In the last 5 years, regulatory agencies and drug monitoring centres have been developing computerised data-mining methods to better identify reporting relationships in spontaneous reporting databases that could signal possible adverse drug reactions. At present, there are no guidelines or standards for the use of these methods in routine pharmaco-vigilance. In 2003, a group of statisticians, pharmaco-epidemiologists and pharmaco-vigilance professionals from the pharmaceutical industry and the US FDA formed the Pharmaceutical Research and Manufacturers of America-FDA Collaborative Working Group on Safety Evaluation Tools to review best practices for the use of these methods.In this paper, we provide an overview of: (i) the statistical and operational attributes of several currently used methods and their strengths and limitations; (ii) information about the characteristics of various postmarketing safety databases with which these tools can be deployed; (iii) analytical considerations for using safety data-mining methods and interpreting the results; and (iv) points to consider in integration of safety data mining with traditional pharmaco-vigilance methods. Perspectives from both the FDA and the industry are provided. Data mining is a potentially useful adjunct to traditional pharmaco-vigilance methods. The results of data mining should be viewed as hypothesis generating and should be evaluated in the context of other relevant data. The availability of a publicly accessible global safety database, which is updated on a frequent basis, would further enhance detection and communication about safety issues.

Robust tools for monitoring the safety of marketed therapeutic products are of paramount importance to public health. In recent years, innovative statistical approaches have been developed to screen large post-marketing safety databases for adverse events (AEs) that occur with disproportionate frequency. These methods, known variously as quantitative signal detection, disproportionality analysis, or safety data mining, facilitate the identification of new safety issues or possible harmful effects of a product. In this article, we describe the statistical concepts behind these methods, as well as their practical application to monitoring the safety of pharmaceutical products using spontaneous AE reports. We also provide examples of how these tools can be used to identify novel drug interactions and demographic risk factors for adverse drug reactions. Challenges, controversies, and frontiers for future research are discussed.

In a phase 2 study of the mixed μ-opioid receptor agonist/δ-opioid receptor antagonist eluxadoline vs placebo in patients with IBS-D, patients given eluxadoline were significantly more likely to be clinical responders, based on a composite of improvement in abdominal pain and stool consistency. Further study of eluxadoline is warranted to assess its potential as a treatment for IBS-D.

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Sphingolipids are emerging as key regulators of cellular metabolism, proliferation, and apoptosis (1, 2). One of the cellular actions of sphingolipids is the release of Ca2+ from intracellular stores (3, 4). Sphingosine, sphingosine phosphate, and sphingosyl-phosphocholine (SPC) all mediate release of Ca>+ from intracellular stores. Until recently, the mechanism by which sphingolipids could release Ca2+ from intracellular stores was unknown. We have described the electrophysiological and biophysical properties of a sphingolipid-gated intracellular Ca'+-permeable channel (5, 6). The sphingolipidgated Ca2+-permeable channel is unlike other known channels. It is not blocked by La3, a prototypical blocker of Ca> selective channels, nor is it blocked by heparin, nifedipine, w-conotoxin, or Ni2+, all selective blockers of specific classes of voltage-gated and ligand-gated intracellular and plasma membrane Ca>+ channels. We developed an assay to examine expression of sphingolipid-gated Ca2+ release from the intracellular stores of Xenopuls oocytes (6). With this, we demonstrated that the mRNA encoding the intracellular sphingolipid-gated Ca2+ release activity is 1.8 kb, much smaller than the 1 16-kb ryanodine receptor message (7), or the -9-kb message

The performance differences between the PRR and MGPS methods are related to (i) greater confounding by demographic factors with PRR; (ii) a higher tendency of PRR to detect false-positive signals when the number of reports is small; and (iii) the conventional thresholds that have been adapted for each method. PRR tends to be more 'sensitive' and less 'specific' than MGPS. A high-specificity disproportionality method, when used in conjunction with medical triage and investigation of critical medical events, may provide an efficient and robust approach to applying quantitative methods in routine postmarketing pharmacovigilance.