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A Quality Risk Management Model Approach for Cell Therapy Manufacturing

Author

Listed:
  • Fabio Lopez
  • Chiara Di Bartolo
  • Tommaso Piazza
  • Antonino Passannanti
  • Jörg C. Gerlach
  • Bruno Gridelli
  • Fabio Triolo

Abstract

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.

Suggested Citation

  • Fabio Lopez & Chiara Di Bartolo & Tommaso Piazza & Antonino Passannanti & Jörg C. Gerlach & Bruno Gridelli & Fabio Triolo, 2010. "A Quality Risk Management Model Approach for Cell Therapy Manufacturing," Risk Analysis, John Wiley & Sons, vol. 30(12), pages 1857-1871, December.
  • Handle: RePEc:wly:riskan:v:30:y:2010:i:12:p:1857-1871
    DOI: 10.1111/j.1539-6924.2010.01465.x
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    References listed on IDEAS

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    1. James H. Lambert & Rachel K. Jennings & Nilesh N. Joshi, 2006. "Integration of risk identification with business process models," Systems Engineering, John Wiley & Sons, vol. 9(3), pages 187-198, September.
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    Cited by:

    1. Peter J. Majewicz & Paul Blessner & Bill Olson & Timothy Blackburn, 2020. "Estimating the Probability of Human Error by Incorporating Component Failure Data from User‐Induced Defects in the Development of Complex Electrical Systems," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 200-214, January.
    2. David M. Vanlandingham & Wesley Hampton & Kimberly M. Thompson & Kamran Badizadegan, 2020. "Modeling Pathology Workload and Complexity to Manage Risks and Improve Patient Quality and Safety," Risk Analysis, John Wiley & Sons, vol. 40(2), pages 421-434, February.

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