RxLogix PV Case Management Webinar
Your Most Comprehensive Digital PV Case Management Solution. AI, Data Sciences, Intelligent Automation & Cloud
Webinar RxLogix’ PV Case Management – Future-Proof Your PV Case Management
Date: April 9, 2025
Time:
07:30-08:30 PDT
10:30-11:30 EST
15:30-16:30 GMT
16:30-17:30 CET
Join us for an exclusive webinar on RxLogix’ PV Case Management, the industry’s most advanced solution designed to streamline compliance, improve efficiency, and seamlessly adapt to evolving pharmacovigilance regulations.
Key Takeaways:
✔ How AI, automation, and cloud technology enhance PV case management
✔ Ways to eliminate manual processes and ensure real-time compliance
✔ Best practices from leading pharma and biotech companies
Speakers
Awais Khan
Associate Vice President, Products RxLogix Corporation
Awais is responsible for PV Publisher. He has more than 15+years of experience in the life-sciences industry, working with several top pharmaceutical companies. His expertise includes in-depth knowledge of PV regulations, strategy and roadmap development, reporting and signaling process/solution design, system implementation and program management. He holds a Bachelor’s Degree in Electrical Engineering from Clemson University, South Carolina.
Richard Wolf
Vice President, Client Relations RxLogix
Richard brings over 20 years of PV Operations experience, having led global organizations and implemented safety systems at major pharmaceutical companies. His career began at Accenture, followed by 12 years at Johnson & Johnson optimizing processes and technologies. He spent the last 10 years at CSL Behring, where he developed the Global PV Operations group, implemented managed services, and optimized interfaces with Clinical, Quality, and Medical Information functions.
We will explore how the system:
- Automatically extract and classify case information (e.g., reporter info, patient details, suspect drug, event).
- Identifies potential duplicate cases using fuzzy matching and pattern recognition.
- AI flags seriousness criteria (e.g., hospitalization, death) and compares events against known product labels.
- Use Case: Auto-codes adverse events and drug names using MedDRA and WHO Drug Dictionary.
- Converts structured and unstructured data into readable medical narratives.
- Assigns tasks to the right user based on workload, geography, language skills, etc.
- AI predicts whether a case needs to be submitted to a specific HA and within what timeframe.
- Early pattern recognition from incoming cases to suggest potential new signals.
- Captures and transcribes patient/HCP calls; auto-triggers case creation.
We look forward to your participation!
