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The FDA/PhUSE collaboration was created to provide high-quality quantitative analysis of information on product safety, effectiveness and quality. The core infrastructure for FDA's scientific community will help support ongoing efforts in pre-market development, modernization of drug review, post-market safety and drug quality. Key projects within the FDA's Computational Science Center are in areas of developing data standards and expanding the use of electronic review tools.
Improving Data Quality
This working group will focus on collaborating to develop a robust process to rapidly validate and assess data quality as data moves through product life cycle across both industry and regulatory review. The group will discuss current pains and potential solutions regarding topics such as current data validation rules, therapeutic specific data issues and improving the quality of the data to support specific analytical needs.
Optimizing the use of Data Standards
The development and adoption of data standards over the last decade has shown significant promise in improving efficiencies in the product submission and review process. However, there have also been gaps, issues and challenges in the interpretation and use of the standards. This group will identify specific gaps preventing FDA and industry from optimizing the use of standards and collaborate to close those gaps.
Development of Standard Scripts for Analysis and Programming
With the development and implementation of industry data standards, there is a great opportunity to develop standard reporting across industry and to support the needs of FDA medical and statistical reviewers. This working group will identify potential standard scripts for data transformations and analyses across and within therapeutic areas. The goal will be to begin the process of standardizing analyses across the industry, but also include examples of what can be done with a standardized data set.
Non-Clinical Road-map and Impacts on Implementation
There is a need to improve nonclinical assessment and regulatory science by identifying key needs and challenges in the field and then establish an innovative framework for addressing them in a collaborative manner. The group created a framework for moving certain projects forward to support nonclinical informatics efforts and to develop specific implementation solutions and SEND.