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Signal management in pharmacovigilance is a process of multiple activities evaluating risks associated with a particular medicinal product, or whether known risks associated with a particular drug have changed in frequency or severity. The signal management process follows a systematic approach: Signal detection, Signal Validation Signal prioritization, Signal assessment, Recommendation for action, and finally Exchange of information. Signal detection is the most vital part of signal management. Traditional methods include usage of solitary algorithms which are not accompanied by additional features of qualitative data mining resulting in mediocre performance. TCS scientists devised a hybrid approach in which the algorithm is fueled to assess a signal and also manage it for effective grading based on a qualitative approach.
In this paper we provide a comprehensive and detailed description of this hybrid approach.
About the authors
Image of Dr. Alejandra Guerchicoff
Dr. Alejandra Guerchicoff
Dr. Alejandra Guerchicoff is a PhD in molecular genetics with a post-doctoral training in molecular cardiology. She is working as an Industry Advisor for TCS ADD platform with the Life Sciences unit at Tata Consultancy Services (TCS). Dr. Guerchicoff possesses a rich experience of more than 20 years in the domain of clinical research and post-marketing pharmacovigilance, for medical devices, drugs, combination products, gene and cell therapy, and software as medical device products.
Image of Ashutosh Pachisia
Ashutosh Pachisia
Ashutosh Pachisia is a Data Scientist at Tata Consultancy Services (TCS). With nearly half a decade of experience in IT. He has a rich experience leading large complex programs and driving key initiatives for TCS Healthcare.
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