Automated Clinical Trial Adverse Event Monitoring System

Create a Python-based automated monitoring system that scrapes multiple clinical trial databases and research repositories to track and categorize potential adverse events in real-time. Utilize libraries like BeautifulSoup and Scrapy for web scraping, implement machine learning classification for event severity, and develop an alert mechanism that immediately notifies research coordinators of high-risk event patterns. The system should generate comprehensive weekly reports and integrate with existing clinical research management platforms.