Plug and Play FAERS quarterly data files
Rapidly upload, process, clean, and filter the standard data files from the FAERS public database with a Dataiku Application.
Explore !The goal of this ready-to-use solution is to accelerate the discovery of potential Adverse Drug Reaction (ADR) signals. It enables users to upload quarterly data from spontaneous reporting systems and uses statistical metrics to generate disproportional frequencies of drugs and even pairs across various populations. More details on the specifics of the solution can be found on the knowledge base. This solution is only available on installed instances.
Business Overview
The efficiency of post-market drug safety surveillance functions plays a critical role in reinforcing patient safety and securing successful drug launches. Compliance in safety reporting and surveillance is a must-meet regulatory requirement (Good Pharmacovigilance Practice) and failure to appropriately report, detect, and address adverse drug reactions can lead to patient harm, drug recall, and significant costs.
The focus on pharmacovigilance efficiency is further reinforced as Adverse Drug Reactions (ADR) are increasingly found to be a leading cause of both mortality and morbidity, particularly in older populations. Research has shown ADRs are responsible for anywhere from 5% to 30% of all hospitalizations with a potential global economic burden of over $1 trillion USD. Given the rigid criteria of clinical research, pharmacovigilance practices often enable the first comprehensive assessment of the benefit-risk profile of marketed drugs in diverse, and potentially under-represented, real-world patient populations.
As the volume/velocity/variety of safety reporting data grows, it is becoming essential for global safety teams at drug manufacturers, health outcomes research institutions, and regulatory bodies alike to adopt new analytics-driven approaches, that can be automated at scale, to improve early signal detection and reliability in the pharmacovigilance process.
Highlights
- Quickly ingest data files extracted from the FDA Adverse Event Reporting System (FAERS) database
- Easily process the data, detect duplicate reports, and filter on demographic, drug, reaction, and report characteristics
- Identify and visualize patterns in safety data with Dataiku’s descriptive analytics and charts
- Calculate common disproportionality metrics for statistical inference and signal detection
- Achieve immediate insights with a user-friendly Dataiku App to filter reports, generate signals for cohorts, and create drug/reaction analytics to ensure patient safety and increase regulatory compliance with early detection of potential ADR signals
Reproducible, automated flow for data cleaning and drug/reaction signal analysis
Automate and visualize the complex data preparation process to take raw report data on drugs, indications, reactions, outcomes, and demographics to analysis-ready signal surveillance.
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Generate measures of disproportionality (ROR, PRR, EBGM)
Understand and triage the potential drug safety signals found in spontaneously reported systems with common disproportionality metrics and descriptive analytics
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Interactive visual dashboards of safety trends
Gain the complete picture of the complex patterns and potential safety concerns particular to your therapeutic through interactive visualization to monitor and triage potential safety signals related to your brands.
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Insights on drivers of potential drug safety signals and outcomes in reports across cohorts
Discover disparate trends in adverse drug reactions across age groups and gender cohorts.
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From signals to investigation
Easily integrate large amounts of data from spontaneous reporting systems, and just as easily push the resulting datasets into case management systems for investigation.
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