Identification and Evaluation of Safety Signals of Drugs Currently under Development Using a Limited Data Set - B. K. Romanov; N. I. Zykova; R. N. Alyautdin; Yu. V. Olefir (Ministry of Health of the Russian Federation, Federal State Budgetary Institution «Scientific Centre for Expert Evaluation of Medicinal Products», 2019)
A recent increase in the number of safety signals of varying quality being submitted to the national and industry databases calls for the development of formalized search and analysis algorithms. The aim of the study was to develop an approach to identification and evaluation of safety signals in the database of an expert institution containing notifications of serious adverse events (SAE) that occurred during clinical trials. A specific feature of this approach is that it can be used in limited databases which, unlike international databases containing millions of reports (VigiBase, EudraVigilance), preclude the use of statistical methods for measurement of disproportionality. The proposed approach consists in evaluation of several criteria: two discriminatory ones (the geographic location of the clinical trial site and the type of report - whether it belongs to clinical trial documents other than the CIOMS form), and four expert criteria (whether a serious adverse event is a serious adverse reaction, whether the serious adverse reaction is predictable or not, the degree of reliability of the cause-effect relationship, and the benefit-risk ratio). The application of this approach resulted in the development of the «Signals» module of the expert institution's SAE database. The «Signals» module is designed to calculate the rating of safety signals which can be used for conclusive identification and management of safety signals, and provides basis for scientifically well-grounded expert decisions on the need for administrative action on the clinical trial or its further monitoring. The developed approach can be used in the industry, national, and international pre- and postauthorization pharmacovigilance databases.