Signal detection is a critical part of the overall risk management process and has evolved quite significantly over the last few years. Various signal detection methods have been developed and applied to probe the adverse event databases to identify identification of disproportionality in the particular drug adverse event pairs. It is quintessential to accurately track and manage signals keeping in view the growing importance of stringent regulations across the globe. Signals in pharmacovigilance have a variety of sources. Pharmacovigilance may not rely upon one single method, but needs a strategy of complementary activities. Statistical data mining approaches have been developed and applied in the field of drug safety surveillance, adding to the toolkit of pharmacovigilance professionals. The study revealed that no statistical methods or algorithms would replace the importance of medical and scientific judgment of trained pharmacovigilance professionals. 
Conclusion	There is no single right approach that would be optimal for all medicinal products in all situations. It is necessary to find an optimum balance, not just with regard to the use of statistics (Frequentist vs Bayesian) but also among thresholds used for signal detection. A number of investigations explored whether differences exist between Frequentist and Bayesian approaches and found that PRR is more sensitive than MGPS, although the estimation from the MGPS is believed to be more robust when the number of reports is small. Further development of statistical methods and technological solutions to analyse large amounts of data to detect signals for potential safety issues, while minimizing noise, would enhance the efficiency and effectiveness of pharmacovigilance activities. Overall, data derived from DMAs should be considered with caution and guided by appropriate clinical evaluation. This clinical perspective should always be considered to support really appropriate drug use, balancing drug effectiveness, safety and, above all, actual patients’ needs. The statistical procedures underlying contemporary data mining cannot offset the limitations of spontaneous reporting system data. Qualitative medical review and assessment are indispensable to guide the quantitative analysis and evaluation. As the amount of information increases, codifying human experts’ tacit reasoning and consistent application of sound pharmacovigilance logic become more and more important in supporting proactive and scalable safety surveillance.

Evaluation of signal detection and validation methods in Pharmacovigilance: US and EU perspective

DIA Europe 2020 

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