Pharmacovigilance studies without a priori hypothesis systematic review highlights inappropriate multiple testing correction procedures.

L Gaucher, P Sabatier, S Katsahian… - Journal of Clinical …, 2023 - Elsevier
Objective The purpose of this study was to systematically review the statistical methods used
in pharmacovigilance studies without a priori hypotheses. Study Design and Setting A …

A comprehensive review of computational techniques for the prediction of drug side effects

K Sachdev, MK Gupta - Drug Development Research, 2020 - Wiley Online Library
Drugs refer to the chemical compounds that are consumed by the human body and induce a
change by interacting with the protein targets. The drugs may induce favorable or …

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs

M Liu, Y Wu, Y Chen, J Sun, Z Zhao… - Journal of the …, 2012 - academic.oup.com
Objective Adverse drug reaction (ADR) is one of the major causes of failure in drug
development. Severe ADRs that go undetected until the post-marketing phase of a drug …

Shrinkage observed-to-expected ratios for robust and transparent large-scale pattern discovery

GN Norén, J Hopstadius, A Bate - Statistical methods in …, 2013 - journals.sagepub.com
Large observational data sets are a great asset to better understand the effects of medicines
in clinical practice and, ultimately, improve patient care. For an empirical pattern in …

Data mining techniques in pharmacovigilance: analysis of the publicly accessible FDA adverse event reporting system (AERS)

E Poluzzi, E Raschi, C Piccinni… - Data mining applications …, 2012 - books.google.com
Drug use in medicine is based on a balance between expected benefits (already
investigated before marketing authorization) and possible risks (ie, adverse effects), which …

Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports

R Cai, M Liu, Y Hu, BL Melton, ME Matheny… - Artificial intelligence in …, 2017 - Elsevier
Objective Drug-drug interaction (DDI) is of serious concern, causing over 30% of all adverse
drug reactions and resulting in significant morbidity and mortality. Early discovery of adverse …

Mining patients' narratives in social media for pharmacovigilance: adverse effects and misuse of methylphenidate

X Chen, C Faviez, S Schuck, A Lillo-Le-Louët… - Frontiers in …, 2018 - frontiersin.org
Background: The Food and Drug Administration (FDA) in the United States and the
European Medicines Agency (EMA) have recognized social media as a new data source to …

Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records

M Liu, ER McPeek Hinz, ME Matheny… - Journal of the …, 2013 - academic.oup.com
Objective Medication safety requires that each drug be monitored throughout its market life
as early detection of adverse drug reactions (ADRs) can lead to alerts that prevent patient …

A review of statistical methods for safety surveillance

L Huang, T Guo, JN Zalkikar… - … Innovation & Regulatory …, 2014 - journals.sagepub.com
The data-mining statistical methods used for disproportionality analysis of drug–adverse
event combinations from large drug safety databases such as the FDA's Adverse Event …

Improving drug safety: From adverse drug reaction knowledge discovery to clinical implementation

Y Tan, Y Hu, X Liu, Z Yin, X Chen, M Liu - Methods, 2016 - Elsevier
Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000
fatalities in the United States every year with an annual cost of $136 billion. Early detection …