Opportunities and Resources
- An Opportunity for Establishing Systems Biology Centers for Infectious Diseases
- Develop Tools To Advance Therapeutic Discovery for Select Antimicrobial-Resistant Gram-Negative Bacteria
In The News
- NIH To Enhance the Grant Closeout Process Next Month
- Institutions: Apply for Administrative Supplements To Cover Stipend Increases
- Help Shape NIH Strategies for Data Management and Sharing
- News Briefs
- To Name or Not To Name
- Reader Questions
New Funding Opportunities
NIAID received more research project grant applications in fiscal year 2016 than ever before, and since we set NIAID’s Research Project Grant (R01) payline higher than it’s been since FY 2006, we also saw the highest success rate for R01-equivalent* applications of the past five years.
In this article, we will lay out that data and make a few observations along the way.
To start, consider the total counts of R01-equivalent and exploratory/developmental research grant (R21) applications by year:
|FY 2012||FY 2013||FY 2014||FY 2015||FY 2016|
As you can see, the number of R01-equivalent applications dropped 7.8 percent from FY 2012 to FY 2014, but that drop reversed itself, as we received 4.4 percent more R01-equivalent applications in FY 2016 than in FY 2012.
Meanwhile, the number of incoming R21 applications has continued its decade-long pattern of steadily climbing, an increase of 23.6 percent from FY 2012 to FY 2016.
Next, take a look at our paylines for R01 and R21 grant applications over the last five years. Note that the R01 paylines are calculated as percentiles while the R21 paylines are determined as overall impact/priority scores, as explained at Understand Paylines and Percentiles.
|FY 2012||FY 2013||FY 2014||FY 2015||FY 2016|
Note that the R01 paylines listed above are for established investigators. NIAID sets a separate payline for new and early-stage investigators, usually four percentage points higher than the general R01 payline.
For both R01 and R21 grant applications, there was a payline reduction from FY 2012 to FY 2013 (due in part to budget sequestration) and a significant increase from FY 2014 to FY 2015. Fortunately, we were able to keep the paylines rising in FY 2016.
Given those yearly paylines, NIAID funded the following number of awards:
|FY 2012||FY 2013||FY 2014||FY 2015||FY 2016|
As the table makes clear, NIAID made more awards in FY 2016 than in any other year displayed. For R21 awards specifically, FY 2016 represents an increase in award count of nearly one third since FY 2012.
All that combines to yield the following success rates:
|Success Rates (in percentage)|
|FY 2012||FY 2013||FY 2014||FY 2015||FY 2016|
Clearly, our success rates are moving in the right direction, having continually increased since FY 2013.
We often hear potential applicants speculate that an R21 award is easier to get. However, the success rates for the two activity codes were within a half percentage point of each other in FY 2016. So if you’re deciding which activity code to use for an investigator-initiated application, the scope of your project (e.g., costs and time), rather than past success rates, should determine which mechanism you use.
Finally, as you may already know, the FY 2017 interim R01 payline for established investigators is currently set at the 10 percentile and the R21 payline is set at the 26 overall impact/priority score. Often, our final paylines are higher than the interim paylines we set at the start of the fiscal year, although you shouldn’t take that for granted. For more on our budget process, read NIAID Paylines and Budget Information Changes Throughout the Year.
*Note: “R01-equivalent” combines the R01 and Method to Extend Research in Time Award (R37) activity codes.
Opportunities and Resources
Title: Systems Biology: The Next Generation for Infectious Diseases
As part of NIAID's Systems Biology for Infectious Diseases Research program, a new funding opportunity announcement (FOA) seeks applications to establish Systems Biology Centers for infectious diseases.
The systems biology approach consists of repeated cycles of generating, analyzing, and integrating experimental data; modeling system-wide molecular networks structure and dynamics; and predicting microbial and host systems’ responses to perturbations or alterations of experimental conditions and experimental validation.
From hypothesis-driven projects that perform large-scale data generation, data analysis, and integration with statistical inference modeling, these Centers will focus on building models of infectious diseases that can be used for discovering predictive markers of disease progression, health, and treatment response.
Some expected results for the program are integrated data sets, maps of host-pathogen interaction networks, computational predictive models of infectious diseases, and new and enhanced computational tools and experimental protocols.
For examples of research areas that are of interest as well as types of projects that will be considered nonresponsive and therefore not reviewed, see the FOA, linked below. Note that this FOA requires using material from human clinical samples (e.g., human cells or tissues, human blood, immune components) and/or pathogen isolates.
Collaboration Is Key
Applicants are required to form interdisciplinary teams that are capable of pursuing coordinated activities that bring together experts in fields such as microbiology, immunology, infectious diseases, and omics technologies with those in mathematics, physics, bioinformatics, and statistical methods and modeling.
Each Center will have the following components:
- Administrative Core—headed by the project director/principal investigator, will be responsible for managing, coordinating, and supervising the entire range of Center activities; monitoring progress; and ensuring that the overall project management plan is implemented effectively and within proposed timelines
- Data Management and Bioinformatics Core—provides data storage, management, and information security services to the Center and all collaborating sites
- Technology Core—provides high-throughput technologies for systems biology analysis of samples
- Modeling Core—responsibilities include developing predictive models of infectious diseases and maintaining computational and statistical tools, machine learning algorithms, and statistical methods necessary for building these models
- Two Synergistic Research Projects—must be organized around a common theme that uses a systems biology approach to 1) build predictive models of infectious diseases and 2) identify, quantify, model, and predict the overall architecture and dynamics of the molecular interaction networks of pathogenic organisms with their host cells during infectious disease
Applications must include milestones and timelines for each research project, activities related to the Administrative Core, and the overall goals of the Center.
For Complete Details
Read the November 16, 2016 Guide announcement.
Develop Tools To Advance Therapeutic Discovery for Select Antimicrobial-Resistant Gram-Negative Bacteria
Gram-negative bacterial pathogens, e.g., carbapenem-resistant Enterobacteriaceae (CRE), multi-drug resistant (MDR) Acinetobacter, and MDR Pseudomonas aeruginosa, are associated with surging rates of drug resistance in healthcare and community settings.
To facilitate therapeutic discovery for these select Gram-negative bacterial pathogens, a recent R01 funding opportunity announcement (FOA) seeks applications for milestone-driven research projects focused on developing and using novel predictive assays, models, and/or research tools based on penetration and efflux of small molecules.
To be responsive, your project must:
- Focus on CRE, MDR Acinetobacter, and/or MDR Pseudomonas aeruginosa.
- Complete assay, tool, or model development before the end of the third year of the project period and initiate discovery activities to show its utility in supporting a corresponding medicinal chemistry program to generate a lead chemical series with demonstrated activity against one or more targeted Gram-negative bacteria.
Given the complex challenges of this objective, you should strongly consider assembling a multidisciplinary team composed of experts in relevant areas. For example, bacterial physiology, microbiology, medicinal chemistry, computational chemistry, biophysics, and specialized technologies such as microscopy, spectroscopy, and electrophysiology, as appropriate.
We encourage your collaborating closely with academic and industry partners to optimally combine innovative basic science with medicinal chemistry expertise and proper access to compound libraries more typically available from industry.
Examples of assay and model development include:
- Quantitative cellular (or model system) assays to measure drug penetration and efflux, independent from standard minimum inhibitory concentration testing
- Innovative quantitative assays to measure drug concentrations in bacterial cytoplasm and/or periplasmic space
- Innovative technologies for assessment of the kinetics of drug penetration and efflux from bacteria
- Computational algorithms for describing/predicting physical-chemical properties/guidelines needed by small molecules for optimal Gram-negative penetration and efflux avoidance
Successful projects will demonstrate the utility of the developed tools or assays to predict and measure potency of candidate therapeutics against Gram-negative targets. Preferably, you will accomplish this by either 1) using the developed models and/or assays to guide a medicinal chemistry campaign aimed at producing a novel chemical series with Gram-negative activity or 2) screening existing libraries using the computational algorithms developed as a tool to find compounds with Gram-negative activity. Alternatively, you can demonstrate the utility of the developed tools/assays by profiling existing libraries of compounds with known Gram-negative activity.
Do not propose the following in your application. If you do, it will be considered nonresponsive and will not be reviewed.
- Projects that do not focus on at least one select Gram-negative pathogen (CRE, MDR Acinetobacter, or MDR Pseudomonas aeruginosa)
- Projects focused only on Gram-positive bacteria or Mycobacterium tuberculosis
- Clinical trials (all phases)
- Projects on AIDS and/or HIV
NIAID intends to commit $9 million in fiscal year 2018 to fund 10 to 15 R01 awards.
The maximum project period is five years. You may request a budget of up to $750,000 in direct costs annually as well as up to an additional $300,000 in the first year of the award for major equipment to ensure that you can meet research objectives and contain biohazards.
Information on Application, Deadlines, and Contact
Optional letters of intent are due April 17, 2017. The application deadline is a month later on May 17.
Read the November 16, 2016 Guide announcement for complete details, including what components to include in your application. Note that you must have a Milestones and Timeline attachment of no more than five pages.
If you have questions, direct them to Dr. Michael Schaefer, the FOA's scientific/research contact.
In The News
Effective January 1, 2017, NIH will replace the Final Progress Report (FPR) with a Final Research Performance Progress Report (Final RPPR), which grantees will be able to complete and submit through a new eRA Commons module. On or after that date, NIH will no longer accept FPRs as uploaded documents.
The format of the Final RPPR will closely follow that of the annual RPPR that grantees submit throughout the life of the grant. This should make final reporting easier to complete.
One key addition to the Final RPPR is the Project Outcomes section. To complete this requirement, grantees will provide a concise summary of the cumulative outcome or findings of the project, and NIH will make that section publicly available.
Another important change: The progress report within a Type 2 (renewal) application will no longer serve as a final progress report for the original grant. Instead, grantees will submit an "Interim-RPPR" while their renewal application is under consideration. If the renewal application is funded, NIH will treat the Interim-RPPR as the annual performance report for the final year of the previous competitive segment. If the renewal application is not funded, the Interim-RPPR will be treated by NIH staff as the grant’s Final RPPR.
As with the FPR, the Final RPPR or Interim-RPPR must be submitted via eRA Commons no later than 120 calendar days from the period of performance end date.
Read the November 23, 2016 Guide notice for complete details.
On December 1, 2016, NIH raised stipend levels for postdoctoral recipients of NIH institutional training and individual fellowship awards. Specifically, the adjustment takes all postdocs with two or fewer years of experience to stipend levels at or above a base rate of $47,484 annually. This policy was first announced in the August 10, 2016 Guide notice.
To help grantee institutions cover the added cost, NIH is accepting applications for administrative supplements through the funding opportunity announcement Administrative Supplements to Existing NIH Grants and Cooperative Agreements.
Calculate your institution’s request for supplemental funding by factoring in the number of months remaining in the award’s budget period, the years of experience of each postdoc, and the difference in monthly stipend amounts following the increase. You can find examples of how to total the amount in the November 7, 2016 Guide notice.
The subsequent Notice of Award for the next budget year will reflect the new FY 2017 stipend levels.
Keep in mind, NIH is implementing this policy independently of the Department of Labor overtime regulations. Institutions should consult their own counsel when considering the applicability of overtime regulations to a particular worker supported by NIH grants.
NIH has long promoted open science and remains committed to ensuring that the results of agency-funded scientific research are, to the extent possible, publicly available to support reuse, reproducibility, and discovery.
To further develop priorities for data management, sharing, and citation, as well as strategies for expanding the Data Sharing Policy, NIH issued a request for information (RFI) soliciting public feedback on data sharing stewardship.
Topics of particular interest identified in the RFI include:
- Highest-priority types of data to be shared
- Costs and value of sharing different data types and how to overcome barriers to data sharing
- Length of time data should be available for secondary research purposes, best practices for maintaining and sustaining the data, and long-term resource implications
- Impact of increased reporting of data and software sharing in the Research Performance Progress Report and competing grant applications
- How to set standards for citation of shared data and software
- Incentives to encourage sharing of data and software
NIH also welcomes your input on related topics you recommend for consideration.
How to Provide Feedback
The deadline to respond to the RFI is December 29, 2016. Submit your comments electronically at NIH Request for Information on Strategies for NIH Data Management, Sharing, and Citation; alternatively, mail or fax your comments to the NIH Office of Science Policy. See “Submitting a Response” in the RFI linked below for further guidance.
Note that NIH will publicly publish all unedited responses, including personal information, after the comment period ends. For complete details about the RFI, read the November 14, 2016 Guide notice. Email questions to SciencePolicy@mail.nih.gov.
Head to NIAID Paylines to see the latest FY 2017 interim paylines for fellowship (F), career development (K), small business (R41, R42, R43, R44), and research project (R03, R15) grant applications.
Next time you need to contact the NIH Office of Extramural Research Grants Information service desk, use its new phone number: 301-945-7573. The service desk answers general inquiries about grants policies, processes, and funding opportunities on behalf of NIH.
We’ve received an outstanding response to Rapid Assessment of Zika Virus (ZIKV) Complications (R21). As a result, we no longer need to accept applications for this funding opportunity announcement (FOA) on a rolling basis. Thus, the FOA will be reissued either later this month or in January to follow standard NIH Application Due Dates. See the November 17, 2016 Guide notice for additional details.
Grantees whose awards use the R61/R33 or UG3/UH3 activity codes are now eligible to apply for administrative supplements through the following funding opportunity announcements: Research Supplements To Promote Diversity in Health-Related Research and Research Supplements To Promote Re-Entry into Biomedical and Behavioral Research Careers.
In your application, we advise you to name only formal co-investigators, consultants, and collaborators as key personnel. Avoid the temptation to list largely uninvolved people or suggest reviewers.
We understand why some applicants might want to name-drop. Knowing that there is an "Investigator" review criterion, you might hope the extra names will show how well-connected you are to particular experts in your area of science. However, your application is not improved by identifying scientists who aren't significantly advising or participating in your proposed project.
There's another risk: naming people or suggesting reviewers can make your review more challenging. To avoid a conflict of interest, NIH review staff can't allow anyone you name in your application to review your application. That includes colleagues in your immediate area of science who might otherwise have been your closest allies during a review.
Try not to point out anyone in particular as an appropriate reviewer. Instead, you should Use the PHS Assignment Request Form to list the areas of scientific expertise needed to understand and review your application.
For more advice on finding information on reviewers and how to write an application with them in mind, read Know Your Audience.
You can ask us a question at email@example.com. After responding, we may ask your permission to include your question in the newsletter.
Enacted annually, appropriations bills give federal agencies the authority to spend a defined amount of money for specified purposes.
Authorizations laws allow appropriations for a program or an agency for a year or more but do not indicate an amount of money. For more information, see “Appropriations Set the Dollars” in Background on NIAID Funding Opportunity Planning and the Budget Cycle.
- RFA-AI-16-080, Systems Biology: The Next Generation for Infectious Diseases (U19)
- NIAID-DAIDS-NIHAI2016075, Nonhuman Primate Virology Laboratory for AIDS Vaccine Research and Development
- PAR-17-056, Investigator-Initiated Extended Clinical Trial (R01)
- PAR-17-057, Global Infectious Disease Research Training Program (D43)
- RFA-AI-16-078, Limited Competition: Clinical Trials in Organ Transplantation in Children (CTOT-C): Mechanistic Ancillary Studies (U01)
- RFA-AI-16-086, Pilot Clinical Trials Targeting HIV-1 Reservoirs in Children (U01)
- NIAID-DAIDS-NIHAI2016069, Reagent Resource Support Program for AIDS Vaccine Development
See other announcements at Opportunities & Announcements.