Sunday, May 9, 2010

Quality Data Pertaining to Clinical Submission - Pharma and FDA

In my experience, greater communication between the pharma industry and FDA is needed when determining quality and adequate clinical submission data handling and cleanup. Pharma and FDA go to great lengths and great expense to ensure data quality. Industry's efforts ensuring clinical submission data quality includes but is not limited to:

  • checking source data and documentation in the field
  • the use of double data entry systems
  • the use of data process cleanup in-process checks
  • computerized data quality checks
  • the use of standard operating procedures for the review of data listings
  • the use of standard operating procedures to identify data outliers
  • the use of standard operating procedures to identify data inconsistencies
  • the use of standard operating procedures to identify data omission
  • the use of standard operating procedures to determine rate of data error
  • the use of validation systems to ensure quality data
  • the use of extensive documentation pertaining to data handling plans
  • the use of extensive quality management data plans
  • the use of extensive documentation plans pertaining to data inconsistencies
  • how to handle agreements when data changes are implemented.

Pharma and FDA both use qualified and experienced clinical submission individuals and teams in order to verify the quality of data.

  • QC
  • QA
  • Auditors
  • Medical Reviewers, Examiners
  • Statisticians
  • Analysis Programmers.

I am certain there is a duplication of effort between FDA and pharma to ensure clinical submission quality data. During an audit for example, FDA reviews all of the clinical submission data and not just the primary endpoints of safety and efficacy. The perception among pharma is that FDA Medical Reviewers and Examiners do not like to find any errors, omissions, or inconsistencies in clinical submission data, even in minor secondary variables and that the application will lose credibility should minor errors occur. Pharma's view is that there is no acceptable error rate. Not completely true! FDA has been proactive in developing regulations and guidelines to ensure quality data pertaining to clinical submission, electronic data formats, eCTD, CTD formats and backbones, nomenclature and terminology, and other related topics. There are obstacles however to joint efforts by FDA and the industry such as inconsistencies among FDA divisions and pharma in terms of computer hardware and software, computer literacy, review standards, integration standards, analysis standards, other related topics. Greater communication early in presubmission and clinical submission strategies and planning between industry and FDA to develop clinical submission data management and data quality measurements and guidelines for your submittable data would eliminate such data perception and help to manage concerns. Develop a communicative partnership with FDA early to ensure a "same page" approach to your clinical submission data and quality measures.

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