Notice of Change to Instructions for PA-18-471 "Innovative Questions in Symptom Science and Genomics (R15 Clinical Trial Not Allowed)"

Notice Number: NOT-NR-18-012

Key Dates
Release Date: February 28, 2018

Related Announcements
PA-18-471

Issued by
National Institute of Nursing Research (NINR)

Purpose

The purpose of this Notice is to update the Research Objectives of PA-18-471, "Innovative Questions in Symptom Science and Genomics (R15 Clinical Trial Not Allowed)." The objectives were modified to eliminate any confusion about clinical trials as they are not allowed for this FOA. One objective has been modified and two objectives have been deleted.
The research objective that will be modified is in the Symptom Science area and is listed below:

  • What innovative methodologies (e.g. modeling) can be used to analyze symptom management algorithms to identify the interventions most likely to be successful in clinical or pragmatic trials?
The two research objectives that will be deleted are in the Genomics area and are listed below:
  • Based on individual omics, environmental factors, and behavior what are the most effective and targeted interventions that can be expedited for translation to reduce risk and promote health?
  • What are the relative contributions of omic markers and phenomic data in predicting individual responses to therapeutic interventions that improve patient outcomes such as quality of life?
Section I. Funding Opportunity Description

Research Objectives
Currently Reads
Symptom Science
  • What are the biological and behavioral dynamics of symptoms (e.g., dyspnea, fatigue, impaired sleep/insomnia, pain, depression) that can change the trajectory of chronic illnesses, and how can the dynamics be optimized and maintained to prevent symptom relapse?

  • What innovative care delivery models (e.g. interdisciplinary, family-based), research methods (e.g. community engaged research, pragmatic trials) and technologies (e.g. eHealth) can be leveraged to improve symptom management and change the chronic illness trajectory especially among individuals who experience disparate health outcomes?

  • How do lifestyle factors, environmental conditions, symptom clusters and symptom treatments impact quality of life and symptom management in different chronic conditions?

  • How do symptom precursors (e.g. biomarkers or conditions such as obesity) contribute to the physiology of symptom risk, severity, duration and response to treatment?

  • What are the 'omic', phenotypic and state dependent indicators related to the mechanism, assessment and management of high impact symptoms (e.g. pain, fatigue, dyspnea) and what is the added value of these indicators beyond clinical parameters in explaining physical and psychological symptoms in both patients and their informal caregivers?

  • What are the common mechanistic pathways (e.g. stimulus to perception, perception to report) that can distinguish underlying symptom cluster trajectories that are amenable to intervention at various points along those pathways?

  • What are the personalized markers (e.g. biomarkers and clinical factors) that can be used to stratify subgroups of patients with different patterns among symptoms to determine the symptom management strategies most effective in improving quality of life?

  • What innovative methodologies (e.g. modeling) can be used to analyze symptom management algorithms to identify the interventions most likely to be successful in clinical or pragmatic trials?

  • How can we create a standardized, feasible, valid, and relevant data and technology infrastructure to routinely collect and aggregate symptom data from patient health records but also from other types of assessments (biological, physiological, performance) to inform clinical care and research?

  • What are the biological indicators that can help determine the presence and severity of subjective symptoms in individuals who cannot self-report (e.g. small children; individuals with cognitive decline) to help improve clinical assessment and management? Is there a role for fMRI?

  • What state-of-the-art research designs/methods (e.g. mixed methods, SMART, MOST) should investigators use to test personalized symptom management strategies to include scalable interventions?

Genomics
  • What are the biologic, physiologic and/or omic mechanisms underlying symptoms and patient outcomes?
  • Based on individual omics, environmental factors, and behavior what are the most effective and targeted interventions that can be expedited for translation to reduce risk and promote health?
  • What are the relative contributions of omic markers and phenomic data in predicting individual responses to therapeutic interventions that improve patient outcomes such as quality of life?

  • For high risk patients who are at the end of life, how can genetic assessment and DNA banking be used to address familial risk?

  • How should omic discoveries be used to create and test technologies (such as clinical tools) that can be used to diagnose clinical problems, predict the clinical course and promote optimal outcomes?

  • In what ways can genomic information be used to promote adherence and improve self-management of chronic conditions?
  • How does the social environment interact with gene expression to influence resilience in coping with life challenges?

Modified to read

Symptom Science
  • What are the biological and behavioral dynamics of symptoms (e.g., dyspnea, fatigue, impaired sleep/insomnia, pain, depression) that can change the trajectory of chronic illnesses, and how can the dynamics be optimized and maintained to prevent symptom relapse?

  • What innovative care delivery models (e.g. interdisciplinary, family-based), research methods (e.g. community engaged research, pragmatic trials) and technologies (e.g. eHealth) can be leveraged to improve symptom management and change the chronic illness trajectory especially among individuals who experience disparate health outcomes?

  • How do lifestyle factors, environmental conditions, symptom clusters and symptom treatments impact quality of life and symptom management in different chronic conditions?

  • How do symptom precursors (e.g. biomarkers or conditions such as obesity) contribute to the physiology of symptom risk, severity, duration and response to treatment?

  • What are the 'omic', phenotypic and state dependent indicators related to the mechanism, assessment and management of high impact symptoms (e.g. pain, fatigue, dyspnea) and what is the added value of these indicators beyond clinical parameters in explaining physical and psychological symptoms in both patients and their informal caregivers?

  • What are the common mechanistic pathways (e.g. stimulus to perception, perception to report) that can distinguish underlying symptom cluster trajectories that are amenable to intervention at various points along those pathways?

  • What are the personalized markers (e.g. biomarkers and clinical factors) that can be used to stratify subgroups of patients with different patterns among symptoms to determine the symptom management strategies most effective in improving quality of life?

  • What innovative methodologies (e.g. modeling) can be used to analyze symptom management algorithms?

  • How can we create a standardized, feasible, valid, and relevant data and technology infrastructure to routinely collect and aggregate symptom data from patient health records but also from other types of assessments (biological, physiological, performance) to inform clinical care and research?

  • What are the biological indicators that can help determine the presence and severity of subjective symptoms in individuals who cannot self-report (e.g. small children; individuals with cognitive decline) to help improve clinical assessment and management? Is there a role for fMRI?

  • What state-of-the-art research designs/methods (e.g. mixed methods, SMART, MOST) should investigators use to test personalized symptom management strategies to include scalable interventions?

Genomics
  • What are the biologic, physiologic and/or omic mechanisms underlying symptoms and patient outcomes?
  • For high risk patients who are at the end of life, how can genetic assessment and DNA banking be used to address familial risk?
  • How should omic discoveries be used to create and test technologies (such as clinical tools) that can be used to diagnose clinical problems, predict the clinical course and promote optimal outcomes?
  • In what ways can genomic information be used to promote adherence and improve self-management of chronic conditions?
  • How does the social environment interact with gene expression to influence resilience in coping with life challenges?

All other aspects of this FOA remain unchanged.

Inquiries

Please direct all inquiries to:

Lois A. Tully, Ph.D.
National Institute of Nursing Research (NINR)
Telephone: 301-594-5968
Email: tullyla@mail.nih.gov