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Subscribe NewsletterSignal Detection and Data Mining in Pharmacovigilance
Product Id
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600241
Overview: This webinar will cover the fundamentals of signal detection, and how these can be augmented by the use of data mining techniques.
In March 2005, the FDA published final guidance on "Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment." This guidance defines the FDA's views on pharmacovigilance concepts, safety signal identification, pharmacoepidemiologic assessment and interpretation of safety signals. This webinar will demonstrate how to meet FDA's requirements for detection of potential signals or trends.
Why should you attend: The requirement for companies to perform signal detection is now mandatory in Europe and highly recommended in the US.
The FDA Amendment Act mandates that companies develop Risk Evaluation and Mitigatiuon Strategies for their products, where required. In order to assess a product's risk-benefit profile it is essential that companies perform signaling analyses based on all available safety data for their products.
Areas Covered in the Session:
In March 2005, the FDA published final guidance on "Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment." This guidance defines the FDA's views on pharmacovigilance concepts, safety signal identification, pharmacoepidemiologic assessment and interpretation of safety signals. This webinar will demonstrate how to meet FDA's requirements for detection of potential signals or trends.
Why should you attend: The requirement for companies to perform signal detection is now mandatory in Europe and highly recommended in the US.
The FDA Amendment Act mandates that companies develop Risk Evaluation and Mitigatiuon Strategies for their products, where required. In order to assess a product's risk-benefit profile it is essential that companies perform signaling analyses based on all available safety data for their products.
Areas Covered in the Session:
- Analysis of demographics, risk assessment, dose effects, product-product interactions, and differences from known background rates
- Strategies for incorporating all relevant data sources, including clinical trials, individual case reports, PSURs, external databases (FDA, WHO), and registries
- Understanding the risk-benefit ratio of a product and how to discover product-adverse event relationships
- Measuring the strength of the relationship of the adverse event and the drug using the Bayesian Confidence Propagation Neural Network algorithm (BCPNN)
- Drug safety and pharmacovigilance
- Regulatory Affairs
- Clinical development