IMPALA is pleased to share our latest work product “Data Analytics for Quality Assurance in Pharmaceutical Development Framework,” which offers insights and guidance on transforming Quality Assurance (QA) in Good Clinical Practice (GCP) and Good Pharmacovigilance Practice (GVP) through the application of advanced analytics.
This Framework reflects on the learnings and key decisions taken by the Intercompany Quality Analytics (IMPALA) Consortium to elevate the goal of advancing analytics in GCP and GVP. This framework can guide Quality Assurance in development, implementation and enhancement of their analytics and technology strategy, regardless of organizational maturity
Three Questions to Consider:
- How can your organization leverage data analytics to enhance risk oversight and quality management activities?
- What are the key challenges your organization faces in adopting data analytics for Quality Assurance?
- What cultural shifts and change management strategies are necessary to implement data analytics effectively in your organization?
For more details, you can access the full document here.
We hope this content will help you take steps towards a more effective and impactful approach to data analytics in Quality Assurance.
IMPALA extends acknowledgements to the contributors and editors who made this document possible.
If you use this framework in any form, IMPALA would love to hear back from you Framework@members.impala-consortium.org
