PDA survey of quality risk management practices in the pharmaceutical, devices, & biotechnology industries

PDA J Pharm Sci Technol. 2008 Jan-Feb;62(1):1-21.

Abstract

In July 2006 the Parenteral Drug Association's Risk Management Task Force for Aseptic Processes, conducted an electronic survey of PDA members to determine current industry practices regarding implementation of Quality Risk Management in their organizations. This electronic survey was open and publicly available via the PDA website and targeted professionals in our industry who are involved in initiating, implementing, or reviewing risk management programs or decisions in their organizations. One hundred twenty-nine members participated and their demographics are presented in the sidebar "Correspondents Profile". Among the major findings are: *The "Aseptic Processing/Filling" operation is the functional area identified as having the greatest need for risk assessment and quality risk management. *The most widely used methodology in industry to identify risk is Failure Mode and Effects Analysis (FMEA). This tool was most widely applied in assessing change control and for adverse event, complaint, or failure investigations. *Despite the fact that personnel training was identified as the strategy most used for controlling/minimizing risk, the largest contributors to sterility failure in operations are still "Personnel". *Most companies still rely on "Manufacturing Controls" to mitigate risk and deemed the utilization of Process Analytical Technology (PAT) least important in this aspect. *A majority of correspondents verified that they did not periodically assess their risk management programs. *A majority of the correspondents desired to see case studies or examples of risk analysis implementation (as applicable to aseptic processing) in future PDA technical reports on risk management.

MeSH terms

  • Biotechnology / statistics & numerical data
  • Biotechnology / trends*
  • Drug Industry / classification*
  • Drug Industry / statistics & numerical data
  • Equipment and Supplies*
  • Humans
  • Risk Management / methods*
  • Surveys and Questionnaires