The PDA Quality & Regulations Conference was held on October 5 and 6, 2022 in Amsterdam; it was healthily attended by a variety of multi-national pharma manufacturers as well as representatives of regulatory bodies from multiple EU countries as well as the USFDA.
The agenda was very much data‑driven as presenters focused on how data and digitization have the potential to feed directly into quality management maturity models, impact risk management approaches, and ultimately drive improved product quality and patient outcomes.
One highlight across the conference timetable was a presentation by Prof. Thomas Friedli and his colleagues from the University of St. Gallen. The presentation focused on how data-centered intelligence can contribute to improvements in manufacturing quality. An interesting finding from his research has been the absence of correlation between internal audit and regulatory authority observations. This deficiency pointed to the core message of many of the presentations – how data-driven risk-based decision making can be successful only if robust and effective quality risk management tools are utilized as part of a comprehensive and efficient PQS across manufacturing and supply‑chain networks. The recurrent message of this presentation (and others) was that good data governance is a core feature of the Culture of Quality within a company, and key quality systems, such as internal audit, play crucial roles in ensuring an effective Quality environment.
Day 2 opened with several interesting presentations from current and former regulators, particularly with regard to managing inspections during the pandemic, training and continuing professional development of inspectors, and hot topics related to data integrity and governance (which regulators are currently focused on). Unsurprisingly, real-time implementation of ICH Q9 and Q10 principles, particularly regarding the generation, management, and interpretation of data, generated much interest. It appears that, while many companies are increasingly utilizing data to make lead-indicator decisions regarding product quality, regulatory concerns remain regarding the maturity of the models employed to govern data quality. As always, regulatory expectations are increasing as the industry moves to optimize inputs and digitize outputs from operations. More than ever, the requirements for robust QRM (Quality Risk Management) processes for monitoring and enhancing performance at operational level and, most importantly, for ensuring product quality and patient safety are expected rather than desirable.
Read our blog here on the future of quality to understand the importance of this rapidly growing trend.
