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Building towards Statistically-Based Pharmaceutical Quality Standards (U01)

Post Date

July 31st 2015

Application Due Date

October 16th 2015

Funding Opportunity Number

RFA-FD-16-003

CFDA Number(s)

93.103

Funding Instrument Type(s)

Cooperative Agreement

Funding Activity Categories

Consumer Protection
Food and Nutrition
Health

Number of Awards

2

Eligibility Categories

State Governments
County Governments
City or Township Governments
Special District Governments
Independent School Districts
Public and State Controlled Institutions of Higher Education
Federally Recognized Native American Tribal Governments
Public Housing Authorities or Indian Housing Authorities
Non-Federally Recognized Native American Tribal Organizations
Non-Profits With 501 (c) (3) Status With The IRS (Except Higher Education Institutions)
Non-Profits Without 501 (c) (3) Status With The IRS (Except Higher Education Institutions)
Private Institutions of Higher Education
For-Profit Organizations (Except Small Businesses)
Small Businesses
Other

Non-domestic (non-U.S.) Entities (Foreign Institutions) are eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are eligible to apply. Foreign components, as defined in the HHS Grants Policy Statement, are allowed.

Funding

  • Estimated Total Funding:

    $2000000

  • Award Range:

    $None - $1000000

Grant Description

The goal of this project is to generate data and develop a statistical sampling and analysis strategy to aid FDA/CDER policy in drafting data-based guidance in support of the use of appropriate statistical tools and standards. Specifically, the development of standards for statistical methods suitable for lot release which could be used to drive industry towards increased product and process understanding throughout the lifecycle of a product. The project will provide data, sampling and data analysis approaches to inform for the agency and the human pharmaceutical industry to advance the development of risk- and science-based standards. These projects could be split into subsets by product type, process type, manufacturing complexity and/or therapeutic index to facilitate understanding.

Contact Information


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