Introduction
iADRs (Interactive Adverse Drug Reactions System) is a web-based interactive system for ADR detection and analysis. This system embraces a novel data cube technique, namely contingency cube, to provide an OLAP-like on-line detection, i.e., inspecting from many different aspects and demographic conditions, such as gender, age, etc., of adverse drug reactions or drug-interactions from the US FDA Adverse Event Reporting System dataset (FAERS). Other features include:
1. Normalization of all drug names, conforming to generic names adopted by RxNorm, automatic drug name transformation, and de-duplication of duplicate copies of reporting records, such as follow-up reports;
2. Supporting various well-known ADR signal measures, including PRR, ROR, IC, χ2(Chi-square test), etc., with default or customized threshold specifications;
3. Providing the detection of both single-drug-induced signals and multiple-drug-induced signals;
4. Linking discovered ADR signals with PubMed for related literature and information.
Version Information
Update - 2021/03/02
The current version of iADRs is 2.1, released on March 8, 2021. Three new signal measures are added to the current release, including BCPNN, SPRT, and Yule's Q.
● Added signal measures BCPNN, SPRT, and Yule's Q.
● Updated drug name normalization api, RxNorm, to latest version.
Update - 2016/03/25
The current version of iADRs is 2.0, released on March 25, 2016. This version embraces some new features compared to the old version. First, the drug names have been normalized to generic names adopted by RxNorm. Second, four new signal measures are added to the current release, including PRR95, ROR95, Chi-square, and Leverage. Moreover, iADRs now can support multi-drug-induced signals detection, and in the outputted result, users can obtain more information about discovered ADR signals by using the chart function and linking to related literatures extracted from PubMed.
● Normalized drug names to generic names.
● Added signal measures PRR95, ROR95, Chi-square, and Leverage.
● Supported multi-drug-induced signals detection.
● Extended chart function.
● Added PubMed hyperlink in outputted result.
About US
This system is developed by members of CILab (Computational Intelligence Lab) at National University of Kaohsiung. It started as a prototype in 2009, a companion result of the thesis of He-Yi Lee, later undergone a major update by Wen-Yu Feng and Chiao-Feng Lo. The first version was launched in 2012. Several members then contributed to the extension of this system, including Jhih-Wei Du, Duen-Chun Yang, Hsin-Ping Chen, Chiao-Yun Hsiao, Feng-Hsiung Huang, Ji-Kai Ho, Min-Hsien Wang, and Jie-Teng Wang.
