To understand the value of computer-aided disproportionality analysis (DA) in relation to current pharmacovigilance signal detection methods, four products were retrospectively evaluated by applying an empirical Bayes method to Merck's post-marketing safety database. Findings were compared with the prior detection of labeled post-marketing adverse events. Disproportionality ratios (empirical Bayes geometric mean lower 95% bounds for the posterior distribution (EBGM05)) were generated for product-event pairs. Overall (1993-2004 data, EBGM05> or =2, individual terms) results of signal detection using DA compared to standard methods were sensitivity, 31.1%; specificity, 95.3%; and positive predictive value, 19.9%. Using groupings of synonymous labeled terms, sensitivity improved (40.9%). More of the adverse events detected by both methods were detected earlier using DA and grouped (versus individual) terms. With 1939-2004 data, diagnostic properties were similar to those from 1993 to 2004. DA methods using Merck's safety database demonstrate sufficient sensitivity and specificity to be considered for use as an adjunct to conventional signal detection methods.

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For many years, approvals of new drugs in Japan have lagged behind those in the United States and Europe. As a result of simultaneous global development strategies, more widespread inclusion of Japan in multiregional clinical trials, and significant reforms and investment in Japan's Pharmaceuticals and Medical Devices Agency reviewer capacity and capability, the drug lag appears to be diminishing. This is allowing new medicines to be approved sooner in Japan, improving the efficiency of drug development and benefiting patients.

As the transition to model-based drug development continues, pharmacometric analysis will have an increasingly important role across the entire life cycle of drug discovery, development, regulatory approval, and commercialization. For this reason, pharmacometrics can--and should--have an integrating function in the transformation to model-based development. This essay describes an approach for formalizing the pharmacometrics process using the disciplines encompassed by enterprise engineering.

The importance of detecting postmarketing safety signals earlier and with a high degree of fidelity is increasingly important and of great interest to industry, regulators, and the public. This issue of Clinical Pharmacology & Therapeutics contains two companion articles that represent exciting new advances in the field of pharmacovigilance and postmarketing safety signal detection. Given that drug safety evaluation and pharmacovigilance science are core competencies in the discipline of clinical pharmacology, these articles should be of interest to clinical pharmacologists as well as drug safety professionals.