MetaADEDB 2.0: a comprehensive database on adverse drug events

2020 ◽  
Author(s):  
Zhuohang Yu ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Safety Assessment ◽  
Adverse Drug Events ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Supplementary Information ◽  
Online Database ◽  
Web Interface ◽  
Drug Discovery And Development ◽  
Comprehensive Information ◽  
User Friendly

Abstract Summary MetaADEDB is an online database we developed to integrate comprehensive information on adverse drug events (ADEs). The first version of MetaADEDB was released in 2013 and has been widely used by researchers. However, it has not been updated for more than seven years. Here, we reported its second version by collecting more and newer data from the U.S. FDA Adverse Event Reporting System (FAERS) and Canada Vigilance Adverse Reaction Online Database, in addition to the original three sources. The new version consists of 744 709 drug–ADE associations between 8498 drugs and 13 193 ADEs, which has an over 40% increase in drug–ADE associations compared to the previous version. Meanwhile, we developed a new and user-friendly web interface for data search and analysis. We hope that MetaADEDB 2.0 could provide a useful tool for drug safety assessment and related studies in drug discovery and development. Availability and implementation The database is freely available at: http://lmmd.ecust.edu.cn/metaadedb/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Immune checkpoint inhibitors-related myocarditis in patients with cancer: an analysis of international spontaneous reporting systems

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rulan Ma ◽  
Quanziang Wang ◽  
Deyu Meng ◽  
Kang Li ◽  
Yong Zhang
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Adverse Drug Events ◽  
Cytotoxic T Lymphocyte ◽  
Checkpoint Inhibitors ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Real World Data ◽  
Safety Issues

Abstract Background Immune checkpoint inhibitors-induced myocarditis presents unique clinical challenges. Here, we assessed post-marketing safety of cytotoxic T-lymphocyte-associated protein-4 (CTLA-4), programmed cell death-1 (PD-1), and programmed death-ligand 1 (PD-L1) inhibitors by mining the real-world data reported in two international pharmacovigilance databases. Methods We analyzed immune checkpoint inhibitors (ICIs)-associated fatal adverse drug events (ADEs) reports from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) collected from July 1, 2014 to December 31, 2019 and data from EudraVigilance (EV) database accessed on February 29, 2020. Three different data mining approaches were used to detect the signal of fatal myocarditis caused by ICIs. Results Based on 7613 ICIs-related ADEs reported to the EV database and 5786 ICIs-associated ADEs submitted to the FAERS database, the most frequently reported ADE was ipilimumab-related colitis. For myocarditis, nivolumab-associated myocarditis was the most common. Among the five fatal toxic effects associated with ICIs, the lethality rate of myocarditis was the highest. Therefore, we further analyzed ICI-associated myocarditis and found that elderly patients and male patients were more likely to develop ICIs-related myocarditis. The results of signal detection showed that the risk signal of avelumab-related myocarditis detected by reporting odds ratio (ROR) method and proportional reporting ratios (PRR) method was the highest, whereas the signal strength of ipilimumab-related myocarditis detected by Bayesian confidence propagation neural networks (BCPNN) method was the strongest. Conclusion The findings of this study indicated the potential safety issues of developing myocarditis when using ICIs, which were consistent with the results of previous clinical trials and could provide a reference for clinical workers when using ICIs.

scholarly journals From big data to bedside decision-making: the case for AdverseEvents

2013 ◽  
Vol 3 (1) ◽  
pp. 3
Author(s):  
Giuseppe Biondi Zoccai ◽  
Elena Cavarretta ◽  
Giacomo Frati
Keyword(s):  
Decision Making ◽  
Clinical Evidence ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Ease Of Use ◽  
Antithrombotic Agent ◽  
Post Marketing ◽  
The Individual ◽  
User Friendly ◽  
Based Medicine

<p>Evidence-based medicine has gained mainstream popularity, but it requires a delicate balance between clinical evidence, physician skills, patient preferences, and costs. Facing the individual patient, even a simple decision such as which antithrombotic agent should be prescribed becomes complex. There are several reasons for this conundrum, but one of the foremost is the limited external validity of pivotal randomized trials, with their extremely restrictive selection criteria. Post-marketing reporting of adverse events is a very useful and democratic means to appraise the risk-benefit profile, but to date such reports were not organized or available. The development of the Food and Drug Administration (FDA) venue for such task, the FDA Adverse Event Reporting System (FAERS) has substantially improved data collection. However, analysis of this extensive relational database remains complex for most but few companies or agencies. AdverseEvents is a novel online platform enabling updated and user-friendly inquiry of FAERS. Given its ease of use, flexibility and comprehensiveness, it is likely going to improve decision making for healthcare authorities and practitioners, as well as patients. This is clearly testified by the precise and informative comparative analysis that can be performed with AdverseEvents on novel antithrombotic agents.</p>

scholarly journals Immune checkpoint inhibitors-related myocarditis in patients with cancer: an analysis of international spontaneous reporting systems

2020 ◽  
Author(s):  
Rulan Ma ◽  
Quanziang Wang ◽  
Deyu Meng ◽  
Kang Li ◽  
yong zhang
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Adverse Drug Events ◽  
Cytotoxic T Lymphocyte ◽  
Checkpoint Inhibitors ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Real World Data ◽  
Safety Issues

Abstract Background: Immune checkpoint inhibitors induced myocarditis presents unique clinical challenges. Here, we assessed post-marketing safety of cytotoxic T-lymphocyte-associated protein-4 (CTLA-4), programmed cell death-1 (PD-1), and programmed death-ligand 1 (PD-L1) inhibitors by mining the real-world data reported in two international pharmacovigilance databases. Methods: We analyzed immune checkpoint inhibitors (ICIs)-associated fatal adverse drug events (ADRs) reports from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) collected from July 1, 2014 to December 31, 2019 and data from EudraVigilance (EV) database accessed on February 29, 2020. Three different data mining approaches were used to detect the signal of fatal myocarditis caused by ICIs. Results: Based on 7613 ICIs-related ADEs reported to the EV database and 5786 ICIs-associated ADEs submitted to the FAERS database, the most frequently reported ADE was ipilimumab-related colitis. For myocarditis, nivolumab-associated myocarditis was the most common. Among the five fatal toxic effects associated with ICIs, the lethality rate of myocarditis was the highest. Therefore, we further analyzed ICI-associated myocarditis and found that elderly patients and male patients were more likely to develop ICIs-related myocarditis. The results of signal detection showed that the risk signal of avelumab-related myocarditis detected by reporting odds ratio (ROR) method and proportional reporting ratios (PRR) method was the highest, whereas the signal strength of ipilimumab-related myocarditis detected by Bayesian confidence propagation neural networks (BCNPP) method was the strongest. Conclusion: The findings of this study indicated the potential safety issues of developing myocarditis when using ICIs, which are consistent with the results of previous clinical trials and can provide a reference for clinical workers when using ICIs.

scholarly journals Evaluation of a Potential Clinical Interaction between Ceftriaxone and Calcium

2010 ◽  
Vol 54 (4) ◽  
pp. 1534-1540 ◽  
Author(s):  
Emily Steadman ◽  
Dennis W. Raisch ◽  
Charles L. Bennett ◽  
John S. Esterly ◽  
Tischa Becker ◽  
...  
Keyword(s):  
Adverse Drug Events ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Organ Damage ◽  
Adverse Event Reporting ◽  
Current Analysis ◽  
Event Reporting ◽  
Drug Involvement ◽  
Intravenous Calcium ◽  
Precipitation Events

ABSTRACT In April 2009, the FDA retracted a warning asserting that ceftriaxone and intravenous calcium products should not be coadministered to any patient to prevent precipitation events leading to end-organ damage. Following that announcement, we sought to evaluate if the retraction was justified. A search of the FDA Adverse Event Reporting System was conducted to identify any ceftriaxone-calcium interactions that resulted in serious adverse drug events. Ceftazidime-calcium was used as a comparator agent. One hundred four events with ceftriaxone-calcium and 99 events with ceftazidime-calcium were identified. Adverse drug events were recorded according to the listed description of drug involvement (primary or secondary suspect) and were interpreted as probable, possible, unlikely, or unrelated. For ceftriaxone-calcium-related adverse events, 7.7% and 20.2% of the events were classified as probable and possible for embolism, respectively. Ceftazidime-calcium resulted in fewer probable embolic events (4%) but more possible embolic events (30.3%). Among cases that considered ceftriaxone or ceftazidime and calcium as the primary or secondary drug, one case was classified as a probable embolic event. That patient received ceftriaxone-calcium and died, although an attribution of causality was not possible. Our analysis suggests a lack of support for the occurrence of ceftriaxone-calcium precipitation events in adults. The results of the current analysis reinforce the revised FDA recommendations suggesting that patients >28 days old may receive ceftriaxone and calcium sequentially and provide a transparent and reproducible methodology for such evaluations.

scholarly journals MOSGA: Modular Open-Source Genome Annotator

2020 ◽  
Author(s):  
Roman Martin ◽  
Thomas Hackl ◽  
Georges Hattab ◽  
Matthias G Fischer ◽  
Dominik Heider
Keyword(s):  
Open Source ◽  
Source Code ◽  
Supplementary Information ◽  
Web Interface ◽  
Fully Integrated ◽  
Sequencing Technologies ◽  
A Genome ◽  
Wide Range ◽  
User Friendly ◽  
Eukaryotic Genomes

Abstract Motivation The generation of high-quality assemblies, even for large eukaryotic genomes, has become a routine task for many biologists thanks to recent advances in sequencing technologies. However, the annotation of these assemblies—a crucial step toward unlocking the biology of the organism of interest—has remained a complex challenge that often requires advanced bioinformatics expertise. Results Here, we present MOSGA (Modular Open-Source Genome Annotator), a genome annotation framework for eukaryotic genomes with a user-friendly web-interface that generates and integrates annotations from various tools. The aggregated results can be analyzed with a fully integrated genome browser and are provided in a format ready for submission to NCBI. MOSGA is built on a portable, customizable and easily extendible Snakemake backend, and thus, can be tailored to a wide range of users and projects. Availability and implementation We provide MOSGA as a web service at https://mosga.mathematik.uni-marburg.de and as a docker container at registry.gitlab.com/mosga/mosga: latest. Source code can be found at https://gitlab.com/mosga/mosga Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Adverse Drug Events in the Prevention and Treatment of COVID-19: A Data Mining Study on FDA Adverse Event Reporting System (FAERS) (Preprint)

2021 ◽  
Author(s):  
Qiang Guo ◽  
Shaojun Duan ◽  
Yaxi Liu ◽  
Yinxia Yuan
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Adverse Drug Events ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Drug Event ◽  
Event Reporting ◽  
Prevention And Treatment

BACKGROUND In the emergency situation of COVID-19, off-label therapies and newly developed vaccines may bring the patients adverse drug event (ADE) risks. Data mining based on spontaneous reporting systems (SRSs) is a promising and efficient way to detect potential ADEs so as to help health professionals and patients get rid of these risks. OBJECTIVE This pharmacovigilance study aimed to investigate the ADEs of “Hot Drugs” in COVID-19 prevention and treatment based on the data of the US Food and Drug Administration (FDA) adverse event reporting system (FAERS). METHODS FAERS ADE reports associated with COVID-19 from the 2nd quarter of 2020 to the 2nd quarter of 2021 were retrieved with “Hot Drugs” and frequent ADEs recognized. A combination of support, proportional reporting ratio (PRR) and Chi-square (2) test was applied to detect significant “Hot Drug” & ADE signals by Python programming language on Jupyter notebook. RESULTS 13,178 COVID-19 cases were retrieved with 18 “Hot Drugs” and 312 frequent ADEs on “Preferred Term” (PT) level. 18  312 = 5,616 “Drug & ADE” candidates were formed for further data mining. The algorithm finally produced 219 significant ADE signals associated with 17 “Hot Drugs”and 124 ADEs.Some unexpected ADE signals were observed for chloroquine, ritonavir, tocilizumab, Oxford/AstraZeneca COVID-19 Vaccine and Moderna COVID-19 Vaccine. CONCLUSIONS Data mining is a promising and efficient way to assist pharmacovigilance work and the result of this paper could help timely recognize ADEs in the prevention and treatment of COVID-19.

scholarly journals SAFETY SIGNAL DETECTION OF CARDIAC DISORDERS ADVERSE DRUG EVENTS FOR AZITHROMYCIN IN PEDIATRIC POPULATION USING HEALTH CANADA ADVERSE EVENT REPORTING SYSTEM DATABASE

2017 ◽  
Vol 9 (6) ◽  
pp. 80
Author(s):  
Gaurav Kumar Shah ◽  
Mukesh Kumar Patel ◽  
Dr. Bhanwarlal Jat
Keyword(s):  
Adverse Event ◽  
Adverse Drug Events ◽  
Reporting System ◽  
Pediatric Population ◽  
Adverse Event Reporting System ◽  
Cardiovascular Disorder ◽  
Paediatric Population ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
System Database

Objective: We conducted signal detection of adverse drug events reported in Health Canada adverse event reporting system database “MedEffect” for azithromycin, a macrolide derivative and the first azalide antimicrobial agent to review the cardiac disorders adverse drug events (ADEs) in pediatric population with the drug labels of selected countries including India, USA, UK, Canada, Switzerland, Australia, New Zealand.Methods: We extracted data between January 1965 and June 2016 from the Canada adverse event reporting system database “MedEffect”. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-adverse event (AE) pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was identified as a potential signal. AE reports for azithromycin, among which 3651 reports were attributed to paediatrics.Results: The signal detected by PRR and ROR for tachycardia associated with azithromycin were found to be 1.3 and for cardiovascular disorder were 1.2. The IC for azithromycin by a Bayesian method was 0.3 for both, tachycardia and cardiovascular disorder. Both AEs of cardiovascular disorder and tachycardia were detected as potential signals of azithromycin for the paediatric population. Comparing drug labels of 7 countries in paediatric population, both adverse events were not listed on any of the labels of seven countries against the pediatric population.Conclusion: We detected 2 new potential signals of azithromycin which were not listed on the labels of 7 countries. Therefore, it should be accompanied by a signal evaluation including causal association, clinical significance, and preventability.

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