Program Overview
In the pharmaceutical industry, effective pharmacovigilance data management and analysis are crucial for ensuring the safety and efficacy of medical products. This one-day workshop provides comprehensive training on the principles and techniques of managing and analyzing pharmacovigilance data. Led by industry specialists with over 25 years of experience, participants will gain practical insights through case studies and interactive sessions, equipping them with the skills to navigate the complexities of pharmacovigilance data effectively.
Features
- Industry Expertise: Learn from specialists deeply entrenched in the pharmaceutical industry, providing real-world perspectives and practical insights
- Comprehensive Curriculum: Delve into the intricacies of pharmacovigilance data management and analysis through a comprehensive one-day workshop format.
- Case Studies: Explore real-life scenarios and case studies to understand the application of data management principles and analysis methods in different contexts.
- Interactive Learning: Engage in discussions, group activities, and hands-on exercises to reinforce learning and foster collaboration among participants.
- Cutting-edge Techniques: Stay updated with the latest trends and techniques in data management and analysis tailored specifically for pharmacovigilance professionals.
Target audiences
- professionals in the pharmaceutical industry involved in pharmacovigilance activities
- pharmacovigilance officers
- drug safety specialists
- regulatory affairs professionals
- clinical researchers
Curriculum
- 4 Sections
- 18 Lessons
- 1 Day
Expand all sectionsCollapse all sections
- Introduction to Pharmacovigilance Data3
- Data Quality Management and Governance5
- 2.1Principles of Data Quality Management
- 2.2Case study: Implementing data quality checks in adverse event reporting systems.
- 2.3Data Governance in Pharmacovigilance
- 2.4Case study: Developing a data governance framework for pharmacovigilance.
- 2.5Components of data governance: policies, standards, processes, roles and responsibilities.
- Data Analysis Methods in Pharmacovigilance8
- 3.1Introduction to data analysis methods used in pharmacovigilance.
- 3.2Case study: Analyzing safety data from clinical trials using descriptive statistics.
- 3.3Principles of signal detection in pharmacovigilance.
- 3.4Methods for signal detection
- 3.5Case study: Detecting and assessing safety signals in post-marketing surveillance data.
- 3.6Risk Assessment and Management
- 3.7Techniques for risk assessment
- 3.8Case study: Assessing the risk of adverse events associated with a new drug.
- Practical Applications and Case Studies2
Instructor
