Early Detection of Important Safety Information

— Recent Methods for Signal Detection —

Abstract

It is very important to provide safety information of new drugs to physicians and patients as soon as possible after the early postmarketing period. For that purpose, it is important to appropriately collect and analyze the spontaneous reports accumulated in databases of companies and regulatory agencies. This paper reviews the analytical methods to assess spontaneous reports. Bate et al. (1998) presented Bayesian Confidence Propagation Neural Network (BCPNN) Method used by Uppsala Monitoring Centre (UMC) of the World Health Organization (WHO). DuMouchel (1999) presented Gamma-Poisson Shrinker (GPS) Program of U. S. Food and Drug Administration (FDA), and Evans et al. (2001) presented Proportional Reporting Ratios (PRR) of the Medicines Control Agency (MCA). Furthermore, DuMouchel and Pregibon (2001) extended the GPS Program, proposing the Multi-Item Gamma Poisson Shrinker (MGPS) Program, which then became the standard method for the FDA. This report also reviews the practical problems (e.g. database, duplication cases, code of Medical Dictionary for Regulatory Activities (MedDRA)) encountered in Japan.