A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Abstract

Pharmacovigilance is the scientific discipline that copes with the continuous assessment of the safety profile of marketed drugs. This assessment relies on diverse data sources, which are routinely analysed to identify the so-called "signals", i.e. potential associations between drugs and adverse effects, that are unknown or incompletely documented. Various computational methods have been proposed to support domain experts in signal detection. However, recent comparative studies illustrated that current methods exhibit high false-positive rates, significantly variable performance across different datasets used for analysis and events of interest, but also complementarity in their outcomes. In this regard, in order to reinforce accurate and timely signal detection, we elaborated through an agent-based approach towards systematic, joint exploitation of multiple heterogeneous signal detection methods, data sources and other drug-related resources under a common, integrated framework. The approach relies on a multiagent system operating based on a collaborative agent interaction protocol, aiming to implement a comprehensive workflow that comprises of method selection and execution, as well as outcomes' aggregation, filtering, ranking and annotation. This paper presents the design of the proposed multiagent system, discusses implementation issues and demonstrates the applicability of the proposed solution in an example signal detection scenario. This work constitutes a step towards large-scale, integrated and knowledge-intensive computational signal detection.

Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches

“…Signal detection (Sarntivijai et al, 2012; Tao et al, 2012; Cheng et al, 2013; Boyce et al, 2014; Cheng and Zhao, 2014; Courtot et al, 2014; Iyer et al, 2014; Wang et al, 2014; Cai et al, 2015, 2017; Dupuch and Grabar, 2015; Liu and Chen, 2015; Koutkias and Jaulent, 2016; Liu et al, 2016, 2018; Knowledge Base Workgroup of the Observational Health Data Sciences and Informatics (OHDSI) Collaborative, 2017; Voss et al, 2017)…”

“…Signal detection (Huang et al, 2011; Gurulingappa et al, 2012; Cheng et al, 2013; Cheng and Zhao, 2014; Iyer et al, 2014; Shang et al, 2014; Cai et al, 2015; Herrero-Zazo et al, 2015; Jiang et al, 2015; Koutkias and Jaulent, 2015, 2016; Bravo et al, 2016; Eshleman and Singh, 2016; Kawazoe et al, 2016; Lowe et al, 2016; Noor et al, 2016; Abdelaziz et al, 2017; Knowledge Base Workgroup of the Observational Health Data Sciences and Informatics (OHDSI) Collaborative, 2017; Nguyen et al, 2017)…”

“…Signal detection (Tari et al, 2010; Gurulingappa et al, 2012; Boyce et al, 2014; Shang et al, 2014; Zhang et al, 2014, 2016; Bravo et al, 2016; Koutkias and Jaulent, 2016; Lowe et al, 2016; Noor et al, 2016; Knowledge Base Workgroup of the Observational Health Data Sciences and Informatics (OHDSI) Collaborative, 2017; Voss et al, 2017)…”

Exploiting heterogeneous publicly available data sources for drug safety surveillance: computational framework and case studies

“…The first, fully relevant citation was a database study, which was made available in PubMed on December, 1999, following 1 prior case report published in June, 1996 (categorised as partially relevant, since its full text was not accessible). From the set of fully relevant citations, 38% (9/24) were case reports, 29% (7/24) were review papers, 16.5% (4/24) were database studies, 2 were clinical studies, 1 was a fundamental study, and 1 was an animal study.…”

“…The Version of Record of this manuscript has been published and is available in Expert Opinion on Drug Safety, Dec. 1, 2016, http://www.tandfonline.com/10.1080/14740338.2017.1257604. 4 and analysis mechanisms to acquire and comprehensively exploit data from these sources in everyday pharmacovigilance practice [16]. Interestingly, an increasing number of such sources are made publicly accessible through well-defined data communication interfaces facilitating programmatic access.…”