Phil Nethercote, independent pharmaceutical industry consultant and Stephanie Harden, global pharmaceutical marketing manager, Waters, discuss the types of error mitigation tools that ensure the quality of data and products among pharma companies.
Key insights:
- Pharmaceutical companies go to great lengths to assure the quality of the data they produce and any error that arises during execution of an analytical procedure must be thoroughly investigated.
- It's important that as part of any investigation, the lab supervisor works closely with the analysts to truly understand the route cause.
- Adopting a detailed structured investigation, identifying the true root cause, and implementing an appropriate CAPA are key to reducing the frequency of errors due to humans.
The reliability of analytical data in the pharmaceutical industry is critical in providing assurance of product quality. As such, data quality is a topic which receives significant focus from regulatory authorities. Pharmaceutical companies go to great lengths to assure the quality of the data they produce and any error that arises during execution of an analytical procedure must be thoroughly investigated, and appropriate corrective and preventative actions taken (CAPA). Not only can an error in performing an analysis have an impact on product quality but frequent errors can lead to significant waste of resources and lead to delays in product flow through a facility.