Complex generic drug products represent an increasing share of the generic marketplace and may have distinct user interface differences compared to reference listed drug (RLD) products.
A modernized post-market surveillance approach is needed to compare clinical outcomes between complex generic
products and their corresponding RLD products to monitor for potential issues with therapeutic equivalence and to inform regulatory decision making.
Real-world data (RWD) combined with machine learning (ML) and/or artificial intelligence (AI) could help to identify post-market signals efficiently in an automated and repeatable fashion, facilitating timely regulatory action.
The purpose of this funding opportunity is to develop and test an AI- or ML-based algorithmic RWD model for post-market surveillance of complex generic drug products.
Relevant Nonprofit Program Categories
Obtain Full Opportunity Text:NSF Publication 24-526
Additional Information of Eligibility:Eligible Applicants: Eligibility is limited to the alumni of U. S. government-sponsored exchange programs, who are citizens or residents of Georgia.
(https://alumni.state.gov/list-exchange-programs) Other Eligibility Requirements: Applicants are only allowed to submit a maximum of two proposal per individual.
If more than two proposals is submitted from an individual, all proposals from that individual will be considered ineligible for funding.
If a group of alumni cooperate to submit a joint project, the requested amount cannot exceed $20,000.
The submitting applicant should be an individual alumnus/alumna or the group of alumni, but the grant can be awarded to the organization partnering in the project.
If the organization will be the awardee, they need to present active SAM.gov registration prior to awarding process.
SAM.gov registration for applicant individuals is not required.
Full Opportunity Web Address:http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf24526Contact: Agency Email Description: terrin.brown@fda.hhs.gov
Agency Email: Date Posted: 2024-01-15
Application Due Date: Archive Date: 2024-04-30