Safety information on QT-interval prolongation: comparison of European Union and United States drug labeling

Dysglycemia and arrhythmias

Disorders in glucose metabolism can be divided into three separate but interrelated domains, namely hyperglycemia, hypoglycemia, and glycemic variability. Intensive glycemic control in patients with diabetes might increase the risk of hypoglycemic incidents and glucose fluctuations. These three dysglycemic states occur not only amongst patients with diabetes, but are frequently present in other clinical settings, such as during critically ill. A growing body of evidence has focused on the relationships between these dysglycemic domains with cardiac arrhythmias, including supraventricular arrhythmias (primarily atrial fibrillation), ventricular arrhythmias (malignant ventricular arrhythmias and QT interval prolongation), and bradyarrhythmias (bradycardia and heart block). Different mechanisms by which these dysglycemic states might provoke cardiac arr-hythmias have been identified in experimental studies. A customized glycemic control strategy to minimize the risk of hyperglycemia, hypoglycemia and glucose variability is of the utmost importance in order to mitigate the risk of cardiac arrhythmias.

Drug-induced QT Prolongation Atlas (DIQTA) for enhancing cardiotoxicity management

Drug-induced prolongation of the QT interval is common in a variety of pharmaceutical treatments and can lead to serious clinical outcomes. Although substantial efforts have been made to prevent drug-induced QT interval prolongation, the lack of a centralized data source remains the main obstacle to further study of the underlying mechanism and the development of effective prediction strategies. To fill this gap, we propose a schema for stratifying the risk of marketed QT prolonging drugs based on US Food and Drug Administration (FDA)-approved drug labeling and developed a Drug-Induced QT Prolongation Atlas (DIQTA). Potential application of DIQTA was shown by precision dosing in off-label use and therapeutic strategy optimization, as well as the facilitation of artificial intelligence (AI)-based modeling in predictive toxicity.

Consistency of listed indications and contraindications between the U.S., the U.K., Japan, and Korea on prescription drug labels

Inclusion of indications and contraindications in drug labeling is essential for drug approval. Little is known regarding how well new drug information labels agree across countries. To compare the number of indications and contraindications on the labels of drugs in the U.S., U.K., Japan, and Korea, we selected 81 new drugs approved in these countries between 2008 and 2016 and assessed the number of indications and contraindications on each label. Average and median numbers with standard deviations were presented for the 81-drug set, and for subsets grouped according to drug class. Correlation analyses were conducted to estimate Pearson and concordance correlation coefficients. No significant difference was observed across countries in the number of indications, the average being 1.69, 1.67, 1.54, and 1.51 in the U.S., the U.K., Korea, and Japan (p = 0.31), respectively. By contrast, substantial variation was observed in the number of contraindications, the average being 1.54, 2.42, 3.53, and 3.00 in the U.S., the U.K., Korea, and Japan (p < 0.001), respectively. Pearson correlation coefficients comparing contraindications were 0.40, 0.48, and 0.47 for U.S.-U.K., U.S.-Korea, and U.S.-Japan, but 0.83, 0.73, and 0.71 for U.K.-Korea, U.K.-Japan, and Korea-Japan, respectively (p < 0.01). There is consistency in the number of indications, but a substantial discrepancy in contraindications listed in drug labeling across countries. Further study is warranted to improve global harmonization of contraindication listings.

Differences between the United States and Japan in labels of oncological drugs

PURPOSE

Our study addresses how the information in the labels differed between United States (US) and Japan, what factors were associated with the decision to place the boxed warning on the label, and the relation of both countries in terms of drug label policy.

METHODS

We investigated adverse drug reactions (ADRs) in boxed warnings for 44 oncological drug labels approved from 2004 to 2014 in both Japan and the US. We applied conditional logistic regression to examine how likely it was for each ADR to be included in a boxed warning.

RESULTS

There were substantial differences in all sections of the labels. The concordance rate between US and Japanese labels was 44.1% for serious adverse reactions and 30.5% for boxed warnings. Our regression analysis indicated that deaths and/or terminations related to specific ADRs reported in clinical trials were significantly associated with inclusion of the ADR in boxed warnings in Japan, but not in the US. The boxed warnings of similar drugs seemed to affect those of follow-on drugs in both countries. US drug labels were likely to influence Japanese labels, but not vice versa.

CONCLUSION

This study suggests that the observed differences are not solely due to differences in clinical outcomes between the two countries, but rather due to differences in regulatory considerations and historical factors in both local and global contexts. Further research is needed to examine the impact of these differences on public health and to determine how and to what extent we should intervene with this status quo. Copyright © 2016 John Wiley & Sons, Ltd.

Computational investigations of hERG channel blockers: New insights and current predictive models

Identification of potential human Ether-a-go-go Related-Gene (hERG) potassium channel blockers is an essential part of the drug development and drug safety process in pharmaceutical industries or academic drug discovery centers, as they may lead to drug-induced QT prolongation, arrhythmia and Torsade de Pointes. Recent reports also suggest starting to address such issues at the hit selection stage. In order to prioritize molecules during the early drug discovery phase and to reduce the risk of drug attrition due to cardiotoxicity during pre-clinical and clinical stages, computational approaches have been developed to predict the potential hERG blockage of new drug candidates. In this review, we will describe the current in silico methods developed and applied to predict and to understand the mechanism of actions of hERG blockers, including ligand-based and structure-based approaches. We then discuss ongoing research on other ion channels and hERG polymorphism susceptible to be involved in LQTS and how systemic approaches can help in the drug safety decision.