The main goal of this proposal is to generate data and develop a statistical sampling/analysis strategy to aid FDA/COER policy in drafting data-based guidance in support of the use of appropriate statistical tools and standards. The goal will be addressed by organizing the work under the following specific aims: 1) Selection of recently distributed pharmaceutical products: Develop a selection rationale to identify major dosage form categories based on the complexity of the dosage form and key characteristics including dose, release mechanism, BCS, therapeutic index, and manufacturing method. 2) Sampling organization and data generation: Organize the sampling to insure that sufficient data are collected for the range of statistical treatments to be developed and tested. Generate the data for selected critical quality, chemical and physical attributes (e.g., tablet weight, hardness, friability, assay, content uniformity, and dissolution) and determine the mean and variance of the entire sample. 3)Comparative estimation accuracy of current/proposed models: Using current standards and alternate models' ability to predict the means and variance against those actually observed from experimentation. 4) Generate standards and alternates for dosage form category specific statistical methods: Develop and identify approaches for inter and intra-category variability suitable for lot release for the categories of dosage forms studied. Variability in the way drug products perform is a major reason for product recalls and potentially negative outcomes in the patient population. This variability may be manifested in the physical-chemical characteristics of the final dosage form as produced, the way it delivers the drug substance, or the way it retains the desired behavior with time, i.e., the self-life. The goal of process control and product testing is to assess the quality of the dosage forms upon release to detect issues and to anticipate problems that may occur during its shelf-life. Because different dosage forms may be designed to perform differently and be variable over a range of characteristics, the proposed project will provide both an exhaustive benchmarking of the variability over the range of dosage forms currently marketed and advanced statistical analysis tools that are ?tailored? to identity meaningful variability within each categories of dosage form identified. This will be driven by an adaptive statistical approach for directing the experimentation as well as developing to desired dosage form category specific tools. The significance of the project is that; 1) it will provide targeted statistical methods to be applied to product release and trouble shooting for the major dosage form categories, and 2) these methods will facilitate the review and approval of new drug products and generic drug products. Together this means higher quality, reduced time to market, and reduced cost.

Public Health Relevance

The proposed project will provide both an in depth benchmarking of the variability over the range of dosage forms currently marketed and advanced statistical analysis tools that are ?tailored? to identity meaningful variability within each categories of dosage form identified. This will be driven by an adaptive statistical approach for directing the experimentation as well as developing to desired dosage form category specific tools. The significance of the project is that; 1) it will provide targeted statistical methods to be applied to product release and trouble shooting for the major dosage form categories, and 2) these methods will facilitate the review and approval of new drug products and generic drug products.

Agency
National Institute of Health (NIH)
Institute
Food and Drug Administration (FDA)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01FD005680-01
Application #
9168711
Study Section
Special Emphasis Panel (ZFD1-SRC (99))
Project Start
2016-06-01
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
1
Fiscal Year
2016
Total Cost
$1,000,000
Indirect Cost
Name
Long Island University Brooklyn Campus
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
City
Greenvale
State
NY
Country
United States
Zip Code
11548