PHARMACEUTICAL INDUSTRY :
Process Capability and Control
  Client:   A major global pharmaceutical company with facilities in the U.S. and Puerto Rico manufacturing ethical drugs in a variety of dosage forms.
     
  Problem:   A product with a long manufacturing history was exhibiting an unacceptable degree of variation in a critical release parameter resulting in some batch rejections and many investigations. In total, the client was collecting data for over 50 parameters. Early development reports and "tribal knowledge" suggested the client knew which of the 50 parameters were "critical" to controlling variation in the key release parameter in question. The data for those parameters resided in multiple locations (e.g. analytical lab, batch records, raw material CoAs, etc.) and in both electronic and paper form. Recent client efforts made to reduce this variation met with only modest success, suggesting the relationship of key product parameters was not fully understood.
     
  Approach:   A Tunnell team, consisting of a pharmaceutical scientist, a statistician, a process analyst, and a data analyst, followed a structured methodology for identifying the root causes of process parameter variation customized for the client's specific situation. Historical process data for all variables was collected and organized into a single electronic database. Process control charts were developed and analyzed. Process capability analysis was performed. Variables were grouped and prioritized based on the capability analysis and insights from Tunnell scientists. In-depth process walk-throughs by experienced pharmaceutical scientists were conducted. Advanced statistical analysis was performed on the data. Focus interviews and focus groups were conducted to mine the collective insight of the client organization.
     
  Results:  
  • Multiple sources of variation were identified
  • New process knowledge was gained related to the relationship between key process parameters (cause-and-effect relationships)
  • Specific recommendations were developed and implemented to reduce variation resulting in significant improvement in process capability and reduced risk of batch rejection and investigations
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