Notice of NIH Participation in Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science
Notice Number:
NOT-OD-21-011

Key Dates

Release Date:

November 24, 2020

Related Announcements

NOT-OD-18-149 - National Science Foundation - National Institutes of Health NSF-NIH Interagency Initiative: Smart and Connected Health

Issued by

Office of The Director, National Institutes of Health (OD)

National Eye Institute (NEI)

National Heart, Lung, and Blood Institute (NHLBI)

National Human Genome Research Institute (NHGRI)

National Institute on Aging (NIA)

National Institute of Allergy and Infectious Diseases (NIAID)

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

National Institute of Biomedical Imaging and Bioengineering (NIBIB)

Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

National Institute on Deafness and Other Communication Disorders (NIDCD)

National Institute of Dental and Craniofacial Research (NIDCR)

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

National Institute on Drug Abuse (NIDA)

National Institute of Environmental Health Sciences (NIEHS)

National Institute of General Medical Sciences (NIGMS)

National Institute of Mental Health (NIMH)

National Institute of Neurological Disorders and Stroke (NINDS)

National Institute of Nursing Research (NINR)

National Institute on Minority Health and Health Disparities (NIMHD)

National Library of Medicine (NLM)

National Center for Complementary and Integrative Health (NCCIH)

National Cancer Institute (NCI)

All applications to this funding opportunity announcement should fall within the mission of the Institutes/Centers. The following NIH Offices may co-fund applications assigned to those Institutes/Centers.

Office of Behavioral and Social Sciences Research (OBSSR)

Purpose

The purpose of this Notice is to announce the collaboration between the NIH and the National Science Foundation (NSF) on an interagency funding opportunity, Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science. The initiative supports innovative, high-risk/high-reward research with the promise of disruptive transformations in biomedical research. Proposals submitted must make fundamental contributions to two or more disciplines, such as computer or information sciences, engineering, social, behavioral, biomedical, cognitive and/or economic sciences, to improve the fundamental understanding of biomedical and health related processes and address a key health problem.

The solicitation aims to address technological and data science challenges that require fundamental research and development of new tools, workflows and methods across many dimensions including, but not limited to, these six scientific themes: Information Infrastructure, Transformative Data Science and Artificial Intelligence, Novel Multimodal Sensor System Hardware, Effective Usability, Automating Health, and Medical Image Interpretation. Traditional disease-centric medical, clinical, pharmacological, biological or physiological studies and evaluations are outside the scope of this solicitation.

The general interests of the participating NIH Institute organizations are outlined below:

National Center for Complementary and Integrative Health (NCCIH)

NCCIH is committed to the rigorous investigation of complementary and integrative health approaches, which include mind and body approaches such as meditation, hypnosis, acupuncture, massage, spinal manipulation/mobilization, yoga, tai-chi, qigong, and music and art therapy, and natural products such as botanicals, probiotics, dietary supplements, and special diet to determine their usefulness, safety and biological mechanisms. Through this solicitation, NCCIH is particularly interested in research that advances technologies, analytics, and models of these complementary and integrative health approaches for the following applications:

  • Pain management
  • Improving sleep and reducing sleep disturbances
  • Reducing symptomatic conditions, such as those associated with menopause and chronic fatigue syndrome
  • Improving management of mental health conditions commonly managed in primary care such as mild to moderate depression or anxiety
  • Adopting and sustaining healthy behaviors such as healthy eating, smoking cessation, and physical activity
  • Promoting emotional well being

National Cancer Institute (NCI)

NCI leads, conducts, and supports cancer research across the nation to advance scientific knowledge and help all people live longer, healthier lives. Through this solicitation , NCI is interested in funding research centered on the use of smart and connected health technologies, analytics, and methods to facilitate the efficient and effective collection, interpretation, flow, and use of health information to improve cancer-related outcomes and decrease health disparities. Advances in technology, analytics, and modeling are needed to enhance outcomes across the continuum of care (prevention, early detection, treatment, survivorship, and end-of-life), throughout the lifespan, and among the general public, cancer survivors (i.e., those living with cancer and those free from cancer), and caregivers. Priorities include rigorous investigations that introduce novel approaches and/or address challenges to data standardization, validation, and integration across levels of analysis, data sources, patient populations, care contexts, and cancer risk behaviors (e.g., diet, physical activity, sun safety, tobacco and alcohol use, sleep and circadian dysfunction, adherence to cancer-related medical and behavioral regimens). In addition to these research priorities, NCI is building a portfolio focused on understanding the perceptual and cognitive processes underlying cancer image interpretation to improve the accuracy of cancer detection and diagnosis. NCI is particularly interested in research projects that:

  • Improve understanding of how connected health methods and technologies can optimize team performance between all members of the patient’s care team (inclusive of the patient and their caregivers) as co-producers of positive health outcomes across the continuum of cancer care (prevention, early detection, treatment, survivorship, and end-of-life).
  • Identify and test strategies to enhance cancer survivors’ engagement in their health care through smart and connected technologies, including symptom management, adverse events reporting and response during and after treatment, and surveillance of late effects.
  • Utilize new or existing home monitoring devices, digital tools, online/web-based platforms, wearables, and/or other technologies to: measure, monitor, and improve cancer-related behaviors across the care continuum, enhance equity and access to care, support clinical decision-making, and evaluate effects on cancer outcomes. This may include the use of technologies for monitoring sociodemographic, environmental, behavioral, cognitive, emotional, psychological, and physiological patterns to identify and predict cancer-related sequalae and outcomes.
  • Use human visual cognition studies to: 1) Inform the development and deployment of augmented reality, virtual reality, and/or 3D printing in surgical interventions; 2) Develop methods to mitigate or reduce inter- and intra-observer variability in cancer image interpretation, particularly for modalities with relatively high levels of variability (e.g., ultrasound); and 3) Develop new methods to study human performance in large digital image sets (e.g., whole slide imaging, 3D CT/MRI).

National Eye Institute (NEI)

NEI is interested in studies that improve the diagnosis, treatment and rehabilitation of individuals with diseases and disorders that affect the visual system. Areas of interest include but are not limited to: New technology, Data science, Informatics, Telemedicine, and Artificial Intelligence/ Deep Learning approaches aimed at advancing the mission of the Institute. Research aimed at improving eye and vision health in rural, inner-city and other underserved and at-risk populations is a high priority and of particular interest.

National Human Genome Research Institute (NHGRI)

NHGRI seeks to fund a broad range of research efforts in genomics data science, statistics, and bioinformatics relevant to either or both of basic or clinical genomic science, and broadly applicable to human health and disease. NHGRI plans to support genomics research through early stage development of innovative and scalable algorithms and analytical methodologies and approaches of high value to the basic and clinical genomics community. The proposed research should be enabling for genomics and be generalizable or broadly applicable across human diseases, biological systems and human health.

National Heart, Lung, and Blood Institute (NHLBI)

The NHLBI is interested in funding research that will accelerate research on precision medicine, clinical decision support, imaging processing/imaging genomics, biological functional annotation of genomic variants, system biology and cellular pathway network modeling, systems science, social determinants, human-centered technologies, artificial intelligence (AI)/machine learning/modeling, health disparities, global health, and implementation of clinical practice guidelines for heart, lung, blood, and sleep diseases. NHLBI will also support research on the influence or predict the incidence, prevalence, and outcomes of heart, lung, blood, and sleep disorders and related social and environmental determinants. NHLBI encourages research that:

  • Includes the training and career development component, particularly interdisciplinary training across biomedical and math/engineering fields.
  • Leverages the data generated by NHLBI programs, such as TOPMed, BioData Catalyst.
  • Uses technology to address health disparities, including low Socioeconomic Status (SES), rural vs. urban settings.

Applicants are strongly encouraged to consult NHLBI Scientific Research Contacts regarding the appropriateness of the planned data resource application to the NHLBI mission, scientific areas of interests, and programmatic priorities. NHLBI-defined programmatic needs, and the NHLBI Strategic Vision inform support of resources, long-term funding needs, and sustainability plans of proposed data resources.

National Institute on Aging (NIA)

NIA is interested in the development of technologies, analytics and models that utilize novel technologies and informatics approaches to understand mechanisms of aging and to improve older adults’ health. Through this solicitation , NIA is interested in funding research centered on the use of big data analytics and smart and connected health technologies, and methods to facilitate the efficient and effective collection, analysis, interpretation, flow, and use of health information to improve age-related outcomes, decrease health disparities and improve care delivery of older adults. Advances in technology, analytics, and modeling are needed to enhance outcomes across the continuum of care (monitoring, prevention, early detection of cognitive decline and other age related disease, treatment trajectory, and utilizing data to improve end-of-life care), and caregivers. Illustrative topic areas include:

  • Collection of data from sensors and application of artificial intelligence to enhance both preclinical and clinical trials and cohort studies;
  • Development and validation of clinical decision support tools that help physicians caring for older adult patients with multiple chronic conditions applying big data science approach;
  • Tools for older adult patient self-management of multiple chronic conditions, including integrating artificial intelligence algorithms to improve healthcare delivery and decision making;
  • Validation and assessment of various methods for assessing and monitoring financial activity, including evaluating scam awareness along older adults experiencing cognitive decline;
  • Data science and artificial intelligence approaches to obtain and analyze molecular and cellular data including from human or animal studies (including laboratory and wild-populations) to identify novel biological mechanisms of aging;
  • Design of technological platforms that identify early, midlife and late hallmarks of aging in human or animal studies;
  • Development of platforms incorporating system biology approaches across species for identifying interactions among hallmarks of aging;
  • Validation and assessment of appropriate user interfaces (e.g., on smart devices) to assist older Americans in health decision making as they face cognitive decline;
  • Development of innovative monitoring technologies relevant to gerontology, including applications of artificial intelligence and machine learning, whose results would be suitable for inclusion in the electronic health records of older adults;
  • Integration of cognitive instruments and other digital biomarkers with electronic health records for early detection of cognitive decline or monitoring of outcomes at point-of-care;
  • Development of socially assistive robots to provide cognitive therapy using artificial intelligence, in-place monitoring, and/or assistance and care coordination for individuals with dementia and their caregivers;
  • Design and modification of technology by incorporating artificial intelligence applications into human factors problems/design associated with aging;
  • Development of applications that incorporate artificial intelligence approaches and behavioral economics principles to assist care providers, caregivers, or older individuals;
  • Integrate data science and artificial intelligence approaches to develop and modify current technology platforms to enable delivery of appropriate care for older adults and individuals experiencing cognitive impairment and dementia, including management of common comorbid conditions; and
  • Design of technological platforms that identify early biomarkers for functional and cognitive changes and assess the impact of intervening health events on the quality of life, well-being, and health status of older Americans.

All applicants, regardless of area of focus, need to clearly articulate how application of artificial intelligence and technology will mitigate health disparities (i.e., training databases should be adequately powered across race/ethnicity/gender), this can include improving access and delivery of care in rural areas. NIA welcomes applications aligned with NIA’s strategic mission (See: https://www.nia.nih.gov/sites/default/files/2020-05/nia-strategic-directions-2020-2025.pdf). Applications addressing topics related to Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD) are strongly encouraged.

National Institute of Allergy and Infectious Diseases (NIAID)

NIAID is interested in funding Smart & Connected Health projects that align with NIAID’s mission to better understand, treat, and prevent infectious diseases, immune-mediated diseases including allergy, autoimmunity, and immune reactions associated with transplantations. Such research may include but is not limited to basic and applied projects that:

  • Develop remote and non-invasive technologies to enable detection and diagnosis of infectious diseases at the point of need and point of care;
  • Innovate in biomedical imaging, including AI approaches for clinical interpretation;
  • Demonstrate effective use of data science to address health disparities;
  • Expand training and expertise in data science;
  • Monitor infectious diseases and/or microbiome at home and in health-care settings;
  • Assist in ensuring drug adherence for antibiotics and antivirals.

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

NIAMS is interested in applications proposing to develop technologies, analytics, and models that will advance research into the causes, treatment, prevention, and socio-behavioral aspects of arthritis, musculoskeletal, and skin diseases. Additionally, NIAMS is interested in similar applications aimed at enhancing basic research on the normal structure and function of bones, joints, muscles, and skin. NIAMS will not support clinical trials through this FOA.

National Institute of Biomedical Imaging and Bioengineering (NIBIB)

The mission of NIBIB is to improve health by leading the development and accelerating the application of biomedical technologies. NIBIB has broad interests in the development of biomedical technologies to improve human health and address health disparities. Program areas of particular relevance include: data science and health information technologies, telehealth, mHealth, point-of-care technologies, medical image interpretation or perception, medical data/image visualization, artificial intelligence, machine learning and deep learning, clinical decision support system, rehabilitation engineering, robotics, and next generation predictive models. The Institute is interested in the development of novel technologies and in advances that enable effective utilization of new or existing technologies.

Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

NICHD encourages technologies, analytics and models that have the potential to transform health and medicine to promote healthy pregnancies, healthy children, and healthy and optimal lives. NICHD supports biological, behavioral, and clinical research related to conception and pregnancy, normal and abnormal development in childhood, reproductive health, population dynamics across the lifespan, and people with intellectual, developmental and physical disabilities. NICHD seeks applications that align with the NICHD Strategic Plan themes of 1. understanding the molecular, cellular and structural basis of development, 2. promoting gynecologic, andrologic and reproductive health, 3. setting the foundation for health pregnancies and lifelong wellness, 4. improving child and adolescent health and the transition to adulthood, and 5. advancing safe and effective therapeutics and devices for pregnant and lactating women, children, and people with disabilities. Areas of interest to NICHD include, but are not limited to:

  • Utilization of electronic health records and large-scale datasets to measure exposure responses to therapy and devices and the linkage of mother-infant or familial records
  • Integration of genomic, nutritional, social and behavioral exposure data and modeling approaches to support the use of pharmacotherapies in pregnant and lactating women, children, and people with intellectual and physical disabilities
  • Understand how technology exposure and media use affect developmental trajectories, health outcomes, and parent-child interactions
  • Development of safe and effective therapeutics and devices (assistive and medical) used by pregnant and lactating women, children, and people with intellectual and developmental disabilities
  • Platforms that include real-time use of disease registries, including registries that track infectious diseases such as HIV/AIDS and intellectual and developmental disabilities such as Autism, to inform surveillance or predictions of outcomes across the lifespan.

National Institute on Drug Abuse (NIDA)

NIDA is specifically interested in applications that support scientific research on drug use and its health and social consequences across the spectrum, from occasional use to problematic use and substance use disorders (SUDs). Some examples of areas of interest include:

  • Using technology and advanced statistical methods to inform our understanding of both behavioral and neurobiological components of drug use that are strongly influenced by diverse environmental and social factors
  • The development and validation of technologies, analytics, and models to help individuals gather, manage, and use data and information related to drug use and their personal health
  • Methods and algorithms for aggregation of data including but not limited to electronic health records (EHRs), laboratory generated data, environmental, and/or behavioral data
  • Diagnostic/monitoring tools and technology platforms to optimize drug use interventions

National Institute on Deafness and Other Communication Disorders (NIDCD)

NIDCD encourages studies that improve the diagnosis, treatment, and management of disorders of hearing, balance, taste, smell, voice, speech, and language. Areas of scientific interest include but are not limited to the following areas. Improved diagnosis and management of dizziness and other vestibular-related disorders, hearing loss, loss of taste, and smell disorders. Development of effective and efficient clinical screening tools for communication disorders that can be applied in remote communities.

National Institute of Dental and Craniofacial Research (NIDCR)

Within the goals of this FOA, NIDCR is interested in supporting innovative, multi-disciplinary, and transformative research to improve dental, oral, and craniofacial health and to address oral health disparities and inequities. Successful applications should be guided by data FAIRness principles and address existing and emerging ethical issues. Examples of areas of interests include but are not limited to the following:

  • Development and implementation of novel devices and technologies, or novel approaches for adoption of existing devices and technologies, for collection and dissemination of medical, health, behavioral, environmental, socioeconomical, and biological data through prevention, diagnosis, and intervention of dental, oral, and craniofacial conditions from conventional and unconventional settings;
  • Development and implementation of novel computational systems and algorithmic tools for analyses of new, legacy, and multidimensional data from diverse resources to tackle health and health disparities and inequities issues of NIDCR’s interest.

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

NIDDK encourages innovative and integrated research on chronic conditions relevant to NIDDK’s mission areas, such as diabetes and other endocrine and metabolic diseases; digestive diseases, nutritional disorders, and obesity; and kidney, urologic, and hematologic diseases; to improve people’s health, quality of life, and to reduce disparities. Examples of projects of interest may include, but are not limited to, those that develop technology, analytics and tools in the following areas:

  • Integration of data repositories, biobanks, and Electronic Health Records (EHR) in support of precision medicine to better characterize diversity and heterogeneity in patient populations, endotypes in diseases, and to assist diagnosis, design of treatment and prevention protocols, risk assessments and prevention of complications.
  • Integration of automated medical image interpretation into clinical workflows or integration of multiple image and -omic data types using new algorithmic, statistical, and mathematical approaches in support of data-driven discovery.
  • Sensors, connected delivery systems (such as closed loop systems), monitoring devices and smart phone applications to enhance patient care, and patient data collection for research and care, including the collection of measures of biological and physiological status, physical activities, as well as measures of behavioral and psychosocial health and comorbidities.
  • Utilization and integration of data from connected devices, handheld and wearable devices, and social media apps to enhance patient-centered care, patient participation and self-management, and to improve behavioral interventions, including in the situation of virtual care and telemedicine.
  • Integration of systems to monitor, prevent, and/or reduce health disparities originating from technology design, selection of training datasets, and information dissemination, and to effectively communicate social and medical information across the clinical, community, and home contexts where individuals seek care and services.

National Institute of Environmental Health Sciences (NIEHS)

NIEHS's mission is to discover how the environment affects people, in order to promote healthier lives. NIEHS supports research aimed at discovering and explaining how factors, including chemical, physical, and synthetic agents; social stressors; weather extremes; and our own microbiomes, among others, affect biological systems. Data types relevant to Environmental Health research include high-dimensional data (genomic, metabolomic), demographic, questionnaire, qualitative, electronic health record, imaging, geospatial, and toxicological data, as well as exposure data from water, soil, sediment, air, and from wearable/personal exposure monitors. Within the goals of this funding opportunity, NIEHS is interested in projects that develop and/or apply innovative data science tools or methods to topics that align with the NIEHS Strategic Plan, including the exposome, co-exposures, predictive toxicology, individual susceptibility, and environmental health disparities. Specific interests include, but are not limited to the following areas:

  • Advancing data readiness of existing environmental health datasets, including making data accessible, structured, quality-controlled, and well-annotated, with appropriate privacy and security protections;
  • Promoting interoperability, aggregation, and harmonization of complex environmental health data to enable research and public health applications (e.g., integrating geospatial/spatiotemporal data from climate, satellite, or air monitoring sources with disease surveillance or other population data);
  • Developing exposure science technologies and standards for the collection of new environmental health data (e.g., mobile health, sensors, biomarkers of environmental exposures);
  • Improving environmental exposure surveillance or exposure science approaches by applying machine learning, AI, or related computational approaches;
  • Developing informatic tools to analyze multi-dimensional environmental exposure data, gene-environment interaction (GxE) data, and related complex data (e.g. imputation techniques for missing observations, novel methodologies for chemical mixtures); and
  • Applying AI or related computational approaches to better understand the impact of environmental exposures on health outcomes at all stages across the lifespan.

National Institute of General Medical Sciences (NIGMS)

NIGMS will accept proposals in response to this solicitation that clearly indicate relevance to one or more of the research areas supported by NIGMS (https://www.nigms.nih.gov/research-areas).

These include fundamental principles, mechanisms, and processes that underlie living organisms at a range of levels, from molecules and cells to tissues, organs, and populations. They also include specific NIGMS-supported clinical areas that affect multiple organ systems: anesthesiology and peri-operative pain; sepsis; clinical pharmacology that is common to multiple drugs and treatments; and trauma, burn injury, and wound healing. Research with the overall goal of gaining knowledge about a specific organ or organ system or the pathophysiology, treatment, or cure of a specific disease or condition will, in most cases, be more appropriate for another Institute or Center.

National Institute of Mental Health (NIMH)

NIMH is interested in deep phenotyping through the development of technologies to capture and analyze fine-grained, multimodal data from individuals with mental disorders and healthy controls, for the purpose of identifying novel biological and behavioral patterns that can (1) add to our understanding of specific mental health constructs and domains of function; (2) reveal causal links between environmental factors and mental functions; (3) uncover developmental trajectories; (4) better predict outcomes; and (5) improve the specificity and timeliness of clinical interventions. Technologies of interest to NIMH include, but are not limited to:

  • Sensors tailored to infer subjective mental states (e.g. mood, thought process, risk of self-harm, abnormal perceptions) from objectively observable behaviors (e.g. speech, movement, social interactions).This includes the ability to identify subgroups of patients with psychiatric disorders objectively, to enable more targeted treatments to be implemented in those subgroups.
  • Sensors adapted to monitor mental health related outcomes across the lifespan, in special populations, and within diverse settings (e.g. young children, geriatric populations, nonverbal individuals, assisted living environments).
  • Platforms for the delivery of nonpharmacological interventions (e.g. cognitive behavioral, psychosocial, stimulation-based) in real-world settings.
  • Sensors to measure outcomes of mental health interventions, including demonstrations of sensitivity to change and correspondence to conventional clinical assessments.
  • Technology allowing simultaneous, temporally synchronized neurophysiology measurements and quantification of behavior, with high spatial and temporal precision, using either invasive or noninvasive methods, toward the long-term goal of closing the loop between real-time behavioral measurements and delivery of targeted interventions in real-world settings.
  • Technologies targeting improvements in mental health care delivery systems, including:
  • Development and testing of methods for fusion and analysis of personal, behavioral, social, contextual, environmental, and organizational data to support development of innovative predictive models for simulation especially for low base-rate events/conditions that are difficult to identify, treat, and/or manage (e.g., suicide).
  • Application of ‘big data’ analytics and/or algorithm development to EHRs to inform real-time clinical decision making and measurement-based care associated with the delivery of mental health services.
  • Test approaches to increase engagement in individuals to effectively participate in their own mental health treatment, such as personalized information systems, accessing and visualizing health data and knowledge.
  • Develop and test strategies to increase adherence, utilization and sustainability for evidence based digital mental interventions/technologies.
  • Technology platforms that include real-time use of disease registries, measurement-based care, feedback systems, and quality improvement processes as part of a continuously learning healthcare system.
  • Research to improve designs, measures, and statistical approaches to support testing of system improvement efforts, including information and communication technologies.
  • Technology platforms which can be utilized across a range of systems (e.g., primary care, schools, criminal justice system, child welfare agencies) to optimize the delivery of effective mental health interventions.
  • Development of innovative technologies to facilitate adoption, implementation, sustainability, and scalability of best practices, or conversely, technologies to de-implement low value mental health services.

National Institute on Minority Health and Health Disparities (NIMHD)

NIMHD’s mission is to lead scientific research to improve minority health and reduce health disparities. The Social Determinants of Health (SDOH) include individual and structural factors, such as demographics, education, access to care, economic stability, social and community context, which have a significant impact on health outcomes and healthcare quality and costs for underserved populations. NIMHD is interested in the development and evaluation of innovative technologies, analytics, statistical methods and models that:

  • Standardize the collection, enable the communication, and facilitate the integration of real time actionable SDOH data into the existing workflows of clinicians and community-based care providers, to enable decision support, foster resource and information sharing, and improve patient care and clinical care coordination for underserved populations, making it easier to connect individual patients with resources that can address their social needs.
  • Facilitate the analysis and integration of spatially linked SDOH information with community and population health data, to inform the design of effective multi-level interventions aimed at reducing and encouraging elimination of disparities in health outcomes and quality of care.
  • Foster recruitment and enrollment for statistically valid representation of racial/ethnic minority and other populations with health disparities in clinical research studies and especially in therapeutic clinical trials and disease states for which disparities are observed.
  • Dissect potential racial and ethnic, socioeconomic status, privilege, and disability biases that may be introduced into prediction algorithms and machine learning–based clinical decision support tools in order to prevent further discrimination and to foster appropriate care for all population groups.

National Institute of Neurological Disorders and Stroke (NINDS)

Within the goals of this funding opportunity, NINDS is particularly interested in research that advances technologies and systems with the potential to decrease the burden of neurological disorders and stroke. Examples of areas of interest include:

  • Collaborative projects that bring data science approaches to neurobiological problems to better understand fundamental neural mechanisms, circuits, or systems and behavior
  • The development and validation of invasive and non-invasive devices, diagnostic and digital monitoring tools, advanced imaging techniques, computational models, and tissue engineering techniques. Projects seeking to translate engineering products or devices to patient use, including those that require regulatory approval, would be best directed to other programs targeting that stage of development in the NINDS Division of Translational Research.
  • Tools for harmonization and integration of biomedical data repositories including the use of cloud environments and/or for visualizing and interacting with neuroscience datasets that may include integration of spatial and temporal features.
  • Proposals that include related legal, social, or ethical research, as socio-cultural, economic, legal, and ethical implications can amplify or mitigate technical challenges of achieving the Smart Health vision. This includes, for example, broader societal implications of the uses of data and technologies, such as potential benefits, burdens, or risks that might accrue differentially to different populations.

National Institute of Nursing Research (NINR)

The mission of the National Institute of Nursing Research (NINR) is to promote and improve the health of individuals, families, and communities. Digital health tools offer significant new opportunities to improve medical outcomes and enhance the efficiency of care via the convergence of technologies such as biosensors, mHealth, telehealth, health information technology, etc. NINR has a broad interest in the development of digital health technologies for individuals/caregivers that aid in: (i) self-management of acute and chronic conditions to improve quality of life, (ii) symptom management and personalized health strategies, (iii) promotion of wellness and disease/disability prevention and (iv) tools that enhance end-of-life care and palliative care across the lifespan. There is a special emphasis on the development of technologies that would aid in the understanding and reduction of health disparities.

National Library of Medicine (NLM)

NLM is interested in the development of technologies, analytics and models that utilize novel informatics and data science approaches to help individuals gather, manage and use data and information about their personal health. To bring the benefits of big data research to consumers and patients, new biomedical informatics and data science approaches are needed, shaped to meet the needs of consumers and patients, whose health literacy, language skills, technical sophistication, education and cultural traditions affect how they find, understand and use personal health information. Novel data science approaches are needed to help individuals at every step, from harvesting to storing to using data and information in a personal health library. These approaches should support FAIR (Findable, Accessible, Interoperable, Reusable) principles of data management.

Office of Data Science Strategy (ODSS)

The mission of ODSS is to catalyze new capabilities in biomedical data science for modernization of the NIH data ecosystem, development of a diverse and talented data science workforce, and the development and dissemination of advanced technologies and methods. ODSS has broad interests in petabyte scale data science methodology and ethics, transparency and bias in AI. Program areas of particular relevance include: adaptive methods and algorithms to handle petabyte-size data query, analysis, and encryption; Edge-to-Fog mobile-device and data-interface tools that aggregate data to a cloud environment; FHIR applications with relevance to clinical and research data; AI applications in transparency and bias in large biomedical datasets; and methods to dynamically improve metadata with advance knowledge graphs for AI applications. Applications must also be relevant to the objectives of at least one of the participating NIH Institutes and Centers (IC) listed above. ODSS does not award grants. Please contact the relevant IC program contact listed for questions related to IC research priorities and funding.

Application Preparation and Submission Instructions

Proposals submitted in response to this program solicitation should be prepared and submitted in accordance with the general guidelines contained in the NSF Proposal & Award Policies & Procedures Guide (PAPPG). The complete text of the PAPPG is available electronically on the NSF website at: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg. Paper copies of the PAPPG may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail fromnsfpubs@nsf.gov. Proposers are reminded to identify this program solicitation number in the program solicitation block on the NSF Cover Sheet for Proposal to the National Science Foundation. Compliance with this requirement is critical to determining the relevant proposal processing guidelines. Failure to submit this information may delay processing.

Budgetary Information

Projects will be funded for up to a four-year period and for up to a total of $300,000 per year. Budgets should include travel funds to attend one Smart Health PI meeting annually for the project PIs, co-PIs and other team members as appropriate from all collaborating institutions.

Inclusion of voluntary committed cost sharing is prohibited.

For NIH, indirect costs on foreign subawards/subcontracts will be limited to eight (8) percent.

NIH Process

For those applications that are selected for potential funding by participating NIH ICs, the PD/PI will be required to resubmit the application in an NIH-approved format to the NIH. PD/PIs invited to submit to NIH will receive further information on submission procedures from NIH. An applicant will not be allowed to increase the proposed budget or change the scientific content of the proposal in the submission to the NIH. Indirect costs on any foreign subawards/subcontracts will be limited to eight percent. The results of the review will be presented to the involved Institutes' National Advisory Councils for the second level of review. For information purposes, NIH PD/PIs may wish to consult the OER website which provides excellent generic information about all aspects of NIH grantsmanship, including competitive renewals (https://grants.nih.gov/grants/grants_process.htm).

Inquiries

Please direct all inquiries to:

Inquiries are encouraged and NIH Scientific/Research contacts are listed below. Please see the NSF Smart Health website for names and contact information of participating NSF Directorates.

Merav Sabri, PhD
National Center for Complementary and Integrative Health (NCCIH)
Telephone: 301-496-2583
Email: merav.sabri@nih.gov

Robin Vanderpool, DrPH
National Cancer Institute (NCI)
Telephone: 240-276-6558
Email: vanderpoolrc@mail.nih.gov

James Gao, PhD
National Eye Institute (NEI)
Telephone: 301-594-6074
Email: james.gao@nih.gov

Heather A. Colley, M.S.
National Human Genome Research Institute (NHGRI)
Telephone: 301-480-2332
Email: junkinsh@mail.nih.gov

Erin Iturriaga, DNP
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0403
Email: erin.iturriaga@nih.gov

Partha Bhattacharyya, PhD
National Institute on Aging (NIA)
Telephone: 301-496-3136
Email: bhattacharyyap@mail.nih.gov

Ishwar Chandramouliswaran, PhD
National Institute of Allergy and Infectious Diseases(NIAID)
Telephone: 301-761-7822
Email: ishwar.chandramouliswaran@nih.gov

Anthony Kirilusha, PhD
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Telephone: 301-451-7648
Email: anthony.kirilusha@nih.gov

Qi Duan, PhD
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Telephone: 301-827-4674
Email: qi.duan@nih.gov

Samantha Calabrese, PhD
Eunice Kennedy Shriver National Institute of Child Health and Human Development(NICHD)
Telephone: 301-827-7568
Email: samantha.calabrese@nih.gov

Susan Wright, PhD
National Institute on Drug Abuse (NIDA)
Telephone: 301-402-6683
Email: susan.wright@nih.gov

Roger Miller, PhD
National Institute on Deafness and Other Communication Disorders(NIDCD)
Telephone: 301-402-3458
Email: millerr@nidcd.nih.gov

Emir Khatipov, PhD
National Institute of Dental and Craniofacial Research (NIDCR)
Phone: 301-594-3977
Email: emir.khatipov@nih.gov

Xujing Wang, PhD
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Telephone: 301-451-2862
Email: xujing.wang@nih.gov

Christopher Duncan, PhD
National Institute of Environmental Health Sciences (NIEHS)
Telephone: 984-287-3256
Email: christopher.duncan@nih.gov

Paul Brazhnik, PhD
National Institute of General Medical Sciences (NIGMS)
Telephone: 301-451-4317
Email: brazhnikp@nigms.nih.gov

Adam Haim, PhD
National Institute of Mental Health (NIMH)
Telephone: 301-435-3593
Email: adam.haim@nih.gov

Deborah Duran, PhD
National Institute on Minority Health and Health Disparities (NIMHD)
Telephone: 301-594-9809
Email: deborah.duran@nih.gov

Sahana N. Kukke, PhD
National Institute of Neurological Disorders and Stroke(NINDS)
Telephone: 301-496-1447
Email: sahana.kukke@nih.gov

Kristopher Bough, PhD
National Institute of Nursing Research (NINR)
Telephone: 301-496-2604
Email: kristopher.bough@nih.gov

Yanli Wang, PhD
National Library of Medicine (NLM)
Telephone: 301-594-4882
Email: yawang@mail.nih.gov

Dana Wolff-Hughes, PhD
Office of Behavioral and Social Sciences Research (OBSSR)
Telephone: 301-496-0979
Email: dana.wolff@nih.gov

Fenglou Mao, PhD
Office of Data Science Strategy (ODSS)
Telephone: 301-451-9389
Email: fenglou.mao@nih.gov


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