Required Application Instructions

It is critical that applicants follow the instructions in the SF424 (R&R) Application Guide, except where instructed to do otherwise (in this FOA or in a Notice from the NIH Guide for Grants and Contracts). Conformance to all requirements (both in the Application Guide and the FOA) is required and strictly enforced. Applicants must read and follow all application instructions in the Application Guide as well as any program-specific instructions noted in Section IV. When the program-specific instructions deviate from those in the Application Guide, follow the program-specific instructions. Applications that do not comply with these instructions may be delayed or not accepted for review.

Part 1. Overview Information
Part 2. Full Text of the Announcement

Section I. Funding Opportunity Description
Section II. Award Information
Section III. Eligibility Information
Section IV. Application and Submission Information
Section V. Application Review Information
Section VI. Award Administration Information
Section VII. Agency Contacts
Section VIII. Other Information

The goal of this interagency funding opportunity announcement (FOA) is to support the development of multiscale models to accelerate biological, biomedical, behavioral, environmental and clinical research. The NIH, ARO, DOE, FDA, NASA, NSF, and ONR recognize that in order to efficiently and effectively address the challenges of understanding multiscale biological and behavioral systems, researchers will need predictive, computational models that encompass multiple biological and behavioral scales. This FOA supports the development of non-standard modeling methods and experimental approaches to facilitate multiscale modeling, and active participation in community-driven activities through the Multiscale Modeling (MSM) Consortium, www.imagwiki.nibib.nih.gov.

Multiscale modeling uses mathematics and computation to quantitatively represent and simulate a system at more than one scale while functionally linking the mathematical models across these scales. This FOA is focused on biological and behavioral scales, which include atomic, molecular, molecular complexes, sub-cellular, cellular, multi-cell systems, tissue, organ, multi-organ systems, organism/individual, group, organization, market, environment, and populations. Multiscale models of biological and behavioral systems can be used as important tools to address a range of biomedical, biological, behavioral, environmental, and clinical problems. Multiscale modeling and analysis methods can provide fundamental infrastructure for understanding and predicting biological and environmental processes; diseases; and human and organizational behavior patterns and outcomes.

In 2004 the Interagency Modeling and Analysis Group (IMAG) released the Interagency Opportunities in Multiscale Modeling (MSM) in Biomedical, Biological, and Behavioral Systems Initiative, which laid the foundation for multiscale modeling by supporting grants that develop the mathematical and computational interfaces between biological scales (http://www.nsf.gov/pubs/2004/nsf04607/nsf04607.htm). In 2007 IMAG released the Predictive Multiscale Models of the Physiome in Health and Disease FOA to promote the development of multiscale models at higher levels of the physiome that are predictive of health and disease (https://grants.nih.gov/grants/guide/pa-files/par-08-023.html). In 2010, the IMAG Futures Report produced a systematic assessment, at multiple biological scales and across multiple biomedical fields, of the extent to which computational modeling has made an impact in the broader biomedical research endeavor, https://www.nibib.nih.gov/sites/default/files/IFM%20Report_FINAL.pdf. In 2011 IMAG released the Predictive Multiscale Models for Biomedical, Biological, Behavioral, Environmental and Clinical Research (Interagency U01) FOA to promote both the development of novel multiscale models and methods, and multiscale physiome modeling; in addition to the development of targeted partnerships to increase the impact of multiscale models in basic and translational biomedical, biological, behavioral, environmental and clinical research, https://grants.nih.gov/grants/guide/pa-files/PAR-11-203.html. This is the reissue of that FOA.

The original MSM initiative gave rise to the Multiscale Modeling (MSM) Consortium which is composed of several working groups focusing on scientific and computational issues related to multiscale modeling. The MSM Consortium now serves to bring together a growing community of modelers interested in multiscale modeling of biomedical, biological and behavioral systems (www.imagwiki.nibib.nih.gov). In addition IMAG continues to bring together many government agencies interested in multiscale modeling (http://www.nibib.nih.gov/research/featured-programs/interagency-modeling-and-analysis-group-imag). The spirit of IMAG is to promote the development of new or novel modeling and analysis methods throughout the scientific community. Through the MSM Consortium, IMAG promotes collaborative team science and the sharing of good quality scientific modeling and analysis tools as a result of employing appropriate software engineering practices. This cooperative agreement U01 mechanism requires investigators to allocate funds to propose new collaborative activities in the MSM Consortium.

Multiscale models can be designed to integrate diverse data, create testable hypotheses leading to new investigational studies, identify and share gaps in knowledge requiring further research, uncover biological mechanisms, or make predictions about clinical outcome or intervention effects. These models can draw on a variety of data sources including relevant physical, environmental, clinical and population data. Ultimately multiscale models and the information derived from their use will enable biomedical, biological, behavioral, environmental and clinical researchers to understand complex biological and behavioral systems in a manner not possible through traditional research methods. The ultimate goal of the models would be to make realistic scientific predictions to address problems and issues in the environment; in the human body (e.g., to prevent, diagnose and treat the diseases or aberrations in normal development, and/or to predict treatment outcomes); and among individuals, groups, and within populations.

This FOA specifically calls the community to develop and apply multiscale models that link different spatial or temporal scales or different levels of aggregation (w. ref. a wide range of social, behavioral, and population modeling), to address compelling biological, biomedical, behavioral, environmental and clinical problems. Applicants should identify a challenging multiscale problem or approach that is currently not being addressed. The proposed multiscale models are expected to be unique, push the boundaries, and may lead to higher risk projects. Examples of specific challenges include, but are not limited to, those listed below:

• Next-generation multiscale models that integrate between different scientific fields (e.g. cardiovascular and neuroscience) and predict integrated functions
• Higher level models and modeling approaches that integrate multiple physiological (and possibly psychological) systems in order to better understand the human response (e.g. to extended space flight, and other unique environments)
• Novel methods to fuse data-rich and data-poor scales to enable predictive modeling
• Novel methods to fuse biological and/or behavioral processes and mechanisms to model outcomes as a result of various interventions
• Reproducible and reusable multiscale models that will be integrated and adopted into model-poor fields (e.g. tissue engineering, regenerative medicine, drug and gene delivery, preventive interventions)
• Multiscale models strongly coupled with standardized protocols for model-driven data collection
• Implementing virtual clinical trials with multiscale models to predict outcomes
• Problem-driven multiscale models that require high performance computing (see below for available advanced computational resources)
• Model predictions that drive a community of experimentalists towards systematic testing and validation
• Predictive multiscale models that strongly incorporate uncertainty quantification
• Mechanistic multiscale models that bridge to the population level to capture more clinical and biological realism for the population
• Models that generate testable hypotheses regarding the biological underpinnings of behavioral and social phenomena and processes at the individual and population level
• Models that describe mechanisms through which outside-the-skin factors, such as behavioral stressors, social bonding, parenting behavior, etc., can lead to inside-the-skin changes, such as in gene expression, the microbiome, or other factors that affect health or behavior
• Models that provide innovative characterizations of interactions between individual-level behaviors, cognition, or affective processes and group-, market-, or population-level outcomes
• Models to explore underlying mechanisms of individual-, community-, or population-level preventive or therapeutic interventions
• Novel computational modeling approaches for big data that account for simultaneous sources of data on multiple scales; from biological and physiological measures, to social and psychological variables, and to environmental or contextual or societal level factors
• Multiscale models that characterize the implications of individual-level risks for collective outcomes, or the implications of systemic risks for individual behaviors and outcomes
• Predictive multiscale models to improve clinical workflow, standard operating procedures, patient-specific modeling for diagnosis and therapy planning

If investigators are expanding an existing model, the existing model should address a new breakthrough challenge in multiscale modeling, such as those listed in the bullets above. In addition, this FOA seeks to achieve the scientific goals by encouraging highly interactive partnerships that strongly integrate diverse expertise to further increase the impact of multiscale models in the broader research and policy community. Examples of diverse partnerships include, but are not limited to the following:

• experimental and modeling expertise, so that the models create testable hypotheses leading to new investigational studies, or
• mathematical and or statistical expertise with domain-modeling expertise, so that new methods enhance the function of the models, or
• expertise focused on different spatial or temporal scales, or different levels of aggregation, or different experimental and observational scales, or different deterministic and statistics-driven scales, or
• expertise from mature modeling fields with expertise from fields with an emerging use of models, or
• expertise relevant for biological and behavioral modeling; such as, computational neuroscience, systems biology, physiome research, agent-based modeling, system dynamics, microsimulation, decision theory, economics, cognitive science, affective neuroscience, and social network theory.

This FOA uses the U01 cooperative agreement activity code. Project outcomes, milestones and timeline for both scientific progress and participation within the MSM Consortium will be peer reviewed (as described in Section V) and established prior to funding, and must be met prior to funding of each subsequent budget period. The cooperative agreement activity code promotes participation in the MSM Consortium as a funded mandate. In the MSM Consortium plan, applicants are strongly encouraged to propose collaborative activities that contribute to the needs of the wider MSM community, involving community input for the MSM Consortium plan to succeed. Investigators funded from this FOA are expected to play an active role in the MSM Consortium, leading working groups, hosting webinars, and sharing data, models, expertise and other efforts to contribute to the greater multiscale modeling community as appropriate and consistent with achieving the goals of the program (See Section IV.2 MSM Consortium Plan, and Section VI Cooperative Agreement Terms and Conditions of Award). Program staff from the IMAG award agency will have a significant, although not dominant, role in the planning and execution of the supported activities. In addition, IMAG program staff will promote the mission of the MSM Consortium, organize annual meetings, facilitate awardee participation in the Consortium activities, and have a significant role in the assessment of annual milestone performance.

It is expected that the proposed multiscale model cross at least two scales with mechanistic linkages between scales; is developed with explicit predictive capabilities; and is developed with an architecture which will facilitate future model sharing (see Section IV.2 Research Strategy).

Investigators are welcome to use advanced computational resources to support fundamental research and technology development to achieve a predictive, systems-level understanding of complex biological systems. Advanced computing research could provide model development capabilities, data analytics, frameworks for integration and collaboration, and uncertainty quantification. Such computing frameworks can integrate multi-disciplinary, multi-scale data with process models to examine coupled phenomena across a range of scales. Ideally, these frameworks would be flexible enough to enable community-level modeling efforts that integrate data and modeling approaches across a wide spectrum of biological, behavioral, clinical and environmental science disciplines. An ability to connect data with models from a wide variety of sources enables more holistic and robust predictions of complex system behavior. The DOE's Office of Science supports a computing user facility, National Energy Research Scientific Computing Center (NERSC; http://www.nersc.gov/) that will enhance computational research in biology - please see DOE Specific Interests Section below. As well, the NSF Division of Advanced Cyberinfrastructure of the Directorate for Computer & Information Science & Engineering supports the XSEDE Cyberinfrastructure (xsede.org) and eXtreme Digital Resources for Science and Engineering (XD). These projects form an open scientific discovery environment combining high-end computational and data resources at many partner sites to create an integrated, persistent infrastructure, which will also enhance computational research in biology.

Investigators interested in 1) proposing to develop models at a single biological or behavioral scale, or at multiple scales without linking between scales; 2) proposing multiscale modeling without an explicit predictive component; 3) proposing multiscale modeling without representative biological or behavioral mechanisms and processes; 4) proposing to develop models that do not incorporate a model architecture that will facilitate model sharing as appropriate; or 5) proposing a project that does not include a MSM Consortium Plan or a Model Credibility Plan or a Broader Impacts Statement or a Data Management Plan (as described in Section IV.2) should respond to other FOAs.

Specific interests:

The following section briefly describes the specific interests of the participating funding components of this FOA. All interests are examples and are not limited to these cases. Applicants are strongly encouraged to contact the funding components.

The National Institute of Biomedical Imaging and Bioengineering (NIBIB) is interested in supporting the development of predictive multiscale models that have broad diagnostic, therapeutic and interventional applications in diseases or health conditions. Areas of interest include multiscale modeling to complement technology development in all other program areas of the NIBIB, such as medical device development and testing, rehabilitation engineering, surgical techniques, drug and gene delivery, tissue engineering, sensor and microsystems, synthetic biology, and biointerfaces, http://www.nibib.nih.gov/research/scientific-program-areas.

The National Cancer Institute (NCI) is interested in supporting the development of predictive multiscale models of cancer processes. These models may be designed to elucidate basic mechanisms underlying cancer initiation and progression and/or to address important translational, clinical or epidemiological questions related to cancer risk, prevention, diagnosis and treatment.

The National Human Genomic Research Institute (NHGRI) is interested in the development of multiscale models to predict the effects of genomic variation in coding and noncoding regions and epigenetic modification on the transmission of information and events across scales, such as in gene expression, cellular state, disease status, and gene-environment interactions on organismal phenotypes in humans or model organisms; as well as to support the development of major advances in DNA sequencing or other high-throughput genomic technologies.

The National Institute on Aging (NIA) is interested in supporting research on multiscale models that link molecular mechanisms with age-related changes in cognition, emotion, vision, taste, smell, touch, audition, motor, endocrine, metabolic, cardiovascular, hematopoietic, renal, immunologic, and musculoskeletal function; on age-related changes in inflammation and adaptation to stress; on predictive models of age-related increases in organ fibrosis or adipose cell infiltration; and on predictive models of Alzheimer's disease, frontotemporal dementia, and delirium. The NIA also encourages the development of multiscale models of the role of social and behavioral factors in predicting well-being, life expectancy, disability, and the burden of illness.

The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) is interested in supporting research on predictive models related to the causes, treatment, and prevention of arthritis and musculoskeletal and skin diseases. Some examples of research topics for investigation may include, but are not limited to, the development of models to aid in the understanding of the pathogenesis of the rheumatic diseases or of other chronic inflammatory diseases that affect skin, bone and muscle; models of repair and/or regeneration of tissues such as muscle, bone, or skin; or models that address the relationship between musculoskeletal imaging findings and structural integrity of tissues or patient related outcomes such as pain or function.

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) is interested in supporting multiscale modeling research related to the causes, consequences, treatment, and prevention of alcohol-related problems and alcohol use disorders. Examples of research topics include but are not limited to:

• models that characterize interactions between individual-level alcohol-related behaviors and population-level health and economic outcomes;
• models to explore underlying mechanisms of individual-, community-, or population-level preventive interventions;
• projects to model the linkages between inside-the-skin and outside-the-skin determinants or consequences of alcohol consumption, intoxication, or alcohol use disorder;
• multiscale models for complex processes relating alcohol use and abuse, metabolism, and alcohol-related tissue or organ damage, such as progressive development of alcoholic liver disease, alcoholic pancreatitis, or alcohol-induced carcinogenesis in organs including breast, colon, liver, and pancreas;
• multiscale models of the onset or progression of or risks for alcohol dependence;
• models of the determinants and mechanisms underlying changes in drinking before, during, and after treatment, as well as treatment-seeking and utilization; and
• models of the connections between momentary or short-term determinants of drinking behaviors and long-term (chronic, life-cycle, or intergenerational) aspects or consequences of these behaviors.

The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) is interested in research that makes use of computational, mathematical, or engineering models to deepen our understanding of the multiscale biomedical, biological, clinical, behavioral and social processes associated with health, disability, and developmental outcomes from pre-conception into adulthood. Examples of topics of interest to the NICHD include but are not limited to: child, maternal, reproductive and population health models utilizing multiscale perspectives, especially those with the potential to address policy-resistant health problems; multiscale models that address the systems affecting intellectual, behavioral and physical disability outcomes, rehabilitation outcomes, and long-term impacts of disability on individuals, families, and communities; models of the multiscale relationships between demographic and environmental factors and their effects on health and population processes, including fertility, family formation, population distribution and immigration; and multiscale models of developmental processes for explaining embryogenesis and/or organogenesis through understanding the networks of interacting components (i.e. molecules, cells, tissues or organs) on a whole cell, tissue, organ, or organism-wide basis.

The National Institute on Drug Abuse (NIDA) is interested in supporting multiscale modeling research that links molecular mechanisms, intracellular signaling networks, or neural plasticity at the cellular level with the function of brain circuits, cognition, affect, decision-making, and other behavioral and social processes of relevance to understanding drug abuse and addiction. Also of interest are multiscale models that can aid in the prediction of physiological pathologies from drug effects at the cellular level, and multiscale models that include social networks or populations. Finally, NIDA is interested in multiscale modeling for treatment and prevention services to support decision making within and among systems of care that can span individual, organizational, spatial and temporal scales.

The U.S. Army Research Office (ARO), Biomathematics Program is interested in basic, high-risk, high-reward research that uses, develops, and analyzes mechanistic multiscale mathematical models to uncover fundamental relationships in a wide variety of biological systems. The models may use mathematical techniques from fields traditionally used in modeling, such as probability, dynamical systems, and partial differential equations, but innovative modeling methods from traditionally "pure" areas of mathematics such as topology, differential geometry, and algebra are especially sought. Of particular interest currently are projects that use mathematical modeling to find commonalities in mechanism between different biological systems and that express these underlying principles in mathematical terms, as well as research taking advantage of recent advances in neuroscience and newly-available experimental data to gain a fundamental understanding of brain physiology, cognition, and neurological disease through multiscale modeling.

The Department of Energy (DOE) Biological and Environmental Research (BER) Program advances world-class biological and environmental research programs and scientific user facilities to support DOE’s energy, environment, and basic research missions. The Biological Systems Science Division (BSSD, http://science.energy.gov/ber/research/bssd/) provides the scientific and analytical technologies needed to translate genomic sequence into a profound and comprehensive understanding of the myriad of processes carried out by biological systems. Research within this program leverage the genomic code as a starting point to understand systems biology through (1) Systems analysis of the collective omics (e.g. transcriptomics, proteomics and metabolomics) of plants and microbes, (2) Development of new methods for characterizing and imaging molecular systems, and (3) Development of new approaches to synthesize and redesign biology processes. The NERSC scientific computing facility (http://www.nersc.gov/) will provide CPU support to projects that address DOE-BER’s missions in energy and the environment and will require approval by DOE-BER for this support. Applicants interested in DOE funding may wish to use the September due dates for this FOA.

The U.S. Food and Drug Administration (FDA) is interested in development of predictive multiscale models of physiology and pathophysiology that improve our understanding of the performance of medical products, such as medical devices or medical pharmaceuticals, in humans. To facilitate more effective medical product development, improved methods are needed to predict whether a proposed medical product design will function properly and safely. Computational modeling should be integrated with in vitro and in vivo experiments and/ or clinical studies in such a way that these distinct elements and their interplay will provide a more informative medical product evaluation pathway. For example, the Artificial Pancreas Team at FDA’s Center for Devices and Radiological Health (CDRH) is interested in innovative computational modeling approaches to simulate blood glucose fluctuations in response to food, drug (e.g., insulin and/or glucagon) and daily activities in patients with Type 1 diabetes. Such models are expected to facilitate the development of closed-loop delivery systems towards a fully closed-loop, artificial pancreas product that mimics the functions of a healthy pancreas.

The National Aeronautics and Space Administration (NASA) is interested in understanding the human response to extended space flight, with the ultimate goal of developing countermeasures to the debilitating effects of flight. When humans go into space, many physiological changes take place in response to multiple environmental stressors (weightlessness, altered light/dark cycles, radiation exposure, isolation and confinement, etc.). These changes affect most every system in the body (sensorimotor, cardiovascular, muscle, bone, immune, etc.), and can have adverse consequences for health and performance (including psychological). These systems also interact with each other in ways that we do not fully understand. Nevertheless, the body responds with a set of adaptive adjustments, resulting in a situation called space normal. Much research over many years has provided a good understanding of many of the individual adaptive adjustments. However, the multiple systems have often been explored in an ad hoc fashion. What is missing is an overall conceptual framework or organizing principle by which we might better understand how the organism as a whole responds to space flight. Several aspects of this system should be considered in any modeling approach: the population of astronauts is relatively homogeneous, highly trained, and well-characterized; and the flight environment is well-understood and constantly monitored. Insight into critical points of intervention in highly interconnected networks (like the human body) might permit a single countermeasure when currently multiple countermeasures are needed, http://humanresearchroadmap.nasa.gov/evidence/. Interested applicants are encouraged to contact NASA for more information about the NASA risks and research gaps in the Human Research Roadmap of the Human Research Program.

The National Science Foundation (NSF) is the only federal agency dedicated to the support of basic research and education across all fields of science and engineering, in fulfillment of its statutory mission to promote the progress of science; to advance the national health, prosperity, and welfare; and to secure the national defense. Participating NSF components are interested in supporting research at the interfaces of the life sciences, computational sciences, mathematical and physical sciences, and engineering to accelerate understanding of biological and biomedical systems. Advances in methods and tools for predictive modeling, simulation, and analysis of emergent behavior in complex multiscale systems are of interest, including the issues of verification, validation, and uncertainty quantification across scales. Advances in data-analysis techniques and tools that are relevant to these systems are also of interest, in particular for impact on the data deluge.

The Office of Naval Research (ONR) Mathematics, Computer and Information Sciences Division is interested in predictive multiscale modeling including information representation and discovery, information integration, and decision making under uncertainty. Decision making may necessitate inference of intents or high-level cognitive tasks. To this end, basic research is needed to formulate a rigorous foundation for a computational framework that can implement high-level reasoning, via quantitative or qualitative methods, which can cope with newly acquired information and a myriad of variations in operational environments. Of particular interest is development of principled approaches for the analysis of high-dimensional data, including large-scale graphs such as biological networks.

The National Heart, Lung, and Blood Institute (NHLBI) is interested in supporting innovative modeling methods and experimental approaches to facilitate predictive multiscale models of the physiology and pathophysiology of the cardiovascular, pulmonary, hematological and sleep systems.

The National Center for Complementary and Integrative Health (NCCIH) is interested in supporting the development of innovative predictive models related to the mechanisms of complementary and integrative approaches, including natural products and mind and body interventions, in human subjects or appropriate model systems. Randomized clinical trials to validate the predictive models in humans are not supported by this FOA and should seek other funding mechanisms supported by the NCCIH. Examples of research topics include but are not limited to:

• Multiscale models related to predictive and/or modifiable mechanisms of natural products or mind and body approaches (i.e. spinal manipulation or mobilization, massage, tai chi, qi gong, yoga, acupuncture, hypnosis, meditation, biofeedback or mindfulness techniques) for pain management.
• Multiscale models related to predictive and/or modifiable mechanisms of mind and body approaches (i.e. spinal manipulation or mobilization, massage, tai chi, qi gong, yoga, acupuncture, hypnosis, meditation, biofeedback or mindfulness techniques) for post-traumatic stress (disorder), sleep disorders or disturbances, anxiety, or depression.
• Multi-scale modeling research for preventative strategies that links genetics, molecular mechanisms, intracellular signaling, brain circuits, and/or environment with responders and non-responders of complementary interventions (i.e. acupuncture, mindfulness, yoga, natural products, etc.) and/or integrative health interventions.
• Models to predict the systems level biological activity of natural products, especially in the context of complex natural product mixtures as is common in traditional systems of medicine
• Multi-scale models and computational approaches of mechanistic pathways and regulatory networks in probiotic/prebiotic and microbiota-brain-gut interactions and related bio-behavioral networks that can be used consistently in unifying multi-scale frameworks (e.g., neural-hormonal biological systems and microecological principles that promote homeostasis or disease)

NIH grants policies as described in the NIH Grants Policy Statement will apply to the applications submitted and awards made in response to this FOA.

Higher Education Institutions

• Public/State Controlled Institutions of Higher Education
• Private Institutions of Higher Education

The following types of Higher Education Institutions are always encouraged to apply for NIH support as Public or Private Institutions of Higher Education:

• Hispanic-serving Institutions
• Historically Black Colleges and Universities (HBCUs)
• Tribally Controlled Colleges and Universities (TCCUs)
• Alaska Native and Native Hawaiian Serving Institutions
• Asian American Native American Pacific Islander Serving Institutions (AANAPISIs)

Nonprofits Other Than Institutions of Higher Education

• Nonprofits with 501(c)(3) IRS Status (Other than Institutions of Higher Education)
• Nonprofits without 501(c)(3) IRS Status (Other than Institutions of Higher Education)

For-Profit Organizations

• Small Businesses
• For-Profit Organizations (Other than Small Businesses)

Governments

• State Governments
• County Governments
• City or Township Governments
• Special District Governments
• Indian/Native American Tribal Governments (Federally Recognized)
• Indian/Native American Tribal Governments (Other than Federally Recognized)
• Eligible Agencies of the Federal Government
• U.S. Territory or Possession

Other

• Independent School Districts
• Public Housing Authorities/Indian Housing Authorities
• Native American Tribal Organizations (other than Federally recognized tribal governments)
• Faith-based or Community-based Organizations
• Regional Organizations
• Non-domestic (non-U.S.) Entities (Foreign Institutions)

Non-domestic (non-U.S.) Entities (Foreign Institutions) are eligible to apply.
Non-domestic (non-U.S.) components of U.S. Organizations are eligible to apply.
Foreign components, as defined in the NIH Grants Policy Statement, are allowed.

Applicant Organizations

Applicant organizations must complete and maintain the following registrations as described in the SF 424 (R&R) Application Guide to be eligible to apply for or receive an award. All registrations must be completed prior to the application being submitted. Registration can take 6 weeks or more, so applicants should begin the registration process as soon as possible. The NIH Policy on Late Submission of Grant Applications states that failure to complete registrations in advance of a due date is not a valid reason for a late submission.

• Dun and Bradstreet Universal Numbering System (DUNS) - All registrations require that applicants be issued a DUNS number. After obtaining a DUNS number, applicants can begin both SAM and eRA Commons registrations. The same DUNS number must be used for all registrations, as well as on the grant application.
• System for Award Management (SAM) (formerly CCR) Applicants must complete and maintain an active registration, which requires renewal at least annually. The renewal process may require as much time as the initial registration. SAM registration includes the assignment of a Commercial and Government Entity (CAGE) Code for domestic organizations which have not already been assigned a CAGE Code.
  • NATO Commercial and Government Entity (NCAGE) Code Foreign organizations must obtain an NCAGE code (in lieu of a CAGE code) in order to register in SAM.
• eRA Commons - Applicants must have an active DUNS number and SAM registration in order to complete the eRA Commons registration. Organizations can register with the eRA Commons as they are working through their SAM or Grants.gov registration. eRA Commons requires organizations to identify at least one Signing Official (SO) and at least one Program Director/Principal Investigator (PD/PI) account in order to submit an application.
• Grants.gov Applicants must have an active DUNS number and SAM registration in order to complete the Grants.gov registration.

Program Directors/Principal Investigators (PD(s)/PI(s))

All PD(s)/PI(s) must have an eRA Commons account. PD(s)/PI(s) should work with their organizational officials to either create a new account or to affiliate their existing account with the applicant organization in eRA Commons. If the PD/PI is also the organizational Signing Official, they must have two distinct eRA Commons accounts, one for each role. Obtaining an eRA Commons account can take up to 2 weeks.

Any individual(s) with the skills, knowledge, and resources necessary to carry out the proposed research as the Program Director(s)/Principal Investigator(s) (PD(s)/PI(s)) is invited to work with his/her organization to develop an application for support. Individuals from underrepresented racial and ethnic groups as well as individuals with disabilities are always encouraged to apply for NIH support.

For institutions/organizations proposing multiple PDs/PIs, visit the Multiple Program Director/Principal Investigator Policy and submission details in the Senior/Key Person Profile (Expanded) Component of the SF424 (R&R) Application Guide.

This FOA does not require cost sharing as defined in the NIH Grants Policy Statement.

Applicant organizations may submit more than one application, provided that each application is scientifically distinct.

The NIH will not accept duplicate or highly overlapping applications under review at the same time. This means that the NIH will not accept:

• A new (A0) application that is submitted before issuance of the summary statement from the review of an overlapping new (A0) or resubmission (A1) application.
• A resubmission (A1) application that is submitted before issuance of the summary statement from the review of the previous new (A0) application.
• An application that has substantial overlap with another application pending appeal of initial peer review (see NOT-OD-11-101).

In addition, the NIH will not accept a resubmission (A1) application that is submitted later than 37 months after submission of the new (A0) application that it follows. The NIH will accept submission:

• To an RFA of an application that was submitted previously as an investigator-initiated application but not paid;
• Of an investigator-initiated application that was originally submitted to an RFA but not paid; or
• Of an application with a changed grant activity code.

Applicants must download the SF424 (R&R) application package associated with this funding opportunity using the Apply for Grant Electronically button in this FOA or following the directions provided at Grants.gov.

It is critical that applicants follow the instructions in the SF424 (R&R) Application Guide, including Supplemental Grant Application Instructions except where instructed in this funding opportunity announcement to do otherwise. Conformance to the requirements in the Application Guide is required and strictly enforced. Applications that are out of compliance with these instructions may be delayed or not accepted for review.

For information on Application Submission and Receipt, visit Frequently Asked Questions Application Guide, Electronic Submission of Grant Applications.

A Letter of Intent is strongly encouraged. Although a letter of intent is not required, is not binding, and does not enter into the review of a subsequent application, the information that it contains allows IC staff to estimate the potential review workload and plan the review.

By the date listed in Part 1. Overview Information, prospective applicants are asked to submit a letter of intent that includes the following information:

• Descriptive title of proposed activity
• Name(s), address(es), and telephone number(s) of the PD(s)/PI(s)
• Names of other key personnel
• Participating institution(s)
• Number and title of this funding opportunity

The letter of intent should be sent to:

Grace C.Y. Peng, Ph.D.
Telephone: 301-451-4778
Fax: 301-480-1614
Email: grace.peng@nih.gov

All page limitations described in the SF424 Application Guide and the Table of Page Limits must be followed.

The following section supplements the instructions found in the SF424 (R&R) Application Guide and should be used for preparing an application to this FOA.

All instructions in the SF424 (R&R) Application Guide must be followed.

All instructions in the SF424 (R&R) Application Guide must be followed.

All instructions in the SF424 (R&R) Application Guide must be followed.

Other Attachments:

All Applicants must include the following separate attachments:

• MSM Consortium Plan
• Model Credibility Plan
• Broader Impacts statement
• Data Management Plan

MSM Consortium Plan (limited to one page)

As a cooperative agreement, investigators are required describe in a "MSM Consortium Plan" how this project will contribute to the IMAG-MSM Consortium activities, describing specific milestones and timeline of participation within the MSM Consortium, involving community input in order for the MSM Consortium plan to succeed (e.g. developing standards, curriculum, opinion papers, etc.). The key investigators are expected to take an active role in the MSM Consortium, co-leading one or more working groups for a minimum of two years during the award period, planning and participating in the annual MSM Consortium meetings, and sharing data, models, expertise, and other efforts to contribute to the greater multiscale modeling community as appropriate and consistent with achieving the goals of this program (See Section VI Cooperative Agreement Terms and Conditions). Applicants are encouraged to look at current and past MSM Consortium activities on the IMAG wiki, www.imagwiki.nibib.nih.gov. Investigators must devote personnel and effort to work towards the proposed MSM Plan goals during the proposed project period.

In the body of the text, begin the section with a heading indicating MSM Consortium Plan . When saving this file for uploading, name it MSM Consortium Plan .

Applications lacking the MSM Consortium Plan component or exceeding the one-page limit will not undergo peer review.

Model Credibility Plan (limited to one page)

All applicants should outline strategies and metrics for evaluating the credibility of the proposed multiscale model(s) to address the question(s) of interest within the intended domain of application in biomedical, biological, behavioral, environmental or clinical research. This would typically include, but not be restricted to, performing verification, validation, uncertainty quantification and sensitivity analysis, as well as documenting model limitations. Under circumstances where it may be impractical to perform verification, validation, uncertainty quantification and/or sensitivity analysis, applicants are encouraged to substantiate: (1) why it is impractical; and (2) where appropriate, propose alternative methods and metrics that can help build confidence in the model's predictive capabilities for the intended domain of use.

The credibility assessment methods and metrics used may be both qualitative and/or quantitative; and should be accessible for use by a third party not on the proposed project team. Through the terms and conditions of the cooperative agreement (Section VI), the investigators will work with the IMAG project scientists to identify appropriate groups in the MSM Consortium to perform an independent evaluation of the multiscale model as it is being developed. Applicants are encouraged to provide a timeline and personnel effort needed for model evaluation. Applicants should use this plan to substantiate why the proposed methods and metrics are appropriate to establish sufficient confidence in the multiscale model(s) to answer the research questions of interest.

In the body of the text, begin the section with a heading indicating Model Credibility Plan . When saving this file for uploading, name it Model Credibility Plan .

Applications lacking the Model Credibility Plan or exceeding the one-page limit will not undergo peer review.

Broader Impacts Statement (limited to one page)

Broader Impacts encompasses the potential to benefit society and contribute to the achievement of specific, desired societal outcomes. Broader impacts may be accomplished through the research itself, through the activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project. IMAG values the advancement of scientific knowledge and activities that contribute to achievement of societally relevant outcomes. Such outcomes include, but are not limited to: full participation of women, persons with disabilities, and underrepresented minorities in science, technology, engineering, and mathematics (STEM); improved STEM education and educator development at any level; increased public scientific literacy and public engagement with science and technology; improved well-being of individuals in society; development of a diverse, globally competitive STEM workforce; increased partnerships between academia, industry, and others; improved national security; increased economic competitiveness of the United States; and enhanced infrastructure for research and education. Indicate the mentoring activities provided to postdoctoral researchers supported on the project.

In the body of the text, begin the section with a heading indicating Broader Impacts. When saving this file for uploading, name it Broader Impacts.

Applications lacking the Broader Impacts Statement or exceeding the one-page limit will not undergo peer review.

Data Management Plan (limited to two pages)

Applicants must describe the plans for data management. For further details, see the NSF Grant Proposal Guide, Chapter II.C.2.j, second bullet. The Data Management Plan may include:

• the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project;
• the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies);
• policies and provisions for re-use, re-distribution, and the production of derivatives; and
• plans for archiving data, samples, and other research products, and for preservation of access to them.

A valid Data Management Plan may include only the statement that no detailed plan is needed, as long as the statement is accompanied by a clear justification.

In the body of the text, begin the section with a heading indicating Data Management Plan. When saving this file for uploading, name it Data Management Plan.

Applications lacking the Data Management Plan or exceeding the two-page limit will not undergo peer review.

All instructions in the SF424 (R&R) Application Guide must be followed.

All instructions in the SF424 (R&R) Application Guide must be followed.

Applicants to this FOA are required to allocate funds for the following:

1) to pursue collaborative efforts, through the MSM Consortium Plan, that can only be achieved through MSM community input;

2) to allow at least two key investigators with complementary expertise to travel to the annual MSM Consortium Meetings;

3) to implement the third party evaluation, as proposed in their Model Credibility Plan;

4) to budget for and plan model repositories, and appropriate software engineering efforts.

All instructions in the SF424 (R&R) Application Guide must be followed.

All instructions in the SF424 (R&R) Application Guide must be followed.

All instructions in the SF424 (R&R) Application Guide must be followed, with the following additional instructions:

Research Strategy:

Investigators should to identify a compelling multiscale problem or approach that is currently not being addressed - that is, beyond current practice - and address its impact on the field. If investigators are expanding an existing model the existing model must address a new breakthrough challenge in multiscale modeling. Investigators are encouraged to use the bullets in Section I, or similar challenges to identify their problem. Investigators must clearly explain how their model is multiscale.

The proposed multiscale model must incorporate substantial representations of the underlying biological or behavioral mechanisms and processes from at least two scales and at least one linkage between scales. These multiscale models may also include dynamical processes which span multiple time and spatial scales or levels of aggregation. Different levels of aggregation are important to a wide range of social, behavioral, and population modeling.

Investigators should provide rationale for the predictive aspects of the proposed multiscale model. Investigators are required to provide a convincing technical plan (approach) for achieving predictive outcomes from the proposed multiscale model. Predictive models generate new hypotheses, and do not merely recapitulate the data that were used to build them. Challenges to predictive multiscale modeling arise as a result of our limited understanding of the complex, dynamic nature of the biological or behavioral system, the availability of and limited access to good quality data, and the difficulties involved in understanding, communicating, and sharing modeling methods among multiple disciplines. It may be beneficial to use both bottom-up and top-down approaches to multiscale modeling to facilitate the development of predictive models. In the Model Credibility Plan, investigators are required to describe the methods and metrics that can help establish confidence in the model's predictive capabilities for the intended domain of use.

The data used to develop the model must be identified and appropriately justified for each scale and link modeled. Parameter estimation and model validation should be based on experimental and/or observational data as appropriate. IMAG strongly encourages the use of secondary datasets where possible. If new data are collected, the collection must be justified for the development of the model. As a supplemental resource, the NIH has established a Common Data Element (CDE) Resource Portal" (http://cde.nih.gov/) to assist investigators in identifying NIH-supported CDEs when developing protocols, case report forms, and other instruments for data collection. The creation of standard datasets is strongly encouraged. As a part of the IMAG/MSM Consortium (www.imagwiki.nibib.nih.gov) funded investigators of this FOA will interact with this community of modelers to further promote data sharing and scientific collaboration as appropriate and consistent with achieving the goals of this program.

Investigators should clearly describe the model architecture and highlight aspects of the architecture which will facilitate future model sharing. Models must be designed so that components or modules within the models are clearly documented and can be independently and explicitly reproduced by and shared with other modelers as appropriate and consistent with achieving the goals of this program.

Investigators should propose plans to link proposed models with other relevant models (See instructions below for Plan for Sharing Models and Software). As a part of the IMAG/MSM Consortium (www.imagwiki.nibib.nih.gov), funded investigators of this FOA will interact with this community of modelers to further promote model sharing and scientific collaboration as appropriate and consistent with achieving the goals of this program. Investigators are strongly encouraged to employ standardized ontologies and languages for model representation where appropriate (e.g. domain-specific Extensible Markup Language (XML)-based model representations such as SBML and CellML). The benefits of software engineering practices are expected to include, but are not limited to, model reproducibility, improved functionality by linking disparate but scientifically appropriate software, reduction of redundant software efforts, efficient software reuse, and improvement in quality of software by opening the development process to more scientists.

Investigators must include specific milestones and timeline of scientific progress and MSM Consortium participation.

Investigators should reach out to other experts to further complement their expertise, and indicate the type of partnership that will be achieved in the proposed project, and how this partnership will address the particular goals and future impact of the proposed model. This FOA encourages highly interactive partnerships that strongly integrate diverse expertise to further increase the impact of multiscale models in the broader research and policy community, see examples of partnerships in Section I.

Resource Sharing Plan: Individuals are required to comply with the instructions for the Resource Sharing Plans as provided in the SF424 (R&R) Application Guide, with the following modification:

• All applications submitted for the January 25, 2015, due date or after are expected to comply with the NIH Genomic Data Sharing Policy as detailed in NOT-OD-14-111, as applicable.
• All applications, regardless of the amount of direct costs requested for any one year, should address a Data Sharing Plan and a Plan for Sharing Models and Software. The plans may include policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
  
• Plan for Sharing Models and Software: In the body of the text, begin the section with a heading indicating Plan for Sharing Models and Software.
• All applicants are expected to include a plan for sharing the models proposed in their grant application consistent with achieving the goals of this program. Detailed sharing plans should be provided for the model components or modules, modeling parameters and associated datasets. The plan should include the minimum requirements for model documentation, model building, model validation and model reproducibility. Applicants are also expected to include plans to link proposed models with other relevant models. Applicants are strongly encouraged to make their models electronically available in synchrony with paper publication. Investigators are expected to include appropriate data, model and software sharing plans to collaborate with others not on the investigative team and allow others external to the investigative team to reproduce, test, validate, reuse and extend the models.
• A software dissemination plan, with appropriate timelines, is expected to be included in the application. There is no prescribed single license for software produced through grants responding to this announcement. However, this FOA includes goals for software dissemination, and reviewers will be instructed to evaluate dissemination plans relative to these goals:
• The software should be freely available to biomedical, biological, behavioral, environmental, and clinical researchers and educators in the non-profit sector, such as institutions of education, research institutions, and government laboratories.
• The terms of software availability should permit the commercialization of enhanced or customized versions of the software, or incorporation of the software or pieces of it into other software packages.
• To preserve utility to the community, the software should be transferable such that another individual or team can reproduce the model and continue development in the event that the original investigators are unwilling or unable to do so.
• The terms of software availability should include the ability of researchers to modify the source code and to share modifications with other colleagues. An applicant should take responsibility for creating the original and subsequent official versions of a piece of software, and should provide a plan to manage the dissemination or adoption of improvements or customizations of that software by others. This plan should include a method to distribute other user's contributions such as extensions, compatible modules, or plug-ins.

Appendix: Do not use the Appendix to circumvent page limits. Follow all instructions for the Appendix as described in the SF424 (R&R) Application Guide.

When conducting clinical research, follow all instructions for completing Planned Enrollment Reports as described in the SF424 (R&R) Application Guide.

When conducting clinical research, follow all instructions for completing Cumulative Inclusion Enrollment Report as described in the SF424 (R&R) Application Guide.

Foreign (non-U.S.) institutions must follow policies described in the NIH Grants Policy Statement, and procedures for foreign institutions described throughout the SF424 (R&R) Application Guide.

Part I. Overview Information contains information about Key Dates. Applicants are encouraged to submit applications before the due date to ensure they have time to make any application corrections that might be necessary for successful submission.

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date. If a Changed/Corrected application is submitted after the deadline, the application will be considered late.

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

Information on the submission process and a definition of on-time submission are provided in the SF424 (R&R) Application Guide.

This initiative is not subject to intergovernmental review.

All NIH awards are subject to the terms and conditions, cost principles, and other considerations described in the NIH Grants Policy Statement.

Pre-award costs are allowable only as described in the NIH Grants Policy Statement.

Applications must be submitted electronically following the instructions described in the SF424 (R&R) Application Guide. Paper applications will not be accepted.

Applicants must complete all required registrations before the application due date. Section III. Eligibility Information contains information about registration.

For assistance with your electronic application or for more information on the electronic submission process, visit Applying Electronically. If you encounter a system issue beyond your control that threatens your ability to complete the submission process on-time, you must follow the Guidelines for Applicants Experiencing System Issues.

Important reminders:

All PD(s)/PI(s) must include their eRA Commons ID in the Credential field of the Senior/Key Person Profile Component of the SF424(R&R) Application Package. Failure to register in the Commons and to include a valid PD/PI Commons ID in the credential field will prevent the successful submission of an electronic application to NIH. See Section III of this FOA for information on registration requirements.

The applicant organization must ensure that the DUNS number it provides on the application is the same number used in the organization’s profile in the eRA Commons and for the System for Award Management. Additional information may be found in the SF424 (R&R) Application Guide.

See more tips for avoiding common errors.

Applicants interested in DOE funding

Applicants interested in DOE funding may wish to use the September due dates. Applications to the January and May due dates will be accepted and reviewed, but funding decisions from DOE will not be made until the end of September the following year.

Upon receipt, applications will be evaluated for completeness and compliance with application instructions by the Center for Scientific Review, NIH. Applications that are incomplete or non-compliant will not be reviewed.

Applicants are required to follow our Post Submission Application Materials policy.

Only the review criteria described below will be considered in the review process. As part of the NIH mission, all applications submitted to the NIH in support of biomedical and behavioral research are evaluated for scientific and technical merit through the NIH peer review system.

Reviewers will provide an overall impact score to reflect their assessment of the likelihood for the project to exert a sustained, powerful influence on the research field(s) involved, in consideration of the following review criteria and additional review criteria (as applicable for the project proposed).

Reviewers will consider each of the review criteria below in the determination of scientific merit, and give a separate score for each. An application does not need to be strong in all categories to be judged likely to have major scientific impact. For example, a project that by its nature is not innovative may be essential to advance a field.

Does the project address an important problem or a critical barrier to progress in the field? If the aims of the project are achieved, how will scientific knowledge, technical capability, and/or clinical practice be improved? How will successful completion of the aims change the concepts, methods, technologies, treatments, services, or preventative interventions that drive this field?

Have the investigators identified a compelling multiscale problem or approach that is currently not being addressed, i.e. beyond current practice? Does the project provide a strong rationale for the predictive aspects of the proposed multiscale model?

Are the PD(s)/PI(s), collaborators, and other researchers well suited to the project? If Early Stage Investigators or those in the early stages of independent careers, do they have appropriate experience and training? If established, have they demonstrated an ongoing record of accomplishments that have advanced their field(s)? If the project is collaborative or multi-PD/PI, do the investigators have complementary and integrated expertise; are their leadership approach, governance and organizational structure appropriate for the project?

To what degree have the investigators brought together diverse experts to further complement their expertise? How will this partnership address the particular goals and future impact of the proposed model?

Does the application challenge and seek to shift current research or clinical practice paradigms by utilizing novel theoretical concepts, approaches or methodologies, instrumentation, or interventions? Are the concepts, approaches or methodologies, instrumentation, or interventions novel to one field of research or novel in a broad sense? Is a refinement, improvement, or new application of theoretical concepts, approaches or methodologies, instrumentation, or interventions proposed?

If the application is building upon an existing model, are the investigators using the existing model to address a breakthrough challenge in multiscale modeling?

Are the overall strategy, methodology, and analyses well-reasoned and appropriate to accomplish the specific aims of the project? Are potential problems, alternative strategies, and benchmarks for success presented? If the project is in the early stages of development, will the strategy establish feasibility and will particularly risky aspects be managed?

If the project involves human subjects and/or NIH-defined clinical research, are the plans to address 1) the protection of human subjects from research risks, and 2) inclusion (or exclusion) of individuals on the basis of sex/gender, race, and ethnicity, as well as the inclusion or exclusion of children, justified in terms of the scientific goals and research strategy proposed?

Does the proposed multiscale model incorporate substantial representations of the underlying biological or behavioral mechanisms and processes from at least two scales AND at least one linkage between scales? Does the project provide a convincing technical plan for achieving predictive outcomes from the proposed multiscale model? To what degree does the project include the development of models that can be explicitly shared with other modelers? To what degree does the proposed model architecture, model components or modules, modeling parameters and associated datasets facilitate model reproducibility and sharing? Is the data collection justified for the model development, and will the data be standardized? Are the proposed milestones and timeline feasible for the proposed work?

Will the scientific environment in which the work will be done contribute to the probability of success? Are the institutional support, equipment and other physical resources available to the investigators adequate for the project proposed? Will the project benefit from unique features of the scientific environment, subject populations, or collaborative arrangements?

As applicable for the project proposed, reviewers will evaluate the following additional items while determining scientific and technical merit, and in providing an overall impact score, but will not give separate scores for these items.

MSM Consortium Plan

Is the MSM Consortium Plan feasible and appropriate for this project? Have the investigators devoted an adequate amount of personnel and effort to contribute meaningfully to the MSM Consortium? Are the milestones, timeline and budget appropriate for active participation within the MSM consortium? Will the activities and efforts proposed in the plan contribute to the greater multiscale modeling community? Have the investigators proposed co-leading an existing MSM Working Group, or proposed new Working Groups to co-lead?

Model Credibility Plan

Is the Model Credibility Plan feasible and appropriate for this project? To what degree will the proposed credibility assessment methods and metrics establish confidence in the model's predictive capabilities for the intended domain of use? Are the proposed timeline and budget appropriate for model evaluation by a third party?

Broader Impacts

What is the potential for the proposed activity to benefit society or advance desired societal outcomes? To what extent do the proposed activities suggest and explore creative, original, or potentially transformative concepts? Is the plan for carrying out the proposed activities well-reasoned, well-organized, and based on a sound rationale? Does the plan incorporate a mechanism to assess success? How well qualified is the individual, team, or organization to conduct the proposed activities? Are there adequate resources available to the PD/PI (either at the home organization or through collaborations) to carry out the proposed activities? Are appropriate mentoring activities provided to postdoctoral researchers supported on the project?

Data Management Plan

To what degree does the Data Management Plan meet the relevant scientific community’s standards for data management?

For research that involves human subjects but does not involve one of the six categories of research that are exempt under 45 CFR Part 46, the committee will evaluate the justification for involvement of human subjects and the proposed protections from research risk relating to their participation according to the following five review criteria: 1) risk to subjects, 2) adequacy of protection against risks, 3) potential benefits to the subjects and others, 4) importance of the knowledge to be gained, and 5) data and safety monitoring for clinical trials.

For research that involves human subjects and meets the criteria for one or more of the six categories of research that are exempt under 45 CFR Part 46, the committee will evaluate: 1) the justification for the exemption, 2) human subjects involvement and characteristics, and 3) sources of materials. For additional information on review of the Human Subjects section, please refer to the Guidelines for the Review of Human Subjects.

When the proposed project involves human subjects and/or NIH-defined clinical research, the committee will evaluate the proposed plans for the inclusion (or exclusion) of individuals on the basis of sex/gender, race, and ethnicity, as well as the inclusion (or exclusion) of children to determine if it is justified in terms of the scientific goals and research strategy proposed. For additional information on review of the Inclusion section, please refer to the Guidelines for the Review of Inclusion in Clinical Research.

The committee will evaluate the involvement of live vertebrate animals as part of the scientific assessment according to the following five points: 1) proposed use of the animals, and species, strains, ages, sex, and numbers to be used; 2) justifications for the use of animals and for the appropriateness of the species and numbers proposed; 3) adequacy of veterinary care; 4) procedures for limiting discomfort, distress, pain and injury to that which is unavoidable in the conduct of scientifically sound research including the use of analgesic, anesthetic, and tranquilizing drugs and/or comfortable restraining devices; and 5) methods of euthanasia and reason for selection if not consistent with the AVMA Guidelines on Euthanasia. For additional information on review of the Vertebrate Animals section, please refer to the Worksheet for Review of the Vertebrate Animal Section.

Reviewers will assess whether materials or procedures proposed are potentially hazardous to research personnel and/or the environment, and if needed, determine whether adequate protection is proposed.

For Resubmissions, the committee will evaluate the application as now presented, taking into consideration the responses to comments from the previous scientific review group and changes made to the project.

For Renewals, the committee will consider the progress made in the last funding period.

For Revisions, the committee will consider the appropriateness of the proposed expansion of the scope of the project. If the Revision application relates to a specific line of investigation presented in the original application that was not recommended for approval by the committee, then the committee will consider whether the responses to comments from the previous scientific review group are adequate and whether substantial changes are clearly evident.

As applicable for the project proposed, reviewers will consider each of the following items, but will not give scores for these items, and should not consider them in providing an overall impact score.

Reviewers will assess whether the project presents special opportunities for furthering research programs through the use of unusual talent, resources, populations, or environmental conditions that exist in other countries and either are not readily available in the United States or augment existing U.S. resources.

Reviewers will assess the information provided in this section of the application, including 1) the Select Agent(s) to be used in the proposed research, 2) the registration status of all entities where Select Agent(s) will be used, 3) the procedures that will be used to monitor possession use and transfer of Select Agent(s), and 4) plans for appropriate biosafety, biocontainment, and security of the Select Agent(s).

Reviewers will comment on whether the following Resource Sharing Plans, or the rationale for not sharing the following types of resources, are reasonable: 1) Data Sharing Plan; 2) Sharing Model Organisms; 3) Genomic Wide Association Studies (GWAS) /Genomic Data Sharing Plan, and:4) Model and Software Sharing Plan.

Model and software sharing plan:

Does the project include data, model and software sharing plans to collaborate with others who are not on the investigative team? If yes, to what degree? If not, is the reason justified?

Is the plan for sharing the model components or modules, modeling parameters and associated datasets conducive to successful sharing?

Do the sharing plans include minimum requirements for model documentation, parameter estimation, model building, model validation, and the use of effective software engineering where appropriate (i.e., evidence of open, collaborative, software development process that will lead to quality software)?

Will the sharing plans adequately allow others to reproduce, test, validate, reuse and extend the proposed models? If yes, to what degree? If not, is the reason justified?

Reviewers will consider whether the budget and the requested period of support are fully justified and reasonable in relation to the proposed research.

Applications will be evaluated for scientific and technical merit by (an) appropriate Scientific Review Group(s) convened by NIBIB, in accordance with NIH peer review policy and procedures, using the stated review criteria. Assignment to a Scientific Review Group will be shown in the eRA Commons.

As part of the scientific peer review, all applications:

• May undergo a selection process in which only those applications deemed to have the highest scientific and technical merit (generally the top half of applications under review) will be discussed and assigned an overall impact score.
• Will receive a written critique.

Summary statements and grant applications will be made available to the program officers at NIH, ARO, DOE, FDA, NASA, NSF, and ONR for funding decisions.

NSF program staff, when making funding decisions, will give due diligence to the following three merit review principles:

• All NSF projects should be of the highest quality and have the potential to advance, if not transform, the frontiers of knowledge.
• NSF projects, in the aggregate, should contribute more broadly to achieving societal goals. These "Broader Impacts" may be accomplished through the research itself, through activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project. The project activities may be based on previously established and/or innovative methods and approaches, but in either case must be well justified.
• Meaningful assessment and evaluation of NSF funded projects should be based on appropriate metrics, keeping in mind the likely correlation between the effect of broader impacts and the resources provided to implement projects. If the size of the activity is limited, evaluation of that activity in isolation is not likely to be meaningful. Thus, assessing the effectiveness of these activities may best be done at a higher, more aggregated, level than the individual project.

With respect to the third principle, even if assessment of Broader Impacts outcomes for particular projects is done at an aggregated level, PDs/PIs are expected to be accountable for carrying out the activities described in the funded project. Thus, individual projects should include clearly stated goals, specific descriptions of the activities that the PD/PI intends to do, and a plan in place to document the outputs of those activities.

These three merit review principles provide the basis for the merit review criteria, as well as a context within which the users of the criteria can better understand their intent. When evaluating NSF proposals, reviewers will be asked to consider what the proposers want to do, why they want to do it, how they plan to do it, how they will know if they succeed, and what benefits could accrue if the project is successful.

Applications will be assigned initially on the basis of established PHS referral guidelines to the appropriate NIH Institute or Center. Applications will compete for available funds with all other recommended applications. Following initial peer review, recommended applications will receive a second level of review by the appropriate national Advisory Council or Board. The following will be considered in making funding decisions:

• Scientific and technical merit of the proposed project as determined by scientific peer review.
• Availability of funds.
• Relevance of the proposed project to program priorities. Applications of interest to other funding agencies participating on this FOA will be considered jointly with the NIH.

After the peer review of the application is completed, the PD/PI will be able to access his or her Summary Statement (written critique) via the eRA Commons.

Information regarding the disposition of applications is available in the NIH Grants Policy Statement.

If the application is under consideration for funding, NIH will request "just-in-time" information from the applicant as described in the NIH Grants Policy Statement.

A formal notification in the form of a Notice of Award (NoA) will be provided to the applicant organization for successful applications. The NoA signed by the grants management officer is the authorizing document and will be sent via email to the grantee’s business official.

Awardees must comply with any funding restrictions described in Section IV.5. Funding Restrictions. Selection of an application for award is not an authorization to begin performance. Any costs incurred before receipt of the NoA are at the recipient's risk. These costs may be reimbursed only to the extent considered allowable pre-award costs.

Any application awarded in response to this FOA will be subject to terms and conditions found on the Award Conditions and Information for NIH Grants website. This includes any recent legislation and policy applicable to awards that is highlighted on this website.

All NIH grant and cooperative agreement awards include the NIH Grants Policy Statement as part of the NoA. For these terms of award, see the NIH Grants Policy Statement Part II: Terms and Conditions of NIH Grant Awards, Subpart A: General and Part II: Terms and Conditions of NIH Grant Awards, Subpart B: Terms and Conditions for Specific Types of Grants, Grantees, and Activities. More information is provided at Award Conditions and Information for NIH Grants.

Cooperative Agreement Terms and Conditions of Award

The following special terms of award are in addition to, and not in lieu of, otherwise applicable OMB administrative guidelines, HHS grant administration regulations at 45 CFR Parts 74 and 92 (Part 92 is applicable when State and local Governments are eligible to apply), and other HHS, PHS, and NIH grant administration policies.

The administrative and funding instrument used for this program will be the cooperative agreement, an "assistance" mechanism (rather than an "acquisition" mechanism), in which substantial IMAG programmatic involvement with the awardees is anticipated during the performance of the activities. Under the cooperative agreement, the IMAG purpose is to support and stimulate the recipients' activities by involvement in and otherwise working jointly with the award recipients in a partnership role; it is not to assume direction, prime responsibility, or a dominant role in the activities. Consistent with this concept, the dominant role and prime responsibility resides with the awardees for the project as a whole, although specific tasks and activities may be shared among the awardees and the IMAG as defined below.

The PD(s)/PI(s) will have the primary responsibility for:

The Principal Investigator will have the primary responsibility to define objectives and approaches, and to plan, conduct, analyze, and publish results, interpretations, and conclusions of their studies.

Awardees are responsible for identifying specific milestones and timeline for the scientific success of their multiscale model.

Awardees will join the MSM Consortium and are responsible for identifying specific milestones and timeline for their participation within the MSM Consortium, as described in their proposed MSM Consortium Plan. Awardees are expected to play an active role in the MSM Consortium, leading the working groups (WG), hosting webinars, and sharing data, models, expertise, and other efforts to contribute to the greater multiscale modeling community as appropriate and consistent with achieving the goals of this program. The PI(s) will serve as a WG co-lead(s) for a minimum of two years on one or more WGs during the award period (this can be on existing WGs or in forming new WGs). WGs are expected to host at minimum two webinars for the MSM each year. For Multiple PI awards, all PI’s must serve as co-leads on different WGs. Applicants to this FOA will use allocated funds for at least two key investigators with complementary expertise to travel to the annual MSM Consortium Meetings. Awardees are expected to use other allocated funds to actively participate in other MSM Consortium activities as proposed in the MSM Consortium Plan.

Awardees will report on project personnel involvement in the MSM as activities as they occur (e.g. through email with the assigned program officer), and in the annual progress report. Additionally, awardees will report on model credibility assessment, third party evaluation and sharing activities in the annual progress report.

Awardees will retain custody of and have primary rights to the data and software developed under these awards, subject to Government rights of access consistent with current HHS, PHS, and NIH policies.

NIH staff have substantial programmatic involvement that is above and beyond the normal stewardship role in awards, as described below:

IMAG program officials will serve as Project Scientists and will have substantial scientific-programmatic involvement during conduct of this activity, through technical assistance, advice, and coordination above and beyond normal program stewardship in awards, as described below.

Each project will have the support of one or more Project Scientists from IMAG who are assigned an administrative role for the multiscale modeling project.

The IMAG Project Scientists will be responsible for assessing the progress of the projects toward the accomplishment of specified milestones and contributions to the MSM Consortium through milestone performance reviews. Project Scientists will recommend if further funds should be released to the project.

The IMAG Project Scientists will recommend collaborations between awardees of the MSM Consortium and other persons or organizations whose participation will assist with the accomplishment of project goals, and third party model credibility evaluation. These persons or organizations may include other federal agencies, non-profit organizations, or commercial entities.

The IMAG Project Scientists will have a significant, although not dominant, role in the planning and execution of the supported activities. Through the cooperative agreement, IMAG Project Scientists will facilitate awardee participation in the MSM Consortium activities, serve as liaisons to the MSM working groups, participate in virtual discussions of the MSM, and meet on a monthly basis to discuss awardee contributions in the MSM.

An important aspect of IMAG is the coordination of a variety of research efforts across multiple funding agencies. IMAG will continue to update the MSM Consortium of new funding opportunities, and research activities promote the mission and coordination of the MSM Consortium.

Additionally, an agency program official or IC program director will be responsible for the normal scientific and programmatic stewardship of the award and will be named in the award notice.

Areas of Joint Responsibility include:

The awardees, together with IMAG and the MSM Consortium, will jointly agree upon the terms and conditions of the MSM Consortium Plan, the Model Credibility Plan, and the Plan for Sharing Models and Software as appropriate and consistent with achieving the goals of this program. They will jointly organize the annual in-person MSM Consortium meetings. These parties will identify the priority topics to be addressed each year, develop a meeting format that optimally addresses these topics, promote and attend these annual meetings during the duration of the funded project. All U01 Projects and IMAG agencies supporting the U01 projects will be represented at the annual MSM Consortium meeting. All U01 PI’s are expected to help shape the direction of the MSM Consortium and take an active role at the meeting.

Dispute Resolution:

Any disagreements that may arise in scientific or programmatic matters (within the scope of the award) between award recipients and the NIH may be brought to arbitration. An Arbitration Panel composed of three members will be convened. It will have three members: a designee of the Steering Committee chosen without NIH staff voting, one NIH designee, and a third designee with expertise in the relevant area who is chosen by the other two; in the case of individual disagreement, the first member may be chosen by the individual awardee. This special arbitration procedure in no way affects the awardee's right to appeal an adverse action that is otherwise appealable in accordance with PHS regulations 42 CFR Part 50, Subpart D and HHS regulations 45 CFR Part 16.

When multiple years are involved, awardees will be required to submit the Research Performance Progress Report (RPPR) annually and financial statements as required in the NIH Grants Policy Statement.

A final progress report, invention statement, and the expenditure data portion of the Federal Financial Report are required for closeout of an award, as described in the NIH Grants Policy Statement.

The Federal Funding Accountability and Transparency Act of 2006 (Transparency Act), includes a requirement for awardees of Federal grants to report information about first-tier subawards and executive compensation under Federal assistance awards issued in FY2011 or later. All awardees of applicable NIH grants and cooperative agreements are required to report to the Federal Subaward Reporting System (FSRS) available at www.fsrs.gov on all subawards over $25,000. See the NIH Grants Policy Statement for additional information on this reporting requirement.

We encourage inquiries concerning this funding opportunity and welcome the opportunity to answer questions from potential applicants.

eRA Service Desk (Questions regarding ASSIST, eRA Commons registration, submitting and tracking an application, documenting system problems that threaten submission by the due date, post submission issues)
Telephone: 301-402-7469 or 866-504-9552 (Toll Free)
Finding Help Online: https://grants.nih.gov/support/index.html
Email: commons@od.nih.gov

Grants.gov Customer Support (Questions regarding Grants.gov registration and submission, downloading forms and application packages)
Contact CenterTelephone: 800-518-4726
Email: support@grants.gov

GrantsInfo (Questions regarding application instructions and process, finding NIH grant resources)
Telephone: 301-945-7573
Email: GrantsInfo@nih.gov

Wen G. Chen, Ph.D.
National Center for Complementary and Integrative Health (NCCIH)
Telephone: 301-451-3989
Email: chenw@mail.nih.gov

Pankaj Qasba, Ph.D
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0070
Email: qasabap@nhlbi.nih.gov

Grace C.Y. Peng, Ph.D.
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Telephone: 301-451-4778
Email: grace.peng@nih.gov

Nicole Moore, Sc.D.
National Cancer Institute (NCI)
Telephone: 240-276-7624
Email: moorenm@mail.nih.gov

Michael J. Pazin, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 301-496-7531
f Email: pazinm@mail.nih.gov

Wen G. Chen, Ph.D.
National Institute on Aging (NIA)
Telephone: 301-496-9350
Email: chenw@mail.nih.gov

Gregory Bloss
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Telephone: 301-443-3865
Email: Gregory.Bloss@nih.gov

Division of Musculoskeletal Diseases
Gayle Lester, Ph.D.
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Telephone: 301-594-3511
Email: lester1@mail.nih.gov

Division of Skin and Rheumatic Diseases
Hung Tseng, Ph.D.
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Telephone: 301-594-5032)
Email: tsengh@mail.nih.gov

Regina M. Bures, PhD
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Email: buresrm@mail.nih.gov

Susan F. Volman, Ph.D.
National Institute on Drug Abuse (NIDA)
Telephone: 301-435-1315
Email: svolman@nida.nih.gov

Virginia B. Pasour, PhD
U.S. Army Research Office (ARO)
Telephone: 919-549-4254
Email: virginia.b.pasour.civ@mail.mil

Pablo Rabinowicz, Ph.D.
U.S. Department of Energy (DOE)
Telephone: 301-903-0379
Email: pablo.rabinowicz@science.doe.gov

Donna R. Lochner
Food and Drug Administration (FDA)
Telephone: 301-796-6309
Email: donna.lochner@fda.hhs.gov

Thomas Russell, Ph.D.
National Science Foundation (NSF)
Telephone: 703-292-4863
Email: trussell@nsf.gov

Directorate for Computer & Information Science & Engineering
Daniel S. Katz, Ph.D.
National Science Foundation (NSF - CISE)
Telephone: 703-292-2254
Email: dkatz@nsf.gov

Directorate for Engineering
Athanassios Sambanis
National Science Foundation (NSF - ENG)
Telephone: 703-292-2161
Email: asambani@nsf.gov

Directorate for Mathematical & Physical Sciences
Mary Ann Horn, Ph.D.
National Science Foundation (NSF - MPS)
Telephone: 703-292-4879
Email: mhorn@nsf.gov

Mark Shelhamer, ScD
National Aeronautics and Space Administration (NASA)
Telephone: 281-244-7330
Email: mark.j.shelhamer@nasa.gov

Pedja Neskovic, Ph.D.
Office of Naval Research (ONR)
Telephone: 703-696-4304
Email: predrag.neskovic@navy.mil

David Balshaw, PhD
National Institute of Environmental Health Sciences (NIEHS)
Telephone: 919-541-2448
Email: balshaw@niehs.nih.gov

David T. George, Ph.D.
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Telephone: 301-496-8633
Email: GeorgeD@nih.gov

Shelley Carow
National Center for Complementary and Integrative Health (NCCIH)
Telephone: 301-594-3788
Email: carows@mail.nih.gov

Ronald Calder
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0148
Email: caulderr@nhlbi.nih.gov

James Huff
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Telephone: 301-451-4782
Email: James.Huff1@nih.gov

Carol Perry
National Cancer Institute (NCI)
Telephone: 240-276-6282
Email: perryc@mail.nih.gov

Dave Ruane
National Human Genome Research Institute (NHGRI)
Telephone: 301-451-7928
Email: ruaned@mail.nih.gov

Robin Laney
National Institute on Aging (NIA)
Telephone: 301.496.1473
Email: Robin.Laney@nih.gov

Judy Fox
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Telephone: 301-443-4704
Email: jfox@mail.nih.gov

Mark Langer
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Telephone: 301-451-8216
Email: langerm@mail.nih.gov

Ted Williams
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
Email: williate@mail.nih.gov

Christine Kidd
National Institute on Drug Abuse (NIDA)
Telephone: 301-435-1372
Email: ckidd@nida.nih.gov

Lisa Edwards, MBA
National Institute of Environmental Health Sciences (NIEHS)
Telephone: 919-541-0751
Email: arcger@niehs.nih.gov

Recently issued trans-NIH policy notices may affect your application submission. A full list of policy notices published by NIH is provided in the NIH Guide for Grants and Contracts. All awards are subject to the terms and conditions, cost principles, and other considerations described in the NIH Grants Policy Statement.

Awards are made under the authorization of Sections 301 and 405 of the Public Health Service Act as amended (42 USC 241 and 284) and under Federal Regulations 42 CFR Part 52 and 45 CFR Parts 74 and 92.