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The EU-ADR Web Platform: delivering advanced pharmacovigilance tools

José Luis Oliveira, Pedro Lopes, Tiago Nunes, David Campos, Scott Boyer, Ernst Ahlberg, Erik M. van Mulligen, Jan A. Kors, Bharat Singh, Laura I. Furlong, Ferran Sanz, Anna Bauer-Mehren (+6 others)
2012 Pharmacoepidemiology and Drug Safety  
Keywords Pharmacovigilance, ADR, adverse drug reactions, drug safety, in silico pharmacology.  ...  Advanced tools are in 2 place to mine data from general practitioners research databases, establishing useful connections to other well-known resources. • Web services for the analysis of drug-event associations  ...  adverse drug reactions.  ... 
doi:10.1002/pds.3375 pmid:23208789 fatcat:4lktsd2pdbcsvjkeq227m77ynq

Predicting potential adverse events using safety data from marketed drugs

Chathuri Daluwatte, Peter Schotland, David G. Strauss, Keith K. Burkhart, Rebecca Racz
2020 BMC Bioinformatics  
Adverse event information available from FDA product labels and scientific literature for drugs that have the same activity at one or more of the same targets, structural and target similarities, and the  ...  This approach predicts 53 serious adverse events with high positive predictive values where well-characterized target-event relationships exist.  ...  Disclosures This article reflects the views of the authors and should not be construed to represent the FDA's views or policies.  ... 
doi:10.1186/s12859-020-3509-7 pmid:32349656 fatcat:lgjamm4v6vhx3fbmaqgw643xze

The benefits of data mining

Audrey Bone, Keith Houck
2017 eLife  
Careful analysis of a database populated by physicians and patients sheds new light on the side effects of drugs.  ...  mining and statistical analysis to extract new insights about adverse drug reactions from the database: the first step is to deal with the noise and other problems associated with such crowd-sourced databases  ...  Therefore, adverse drug reactions (ADRs) are often not identified until a drug is tested in a clinical trial, which can result in costly failures.  ... 
doi:10.7554/elife.30280 pmid:28813246 pmcid:PMC5577908 fatcat:33wkwqjfpfap3b2bcgnwkcqh5y

Artificial neural network: A data mining tool in pharmacovigilance

B. Mamatha, P. Venkateswara Rao
2020 Journal of Pharmacovigilance and Drug Research  
The key issue in India is that adverse drug reaction (ADR) has been underreported.  ...  The number of patients who are hospitalized is growing due to adverse drug effects and figuring out the exact cause of ADRs is a problem, if a patient is treated concurrently with several medicines.  ...  random coverage databases suggesting possible adverse drug reactions.  ... 
doi:10.53411/jpadr.2020.1.1.1 fatcat:mb5utsoei5ctjl6zwhpremhgz4

Artificial Neural Network: A Data Mining Tool in Pharmacovigilance

B. Mamatha, P. Venkateswara Rao
2020 Zenodo  
The key issue in India is that adverse drug reaction (ADR) has been under reported.  ...  The number of patients who are hospitalized is growing due to adverse drug effects and to figure out the exact cause of ADRs is a problem, if a patient is treated concurrently with several medicines.  ...  random coverage databases suggesting possible adverse drug reactions.  ... 
doi:10.5281/zenodo.4905481 fatcat:3nhebazavnc7zod2z7vjbswlf4

Drugs Highly Associated with Infusion Reactions Reported using Two Different Data-mining Methodologies

Philip W Moore Keith K Burkhart
2014 Journal of Blood Disorders & Transfusion  
Methods: The Food and Drug Administration Adverse Event Reporting System (FAERS) was data-mined for drugs highly associated with infusion reactions.  ...  However, neither system detected several drugs with established relationships to infusion reactions, including protamine and nitroglycerine.  ...  Acknowledgement The authors thank Helen Houpt MSLS AHIP (Pinnacle Health Library Services) for assistance with editing and manuscript preparation and Elizabeth Morgan MLS (Pinnacle Health Library Services  ... 
doi:10.4172/2155-9864.1000195 fatcat:pw2vprol7neybd5nbvza2dep74

The Use of Traditional Chinese Medicine in Relieving EGFR-TKI-Associated Diarrhea Based on Network Pharmacology and Data Mining

Shuaihang Hu, Wenchao Dan, Jinlei Liu, Peng Ha, Tong Zhou, Xinyuan Guo, Wei Hou, Akhilesh K. Tamrakar
2021 Evidence-Based Complementary and Alternative Medicine  
Prediction of drug targets by introducing the EGFR-TKI molecular structures into the SwissTargetPrediction platform and diarrhea-related targets in the DrugBank, GeneCards, DisGeNET, and OMIM databases  ...  data mining.  ...  Setting and Evidence-Based Research Scheme Design of Traditional Chinese Medicine for Malignant Tumor (K858).  ... 
doi:10.1155/2021/5530898 pmid:33868436 pmcid:PMC8032531 fatcat:vsyjrdgkabbfbh7lfaeguw63c4

Temporal Sequence Associations for Rare Events [chapter]

Jie Chen, Hongxing He, Graham Williams, Huidong Jin
2004 Lecture Notes in Computer Science  
In the experiments, we successfully identify a known drug and several new drug combinations with high risk of adverse reactions.  ...  In many real world applications, systematic analysis of rare events, such as credit card frauds and adverse drug reactions, is very important.  ...  Thus, systematic monitoring of adverse drug reactions is of financial and social importance.  ... 
doi:10.1007/978-3-540-24775-3_30 fatcat:kwbjwmxv35evfbhi5vphehtepq

Cardiotoxicity in Biological Agent-Targeted Therapy for Rheumatoid Arthritis: ADR Signal Mining and Analysis of Food and Drug Administration Adverse Event Reporting System Database

Xiaoyan Tang, Xiaolin Xu, Ji Li, Bin Zhao
2021 Frontiers in Pediatrics  
etanercept were used to mine data from the FDA's adverse event reporting system (FAERS) database from January 1, 2004 through September 30, 2020.  ...  The proportion of death and disability outcomes reported for each targeted treatment represents approximately 20–25% of the total reported severe adverse events.  ...  ACKNOWLEDGMENTS This study was assisted by many clinical pharmacists and physicians, as well as guided by many experts in the fields of pharmacy, clinical medicine, and statistics.  ... 
doi:10.3389/fped.2021.716648 pmid:34712629 pmcid:PMC8546333 fatcat:6utsyrxxh5bipdw4qx2pa4ak3e

Interest of pharmacoepidemiology for pharmacodynamics and analysis of the mechanism of action of drugs

Maryse Lapeyre-Mestre, François Montastruc
2019 The´rapie (Paris)  
) to various receptors and clinical incidence of their adverse drug reactions [10] .  ...  Data mining in these large databases has become a necessity in order to help pharmacovigilance systems to identify early signals for specific ADRs.  ... 
doi:10.1016/j.therap.2018.12.010 fatcat:2oxj5rqfu5fsjhami2ml45npaa

Prediction of adverse drug reactions based on knowledge graph embedding

Fei Zhang, Bo Sun, Xiaolin Diao, Wei Zhao, Ting Shu
2021 BMC Medical Informatics and Decision Making  
Background Adverse drug reactions (ADRs) are an important concern in the medication process and can pose a substantial economic burden for patients and hospitals.  ...  Conclusion In this paper, we introduce a new method to embed knowledge graph to vectorize drugs and ADRs, then use a logistic regression classification model to predict whether there is a causal relationship  ...  Acknowledgements We appreciate the support from the Information Center of the National Center for Cardiovascular Diseases and Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical  ... 
doi:10.1186/s12911-021-01402-3 pmid:33541342 fatcat:k5xmla2psvazbmxq7j6agsxo44

Artificial Neural Network: A Data Mining Tool in Pharmacovigilance

B. Mamatha, P. Venkateswara Rao
2020 Zenodo  
The key issue in India is that adverse drug reaction (ADR) has been under reported.  ...  The number of patients who are hospitalized is growing due to adverse drug effects and to figure out the exact cause of ADRs is a problem, if a patient is treated concurrently with several medicines.  ...  random coverage databases suggesting possible adverse drug reactions.  ... 
doi:10.5281/zenodo.4016660 fatcat:kd3om5basfd4zcg2xe7zhwgi3m

Association between Benzodiazepine Use and Dementia: Data Mining of Different Medical Databases

Mitsutaka Takada, Mai Fujimoto, Kouichi Hosomi
2016 International Journal of Medical Sciences  
To examine the association between benzodiazepine anxiolytic drug use and the risk of dementia, we conducted data mining of a spontaneous reporting database and a large organized database of prescriptions  ...  Methods: Data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) from the first quarter of 2004 through the end of 2013 and data from the Canada Vigilance Adverse Reaction  ...  Acknowledgements We thank the Japan Medical Information Research Institute, Inc. for providing the database of prescriptions.  ... 
doi:10.7150/ijms.16185 pmid:27877074 pmcid:PMC5118753 fatcat:i5kgrrv46zek5lqbpgrq6knyxa

Automatic Filtering and Substantiation of Drug Safety Signals

Anna Bauer-Mehren, Erik M. van Mullingen, Paul Avillach, María del Carmen Carrascosa, Ricard Garcia-Serna, Janet Piñero, Bharat Singh, Pedro Lopes, José L. Oliveira, Gayo Diallo, Ernst Ahlberg Helgee, Scott Boyer (+5 others)
2012 PLoS Computational Biology  
Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological  ...  The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions.  ...  Acknowledgments The authors wish to thank the NLMH for making UMLSH and MesHH available free of charge. Author Contributions  ... 
doi:10.1371/journal.pcbi.1002457 pmid:22496632 pmcid:PMC3320573 fatcat:brbigakv5fd4hfsvekgdtmopj4

Suspected Adverse Drug Reactions Related to Breast Cancer Chemotherapy: Disproportionality Analysis of the Brazilian Spontaneous Reporting System

Flávia Campos Barcelos, Guacira Corrêa de Matos, Mario Jorge Sobreira da Silva, Fabrício Alves Barbosa da Silva, Elisangela da Costa Lima
2019 Frontiers in Pharmacology  
interval of 95% in order to identify possible signals of disproportionate reporting, only among serious suspected adverse drug reactions.  ...  This cross-sectional study (2008 to 2013) aimed to analyse the feasibility of detecting such signals in the Brazilian Pharmacovigilance Database comprising suspected adverse drug reactions related to the  ...  interval of 95% in order to identify possible signals of disproportionate reporting, only among serious suspected adverse drug reactions.  ... 
doi:10.3389/fphar.2019.00498 pmid:31139083 pmcid:PMC6519311 fatcat:plrqntnqtfdzro6wksx5hegzby
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