Full Description
This book provides detailed concepts and information on principles and processes of signal analysis in pharmacovigilance along with case studies. It covers the fundamental concepts and principles of pharmacovigilance, emphasizing the need for robust signal detection and analysis methods. The book reviews the diverse array of databases and tools employed for signal detection, including electronic health records (EHRs), social media mining, claims data, and distributed data networks. In turn, the book discusses the application of molecular dynamics, molecular docking, and the use of the FDA Adverse Event Reporting System (FAERS) database in signal analysis.
Toward the end, the book explores the identification, validation, and assessment of signals associated with vaccines. This book is useful for graduate, post-graduate students of pharmaceutical sciences, and scientists in pharmacology research and drug development.
Contents
Chapter 1: Introduction to Pharmacovigilance: Ensuring Medication Safety. Chapter 2: Drug Safety Signal Detection and management in Pharmacovigilance.Chapter 3: Databases and Tools for Signal Detection of Drugs in Post-Marketing Surveillance.Chapter 4: Role of Electronic medical records, Social Media, Claims data, distributed data networks in signal analysis.Chapter 5: Uncovering False Alarms: Examining Biases and Confounders in Disproportionality Analysis.Chapter 6: Role of Medical Coding in Signal Detection. Chapter 7: Regulatory Aspects in Signal Detection and Assessment. Chapter 8: Disproportionality Methods for Signal Detection in Pharmacovigilance. Chapter 9: Bayesian methods of signal detection. Chapter 10: Subgroup and sensitivity analysis. Chapter 11: Causality Assessment of ICSRs. Chapter 12: Signal Analysis of Drug-Drug Interaction Using Spontaneous Reporting Method. Chapter 13: Use of network pharmacological approaches in signal analysis. Chapter 14: Docking studies in signal analysis: An overview. Chapter 15: Molecular Dynamics simulations in signal validation. Chapter 16: Identification and validation of novel signal of drugs using FAERS database: A case study. Chapter 17: Molecular docking and molecular dynamics in Signal analysis: A case study. Chapter 18: Available Databases and Tools for signal detection of vaccines. Chapter 19: Identification and validation of signals associated with vaccines.Chapter 20: Neurological and behaviour alterations with COVID-19 vaccines using Vaccine Adverse Event Reporting System (VAERS): A Retrospective study. Chapter 21: Pharmacovigilance based drug repurposing via inverse signals.Chapter 22: Prospective role of preclinical experimentation in validating the safety signals.Chapter 23: Role of Artificial Intelligence in Signal Detection. 24. Index.
