SARS-CoV-2 and COVID-19 research supplements

Idaho INBRE researchers and mentors – please note the urgent message below:

From our INBRE Program Officer – re: SARS-CoV-2 and COVID-19 research supplements

The new NIGMS NOSI for SARS-CoV-2 and COVID-19 urgent awards was just published: NOT-GM-20-025: Notice of Special Interest (NOSI) regarding the Availability of Urgent Competitive Revisions for Research on Coronavirus Disease 2019 (COVID-19) and the Causative Virus SARS-CoV-2

NIGMS Feedback Loop about this Notice is also posted at: thttps://loop.nigms.nih.gov/2020/03/urgent-competitive-revisions-to-nigms-grants-to-address-the-coronavirus-pandemic/

We’ve published a notice of special interest (NOSI) (NOT-GM-20-025) to address the urgent need for research on the SARS-CoV-2 virus. We’ll accept competitive revisions (supplements) in three specific scientific areas:

• Incorporation of data related to SARS-CoV-2 into ongoing research efforts to develop predictive models for the spread of SARS-CoV-2 and other related infectious agents (all grant and cooperative agreement activity codes)
• Repurposing or modification of diagnostic tools currently under development to enable rapid detection of SARS-CoV-2 infection (SBIR/STTR grants only)
• Rapid development of potential therapeutic agents for COVID-19 (SBIR/STTR grants only)

 Please note that applications that aren’t responsive to these three areas will be withdrawn without review.

Applications will be accepted on a rolling basis until February 5, 2021, and will be evaluated quickly by an internal review panel convened by NIGMS staff. In addition to other review criteria, applications will be judged on the urgency, significance, and feasibility of the proposed research.

Awards will be made for 1 year. Competitive revisions to R15, R21, and R00 grants may provide support above the established budget limits for the parent awards.

Investigators interested in applying for competitive revisions in response to this NOSI are strongly encouraged to contact NIGMS staff. For inquiries related to predictive models, contact Daniel Janes. For inquiries related to SBIR/STTR, contact Dmitriy Krepkiy