency to purchase or utilize unique supplies or services unavailable in the private sector. Examples are purchase of satellite data, census data tapes, chemical reference standards, analyses, or use of instrumentation or other facilities not available elsewhere. A written justification for federal involvement must be included in the application. In addition, an appropriate form of assurance that documents the commitment, such as a letter of intent from the Federal Agency involved, should be included.
The early career projects will support new, creative investigators with outstanding promise at the Assistant Professor or equivalent level. Principal investigators from applicant institutions applying for the early career portion of the RFA must meet the following additional eligibility requirements:
- Hold a doctoral degree in a field of science or engineering by the closing date of the RFA;
- Be untenured at the closing date of the RFA;
- By the award date, be employed in a tenure-track position (or tenure-track-equivalent position) as an assistant professor (or equivalent title) at an institution in the U.S., its territories, or possessions. Note: For a position to be considered a tenure-track-equivalent position, it must meet all of the following requirements: (1) the employing department or organization does not offer tenure; (2) the appointment is a continuing appointment; (3) the appointment has substantial educational responsibilities; and (4) the proposed project relates to the employee's career goals and job responsibilities as well as to the goals of the department/organization.
The purpose of the early career project is to fund research by the early career PI. Senior researchers may collaborate in a supporting role for early career projects. Early career applications should not propose significant resources for senior researchers and may not list senior researchers as co-PIs.
Potential applicants who are uncertain of their eligibility should contact William Stelz (stelz.william@epa.gov) in NCER, phone (202) 343-9802
B. Cost-Sharing
Institutional cost-sharing is not required.
C. Other
Applications must substantially comply with the application submission instructions and requirements set forth in Section IV of this announcement or they will be rejected. In addition, where a page limitation is expressed in Section IV with respect to parts of the application, pages in excess of the page limit will not be reviewed. Applications must be submitted to EPA (see Section IV.E. “Submission Instructions and Other Submission Requirements” for further information) on or before the solicitation closing date and time in Section IV of this announcement or they will be returned to the sender without further consideration. Also, applications exceeding the funding limits or project period term described herein will be returned without review. Further, applications that fail to demonstrate a public purpose of support or stimulation (e.g., by proposing research which primarily benefits a Federal program or provides a service for a Federal agency) will not be funded.
Applications must propose research in one of the Research Areas identified in Section I.D. As discussed in greater detail in Section I, applications submitted in response to this solicitation’s first Research Area must propose developing quantitative, dose-response models that elucidate toxicity pathways in which the human liver manifests an adverse health effect and/or provides a mediating role in the human response to toxic chemicals. These models must be based on data drawn from multiple scales of biological organization and must indicate the effect of different dose levels of the toxic chemical(s). Moreover, applications submitted in response to this solicitation’s first Research Area must also propose formal model evaluation methods that explain how the researchers will document data provenance, analyze sources of uncertainty and variability, and evaluate alternative model forms. Applications submitted in response to this solicitation’s first Research Area must indicate that the Principal Investigators are willing to work with the Principal Investigators funded under the second research area by providing their data and information about their data, excluding confidential or private information.
As discussed in greater detail in Section I, applications submitted in response to this solicitation’s second Research Area must propose developing a web-accessible database using semantic web technologies in order to integrate data and meta-information on toxicity pathways on multiple scales of biological organization.
In addition, to be eligible for funding consideration, a project’s focus must consist of activities within the statutory terms of EPA’s financial assistance authorities; specifically, the statute(s) listed in I.C. above. Generally, a project must address the causes, effects, extent, prevention, reduction, and elimination of air pollution, water pollution, solid/hazardous waste pollution, toxic substances control, or pesticide control depending on which statute(s) is listed in I.C. above. These activities should relate to the gathering or transferring of information or advancing the state of knowledge. Proposals should emphasize this “learning” concept, as opposed to “fixing” an environmental problem via a well-established method. Proposals relating to other topics which are sometimes included within the term “environment” such as recreation, conservation, restoration, protection of wildlife habitats, etc., must describe the relationship of these topics to the statutorily required purpose of pollution prevention and/or control.
Applications deemed ineligible for funding consideration will be notified within fifteen calendar days of the ineligibility determination.
IV. APPLICATION AND SUBMISSION INFORMATION
Formal instructions for submission through Grants.gov follow in Section E.
A. Internet Address to Request Application Package
Use the application package available at Grants.gov (see Section E. “Submission Instructions and Other Submission Requirements”). Note: With the exception of the current and pending support form (available at http://epa.govhttps://www.epa.gov/research-grants/funding-opportunities-how-apply-and-required-forms), all necessary forms are included in the electronic application package.
An email will be sent by NCER to the Lead/Contact PI and the Administrative Contact (see below) to acknowledge receipt of the application and transmit other important information. The email will be sent from receipt.application@epa.gov; emails to this address will not be accepted. If you do not receive an email acknowledgment within 30 days of the submission closing date, immediately inform the Eligibility Contact shown in this solicitation. Failure to do so may result in your application not being reviewed. See Section E. “Submission Instructions and Other Submission Requirements” for additional information regarding the application receipt acknowledgment.
B. Content and Form of Application Submission
The application is made by submitting the materials described below. Applications must contain all information requested and be submitted in the formats described.
- Standard Form 424
The applicant must complete Standard Form 424. Instructions for completion of the SF424 are included with the form. (However, note that EPA requires that the entire requested dollar amount appear on the 424, not simply the proposed first year expenses.) The form must contain the signature of an authorized representative of the applying organization.
Applicants are required to provide a “Dun and Bradstreet Data Universal Numbering System” (DUNS) number when applying for federal grants or cooperative agreements. Organizations may receive a DUNS number by calling 1-866-705-5711 or by visiting the web site at http://www.dnb.com.
Executive Order 12372, “Intergovernmental Review of Federal Programs,” does not apply to the Office of Research and Development's research and training programs unless EPA has determined that the activities that will be carried out under the applicants' proposal (a) require an Environmental Impact Statement (EIS), or (b) do not require an EIS but will be newly initiated at a particular site and require unusual measures to limit the possibility of adverse exposure or hazard to the general public, or (c) have a unique geographic focus and are directly relevant to the governmental responsibilities of a State or local government within that geographic area.
If EPA determines that Executive Order 12372 applies to an applicant's proposal, the applicant must follow the procedures in 40 CFR Part 29. The applicant must notify their state's single point of contact (SPOC). To determine whether their state participates in this process, and how to comply, applicants should consult http://www.whitehouse.gov/omb/grants/spoc.html. If an applicant is in a State that does not have a SPOC, or the State has not selected research and development grants for intergovernmental review, the applicant must notify directly affected State, area wide, regional and local entities of its proposal.
EPA will notify the successful applicant(s) if Executive Order 12372 applies to its proposal prior to award.
- Key Contacts
The applicant must complete the “Key Contacts” form found in the Grants.gov application package. An “Additional Key Contacts” form is also available at http://epa.govhttps://www.epa.gov/research-grants/funding-opportunities-how-apply-and-required-forms. The Key Contacts form should also be completed for major sub-agreements (i.e., primary investigators). Please make certain that all contact information is accurate.
For Multiple PI applications: The Additional Key Contacts form must be completed (see Section I.F. for further information). Note: The Contact PI must be affiliated with the institution submitting the application. EPA will direct all communications related to scientific, technical, and budgetary aspects of the project to the Contact PI; however, any information regarding an application will be shared with any PI upon request. The Contact PI is to be listed on the Key Contact Form as the Project Manager/Principal Investigator (the term Project Manager is used on the Grants.gov form, the term Principal Investigator is used on the form located on NCER’s web site). For additional PIs, complete the Major Co-Investigator fields and identify PI status next to the name (e.g., “Name: John Smith, Principal Investigator”).
- Table of Contents
Provide a list of the major subdivisions of the application indicating the page number on which each section begins.
- Abstract (1 page)
The abstract is a very important document in the review process. Therefore, it is critical that the abstract accurately describes the research being proposed and conveys all the essential elements of the research. Also, the abstracts of applications that receive funding will be posted on the NCER web site.
The abstract should include the information described below (a-h). Examples of abstracts for current grants may be found on the NCER web site.
- Funding Opportunity Title and Number for this proposal.
- Project Title: Use the exact title of your project as it appears in the application. The title must be brief yet represent the major thrust of the project. Because the title will be used by those not familiar with the project, use more commonly understood terminology. Do not use general phrases such as “research on.”
- Investigators: For applications with multiple investigators, state whether this is a single Lead PI (with co-PIs) or Multiple PI application (see Section I.F.). For Lead PI applications, list the Lead PI, then the name(s) of each co-PI who will significantly contribute to the project. For Multiple PI applications, list the Contact PI, then the name(s) of each additional PI. Provide a web site URL or an email contact address for additional information.
- Institution: In the same order as the list of investigators, list the name, city and state of each participating university or other applicant institution. The institution applying for assistance must be clearly identified.
- Project Period and Location: Show the proposed project beginning and ending dates and the geographical location(s) where the work will be conducted.
- Project Cost: Show the total dollars requested from the EPA (include direct and indirect costs for all years).
- Project Summary: Provide three subsections addressing: (1) the objectives of the study (including any hypotheses that will be tested), (2) the experimental approach to be used (a description of the proposed project), and (3) the expected results of the project and how it addresses the research needs identified in the solicitation, including the estimated improvement in risk assessment or risk management that will result from successful completion of the proposed work.
- Supplemental Keywords: Without duplicating terms already used in the text of the abstract, list keywords to assist database searchers in finding your research. A list of suggested keywords may be found at: http://epa.govhttps://www.epa.gov/research-grants/funding-opportunities-how-apply-and-required-forms.
- Research Plan, Quality Assurance Statement, Data Plan and References
- Research Plan (15 pages)
Applications should focus on a limited number of research objectives that adequately and clearly demonstrate that they meet the RFA requirements. Explicitly state the main hypotheses that you will investigate, the data you will create or use, the analytical tools you will use to investigate these hypotheses or analyze these data, and the results you expect to achieve. Research methods must be clearly stated so that reviewers can evaluate the appropriateness of your approach and the tools you intend to use. A statement such as: “we will evaluate the data using the usual statistical methods” is not specific enough for peer reviewers.
This description must not exceed fifteen (15) consecutively numbered (bottom center), 8.5x11-inch pages of single-spaced, standard 12-point type with 1-inch margins. While these guidelines establish the minimum type size requirements, applicants are advised that readability is of paramount importance and should take precedence in selection of an appropriate font for use in the proposal.
The description must provide the following information:
- Objectives: List the objectives of the proposed research and the hypotheses being tested during the project, and briefly state why the intended research is important and how it fulfills the requirements of the solicitation. This section should also include any background or introductory information that would help explain the objectives of the study. If this application is to expand upon research supported by an existing or former assistance agreement awarded under the STAR program, indicate the number of the agreement and provide a brief report of progress and results achieved under it.
- Approach/Activities: Outline the research design, methods, and techniques that you intend to use in meeting the objectives stated above.
- Expected Results, Benefits, Outputs, and Outcomes: Describe the results you expect to achieve during the project (outputs) and the potential benefits of the results (outcomes). This section should also discuss how the research results will lead to solutions to environmental problems and improve the public’s ability to protect the environment and human health. A clear, concise description will help NCER and peer reviewers understand the merits of the research.
- General Project Information: Discuss other information relevant to the potential success of the project. This should include facilities, personnel expertise/experience, project schedules, proposed management, interactions with other institutions, etc. Applications for multi-investigator projects must identify project management and the functions of each investigator in each team and describe plans to communicate and share data.
- Appendices may be included but must remain within the 15-page limit.
- Quality Assurance Statement (3 pages)
For projects involving environmental data collection or processing, conducting surveys, modeling, method development, or the development of environmental technology (whether hardware-based or via new techniques), provide a Quality Assurance Statement (QAS) regarding the plans for processes that will be used to ensure that the products of the research satisfy the intended project objectives. Follow the guidelines provided below to ensure that the QAS describes a system that complies with ANSI/ASQC E4, Specifications and Guidelines for Quality Systems for Environmental Data Collection and Environmental Technology Programs. Do not exceed three consecutively numbered, 8.5x11-inch pages of single-spaced, standard 12-point type with 1-inch margins.
NOTE: If selected for award, applicants will be expected to provide additional quality assurance documentation.
Address each applicable section below by including the required information, referencing the specific location of the information in the Research Plan, or explaining why the section does not apply to the proposed research. (Not all will apply.)
- Identify the individual who will be responsible for the quality assurance (QA) and quality control (QC) aspects of the research along with a brief description of this person’s functions, experience, and authority within the research organization. Describe the organization’s general approach for conducting quality research. (QA is a system of management activities to ensure that a process or item is of the type and quality needed for the project. QC is a system of activities that measures the attributes and performance of a process or item against the standards defined in the project documentation to verify that they meet those stated requirements.)
- Discuss project objectives, including quality objectives, any hypotheses to be tested, and the quantitative and/or qualitative procedures that will be used to evaluate the success of the project. Include any plans for peer or other reviews of the study design or analytical methods.
- Address each of the following project elements as applicable:
- Collection of new/primary data:
(Note: In this case the word “sample” is intended to mean any finite part of a statistical population whose properties are studied to gain information about the whole. If certain attributes listed below do not apply to the type of samples to be used in your research, simply explain why those attributes are not applicable.)- Discuss the plan for sample collection and analysis. As applicable, include sample type(s), frequency, locations, sample sizes, sampling procedures, and the criteria for determining acceptable data quality (e.g., precision, accuracy, representativeness, completeness, comparability, or data quality objectives).
- Describe the procedures for the handling and custody of samples including sample collection, identification, preservation, transportation, and storage, and how the accuracy of test measurements will be verified.
- Describe or reference each analytical method to be used, any QA or QC checks or procedures with the associated acceptance criteria, and any procedures that will be used in the calibration and performance evaluation of the analytical instrumentation.
- Discuss the procedures for overall data reduction, analysis, and reporting. Include a description of all statistical methods to make inferences and conclusions, acceptable error rates and/or power, and any statistical software to be used.
- Use of existing/secondary data (i.e., data previously collected for other purposes or from other sources):
- Identify the types of secondary data needed to satisfy the project objectives. Specify requirements relating to the type of data, the age of data, geographical representation, temporal representation, and technological representation, as applicable.
- Specify the source(s) of the secondary data and discuss the rationale for selection.
- Establish a plan to identify the sources of the secondary data in all deliverables/products.
- Specify quality requirements and discuss the appropriateness for their intended use. Accuracy, precision, representativeness, completeness, and comparability need to be addressed, if applicable.
- Describe the procedures for determining the quality of the secondary data.
- Describe the plan for data management/integrity.
- Method development:
(Note: The data collected for use in method development or evaluation should be described in the QAS as per the guidance in section 3A and/or 3B above.)Describe the scope and application of the method, any tests (and measurements) to be conducted to support the method development, the type of instrumentation that will be used and any required instrument conditions (e.g., calibration frequency), planned QC checks and associated criteria (e.g., spikes, replicates, blanks), and tests to verify the method’s performance.
- Development or refinement of models:
(Note: The data collected for use in the development or refinement of models should be described in the QAS as per the guidance in section 3A and/or 3B above.)- Discuss the scope and purpose of the model, key assumptions to be made during development/refinement, requirements for code development, and how the model will be documented.
- Discuss verification techniques to ensure the source code implements the model correctly.
- Discuss validation techniques to determine that the model (assumptions and algorithms) captures the essential phenomena with adequate fidelity.
- Discuss plans for long-term maintenance of the model and associated data.
- Development or operation of environmental technology:
(Note: The data collected for use in the development or evaluation of the technology should be described in the QAS as per the guidance in section 3A and/or 3B above.)- Describe the overall purpose and anticipated impact of the technology.
- Describe the technical and quality specifications of each technology component or process that is to be designed, fabricated, constructed, and/or operated.
- Discuss the procedure to be used for documenting and controlling design changes.
- Discuss the procedure to be used for documenting the acceptability of processes and components, and discuss how the technology will be benchmarked and its effectiveness determined.
- Discuss the documentation requirements for operating instructions/guides for maintenance and use of the system(s) and/or process(s).
- Conducting surveys:
(Note: The data to be collected in the survey and any supporting data should be described in the QAS as per the guidance in section 3A and/or 3B above.)Discuss the justification for the size of the proposed sample for both the overall project and all subsamples for specific treatments or tests. Identify and explain the rational for the proposed statistical techniques (e.g., evaluation of statistical power).
- Collection of new/primary data:
- Discuss data management activities (e.g., record-keeping procedures, data-handling procedures, and the approach used for data storage and retrieval on electronic media). Include any required computer hardware and software and address any specific performance requirements for the hardware/software configuration used.
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- Research Plan (15 pages)
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.