During this presentation participants will have the opportunity to get an insight on the current signal detection and management guidelines and tools. What are the authorities’ expectations and findings in the signal management area? During the signal management session, pragmatic approaches, real life examples, lessons learned, as well as processes for signal management and eRMR assessment will be discussed.

• Routine signal detection methods in EudraVigilance
• Ongoing monitoring activities for signal detection
• Enhanced quantitative signal detection methods (data mining)
• Qualitative vs. quantitative assessment of ICSRs

PV inspections are an important process for the authorities to secure PV organisations live up to the legislation, and for PV organisations to secure they have created a QMS at the right level. The presentation will go through best practice for how to prepare and conduct an inspection, including virtual presentations. The presentation will also give examples of recent focus areas for the European authorities.

• PV inspections overall, including inspection set-up
• DKMA inspection on behalf of EMA
• Local PV inspection
• Virtual inspections
• Summary and conclusions

Clinical trials are a dynamic, changing, challenging and demanding environment. It provides with ongoing accumulation of feasibility, clinical and safety data. Blinding non-real time, third party data review with delayed medical monitoring assessment poses certain risks to potential signals detection, risk management, protocol amendments and eventually patient’s well-being and scientific data integrity. An issue that requires practical and pragmatic solutions.

• Medical monitoring, real-time, delayed, periodic
• Accumulating safety data, periodic reporting
• Educating your investigators, your colleagues and yourself
• Patients first, do the right thing, collect additional information
• Signals and trends, follow the science, know your pre-clinical and early clinical data

Modern day vigilance systems tend to generate enormous amounts of data from many different sources. These fragmented data sources create difficulties in identifying trends across complex processes and systems. Connecting these multiple data sources to a single platform supports a centralized tool facilitating continuous process improvements and early detection of operational risks