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Predictive Multiscale Models for Biomedical, Biological, Behavioral, Environmental, and Clinical Research (U01) Webinar

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for PAR-15-085

October 6, 2015

Purpose of the Webinar:

On Tuesday, October 6, 2015, the National Institutes of Health (NIH) National Center for Complementary and Integrative Health (NCCIH) hosted a webinar to provide information to potential applicants to the Interagency Modeling and Analysis Group’s (IMAG) U01 (or Cooperative Agreement) funding opportunity titled “Predictive Multiscale Models for Biomedical, Biological, Behavioral, Environmental, and Clinical Research” (PAR-15-085). This effort involves 12 NIH components and 6 other Federal agencies. The webinar speaker provided an overview of the U01 PAR on predictive multiscale models, described NCCIH’s mission and conceptual framework, presented NCCIH’s high-priority interest topics for this PAR with examples and potential collaborators, outlined submission and review information, and provided answers to audience questions.

Webinar Speakers:

  • Anita McRae-Williams, M.A., Outreach Program Manager, National Center for Complementary and Integrative Health (NCCIH) (Webinar Moderator)
  • Wen G. Chen, Ph.D., Program Director, Basic and Mechanistic Research in Complementary and Integrative Health, Division of Extramural Research, NCCIH

This report summarizes information provided during the webinar about the PAR, the NCCIH and its high-priority research topics related to the PAR, submission and review information, and answers to the questions posed by participants.

What Is the U01 PAR on “Predictive Multiscale Models”?

Why Are Predictive Multiscale Models Important?

  • The NIH collaborated with the National Science Foundation as early as 2004 to support research related to multiscale models because the NIH recognized the importance of predictive multiscale models for biomedical and biological systems.
  • Predictive multiscale models for biomedical and biological systems are needed to: (1) help integrate diverse data, (2) create testable hypotheses, (3) identify and share gaps in knowledge requiring further research, (4) uncover biological mechanisms, and (5) make predictions about clinical outcome or intervention effects.

What Will Be Supported by this PAR?

  • The types of science and research that will be supported through this 2015 re-issue of the funding opportunity announcement must be multiscale and aim to be predictive.
    • In other words, it must link different spatial or temporal scales, different levels of aggregation, different scientific fields, or different physiological systems and/or environmental systems (multiscale), while making realistic scientific predictions to address problems and issues in the environment, in the human body, and among individuals, groups, and within populations (predictive).
    • The work should identify a challenging multiscale problem or approach that is currently not being addressed and propose to develop predictive models that will be unique, push the boundaries, and may lead to higher risk projects.
    • It may expand an existing model to address a new breakthrough challenge in multiscale modeling of biological or biomedical systems.

Expertise/Partnerships

  • Clinicians, epidemiologists, molecular biologists, geneticists, and neurobiologists with expertise (or collaborators with expertise) in computational modeling and/or an interest in developing predictive multiscale models for biological or medical systems are encouraged to apply. Expertise in computational modeling is a key requirement.
  • Highly interactive partnerships are expected. Examples include (but are not limited to):
    • Experimental and modeling expertise to develop models that create testable hypotheses leading to new investigational studies.
    • Mathematical and/or statistical expertise with domain-modeling expertise to develop new methods that will enhance the function of the models.
    • 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.
    • Expertise from mature modeling fields with expertise from fields with an emerging use of models.
    • 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.

Implementation of the U01 Cooperative Agreement

  • Grantees are required to become members of the Multiscale Modeling (MSM) Consortium.
  • Applicants must articulate how their teams will fulfill the MSM Plan in terms of project outcomes, milestones, and timelines for both scientific progress and participation within the MSM Consortium.
  • Collaborative activities that contribute to the needs of the wider MSM community are encouraged. These include leading working groups; hosting webinars; sharing data, models, and expertise; and other efforts;
  • Program staff from the IMAG award agency will have a significant, although not dominant, role in the planning and execution of the supported activities.

NCCIH Mission and Conceptual Framework

  • NCCIH’s mission is to define, through rigorous scientific investigation, the usefulness and safety of complementary and integrative health interventions and their roles in improving health and health care (the NCCIH was formerly known as the National Center for Complementary and Alternative Medicine, or NCCAM)
  • The framework for research on complementary and integrative health approaches can be summarized into a series of steps, ranging from an iterative process of exploratory or pilot studies of the mechanisms, optimization, or feasibility of the interventions, to efficacy and comparative effectiveness studies, to dissemination and implementation studies.
  • Predictive multiscale modeling research is important for every step of the complementary and integrative health research framework.

NCCIH High-Priority Topics of Interest for this PAR

  • For the purpose of this PAR, the NCCIH is soliciting applications that are primarily focused on the mechanistic, exploratory, or piloting types of studies related to complementary and integrative interventions.
  • Those seeking to develop predictive multiscale models for efficacy/effectiveness, dissemination, or implementation studies are strongly encouraged to contact Dr. Wen Chen (chenw@mail.nih.gov), who can direct them to the appropriate program officials at the NCCIH for further guidance as well as identifying other suitable funding initiatives.
  • High-priority topics of interest for this PAR include:
    • Predictive and/or modifiable mechanisms of natural products or mind and body approaches for pain management.
    • Predictive and/or modifiable mechanisms of mind and body approaches for post-traumatic stress (disorder), sleep disorders or disturbances, anxiety, or depression.
    • Preventative strategies that links genetics, molecular mechanisms, intracellular signaling, brain circuits, and/or environment with responders and non-responders of complementary interventions.
    • Predictive models of systems level biological activity of natural products
    • Predictive mechanistic pathways and regulatory networks in microbiota brain-gut interactions and related bio-behavioral networks
    • The topics list above are examples—potential applicants who have concepts that would fit NCCIH’s mission but are not included in these examples are encouraged to contact Dr. Wen Chen (chenw@mail.nih.gov).

Examples of Predictive MSM Research and Potential Collaborators

  • Predictive Models of Multi-scale Measures for the Effects of Acupuncture, Hypnosis, Meditation, or Tai Chi on Pain Management
    • Potential collaborators include:
      • Bruce R. Rosen and Randy Gollub of Massachusetts General Hospital—“Neuroimaging Acupuncture Effects Brain Activity in Chronic Low Back Pain” (P01AT006663).
      • Kirsten Tillisch and Bruce D. Naliboff of the University of California at Los Angeles—“Neuroimaging Biomarkers of Mind-Body Treatment Response in Chronic Visceral Pain” (R01AT007137).
  • Predictive Models of Multi-Scale Measures for Meditation, Yoga, and/or Herb Effects on Mild-to Moderate Depression, Sleep, Stress, or Anxiety
    • Potential collaborators include:
      • Richard Davidson of the University of Wisconsin at Madison—“Wisconsin Center for the Neuroscience and Psychophysiology of Meditation” (P01AT00004952).
      • Richard B. Van Breemen of the University of Illinois at Chicago—“Botanical Dietary Supplements for Women’s Health” (P50AT000155).
  • Predictive Models of Systems-Level Biological Activities of Natural Products, Especially in the Context of Complex Natural Product Mixtures
    • Potential collaborators include:
      • Steven Polyak of the University of Washington—“Mechanisms of Silymarin Hepatoprotection” (R01 AT006842).
      • Nadja Cech of the University of North Carolina Greensboro—“Strategies to Investigate Synergy in Botanical Medicines” (R01 AT006860).
  • Predictive Models of the Interactions between Genes and Natural Product, Such as Supplements, Diets, Botanicals, and Their Influences on Medicine and Health Outcomes
    • Potential collaborators include:
      • Ski Chilton of Wake Forest University—“Role of PUFA-Gene Interactions in Health Disparities” (R01 AT008621-01A1)
      • Ilya Raskin of Rutgers University—“Health Promoting Effects of High-Polyphenol Foods May be Mediated Through Gut Microbiome” (R01 AT008618).
  • Predictive Models of Networks of Microbiota-Brain-Gut Interactions, or the Interactions of Such Networks with Related Omics, Bio-behavioral Networks, or Intervention Strategies and Health Outcomes
    • Potential collaborators include:
      • Elhanan Borenstein of the University of Washington—“A Computational Framework for Designing Microbiome Manipulation” (DP2AT007802).
      • David Kumpp of Northwestern University—“Mechanisms of Probiotic Analgesia” (R01 AT007701).
  • NCCIH’s interests in supporting complementary and integrative health approaches are not restricted to these specific examples. Any highly innovative ideas and proposals that may fit the NCCIH mission are encouraged.

Submission and Review Information

  • There are six remaining submission deadlines, as follows:
    • 2016: January 29, May 30, September 29
    • 2017: January 30, May 29, and September 29
  • The contact for the Letter of Intent (due 1 month before the submission deadline) is Grace C.Y. Peng, Ph.D. (phone: 301-451-4778; fax: 301-480-1614; e-mail: grace.peng@nih.gov).
  • The NCCIH Scientific/Research Contact is Wen G. Chen, Ph.D. (phone: 301-451-3989;
    e-mail: chenw@mail.nih.gov).
  • If proposed work involves an interventional design in human subjects, potential applicants are encouraged to review the NCCIH Clinical Research Toolbox online at nccih.nih.gov/grants/toolbox to familiarize themselves with the processes related to such studies.

Resources

General questions about this webinar or PAR-15-085 can be directed to Dr. Wen Chen at chenw@mail.nih.gov.

Summary of Questions and Answers

Are multi-site collaborations being encouraged, or is this opportunity geared towards multiscale modeling work from within single sites?
The most basic requirement for this PAR is that the work must be multiscale—whether the work is carried out at one site or many should be based on the research team’s needs. There is a budget cap for this PAR, which could restrict the scope of the research somewhat, and applicants should take this into consideration.
Is there an interest in using different cannabinoid molecules such as cannabidiol for treatment of anxiety, PTSD, and potentially some psychoses? Would there be interest in having a multiscale model of either the hippocampus or neocortex to address that?
The cannabinoids are of great interest to us, and the particular approach mentioned above would fit within the scope of this PAR. The NCCIH has a Program Officer who is interested in cannabinoid research, particularly in terms of pain.

This page last modified September 24, 2017