The effective auditing of laboratory data systems is essential in order to ensure that the expectations of regulatory agencies are met. This webinar will provide details of the most common non-conformances and provide staff members, who are unfamiliar with laboratory computer systems with an understanding of the controls that are necessary to ensure the integrity of analytical data. The webinar will teach participants the importance of correct data system configuration and what to look for during the audit. Businesses will benefit by reducing the risk of regulatory action as a result of failure to comply with current expectations. Areas Covered in the Session : Categories of laboratory data system (GAMP) Lifecycle management, archiving and backup What counts as raw data? Protecting the integrity of analytical data General guidance on assigning user privileges Operating system configuration. Application configuration Controls appropriate for chromatography data systems Practices that aid compliance with data integrity requirements Examples from recent FDA warning letters Who Should Attend: Staff who are required to audit analytical operations who do not have a chemical QC background Auditors who require updating on current regulatory expectations QC staff who needs help in regulatory compliance Staff who would like to understand the implications of data integrity for laboratory data systems


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Areas Covered in the Session :

  • Review the current regulatory requirements and guidances (CFR, EU GMPs, ISO, etc.) for environmental monitoring.
  • Discuss issues of sampling methods, selection of sampling sites and the justifications for them.
  • Review the issue of contamination control as an important aspect of EM programs.
  • Discuss the issue of action and alert limits, trending of data and the handling of excursions.
  • What are the most common deficiencies cited by regulatory auditors when auditing environmental monitoring programs?
  • Attendee question and answer period.

Who Should Attend:

  • QA/QC Teams
  • Manufacturing Teams
  • Engineering Teams
  • Validation Teams
  • Regulatory affairs Teams
  • Management Teams
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