Utilizing Real-World Data and Algorithmic Analyses to Assess Post-Market Clinical Outcomes in Patients Switching Amongst Therapeutically Equivalent Complex Generic Drug Products and Reference Listed Drugs (U01) Clinical Trial Not Allowed

Key Facts

Status: Open

Posted date: November 24, 2023

Opportunity ID: 351125

Opportunity number: FOR-FD-24-003

Opportunity category: Discretionary

Agency name: Food and Drug Administration

Agency code: HHS-FDA

Award floor: $300,000

Award ceiling: $300,000

Cost sharing required: No

Funding Instrument Types
  • Cooperative Agreement
Category of Funding Activity
  • Agriculture
  • Consumer Protection
  • Food and Nutrition
Eligible Applicants
  • City or township governments
  • County governments
  • For-profit organizations other than small businesses
  • Independent school districts
  • Native American tribal governments (Federally recognized)
  • Native American tribal organizations (other than Federally recognized tribal governments)
  • Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education
  • Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education
  • Private institutions of higher education
  • Public and State controlled institutions of higher education
  • Public housing authorities/Indian housing authorities
  • Small businesses
  • Special district governments
  • State governments
  • Unrestricted
Tools
Categories (use these for quoted searches)
  • agency_code:hhs_fda
  • category_of_funding_activity:agriculture
  • category_of_funding_activity:consumer_protection
  • category_of_funding_activity:food_and_nutrition
  • cost_sharing_or_matching_requirement:false
  • eligible_applicants:city_or_township_governments
  • eligible_applicants:county_governments
  • eligible_applicants:for_profit_organizations_other_than_small_businesses
  • eligible_applicants:independent_school_districts
  • eligible_applicants:native_american_tribal_governments_federally_recognized
  • eligible_applicants:native_american_tribal_organizations_other_than_federally_recognized_tribal_governments
  • eligible_applicants:nonprofits_having_a_501_c_3_status_with_the_irs_other_than_institutions_of_higher_education
  • eligible_applicants:nonprofits_that_do_not_have_a_501_c_3_status_with_the_irs_other_than_institutions_of_higher_education
  • eligible_applicants:private_institutions_of_higher_education
  • eligible_applicants:public_and_state_controlled_institutions_of_higher_education
  • eligible_applicants:public_housing_authoritiesindian_housing_authorities
  • eligible_applicants:small_businesses
  • eligible_applicants:special_district_governments
  • eligible_applicants:state_governments
  • eligible_applicants:unrestricted
  • funding_instrument_type:cooperative_agreement
  • opportunity_category:discretionary
  • status:open
Description

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.

Utilizing Real-World Data and Algorithmic Analyses to Assess Post-Market Clinical Outcomes in Patients Switching Amongst Therapeutically Equivalent Complex Generic Drug Products and Reference Listed Drugs (U01) Clinical Trial Not Allowed
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.
Utilizing Real-World Data and Algorithmic Analyses to Assess Post-Market Clinical Outcomes in Patients Switching Amongst Therapeutically Equivalent Complex Generic Drug Products and Reference Listed Drugs (U01) Clinical Trial Not Allowed
Open
Food and Drug Administration
Agriculture
Food and Nutrition
Consumer Protection
Cooperative Agreement
State governments
County governments
City or township governments
Special district governments
Independent school districts
Public and State controlled institutions of higher education
Native American tribal governments (Federally recognized)
Public housing authorities/Indian housing authorities
Native American tribal organizations (other than Federally recognized tribal governments)
Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education
Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education
Private institutions of higher education
For-profit organizations other than small businesses
Small businesses
Unrestricted
2023-11-24