Effective data quality governance: challenging five common myths

Effective data governance is essential for seamless connection and data sharing across regulatory, safety, clinical research, and manufacturing processes in the pharmaceutical industry. Key strategies for implementing data quality governance include starting with manageable steps, challenging myths about its complexity and cost, and focusing on culture and organization rather than just technology. Critical elements include establishing clear data quality roles, embedding a data quality mindset, and maintaining transparency and continuous improvement. A phased approach—starting with setting up a framework, followed by operational adjustments and eventually cultural integration—ensures systematic and sustainable improvements in data quality.

Opens on European Pharmaceutical Review