Pharma Co-vigilance : LLM-Based Multi AI Agentic AE Email Triage Service

Customer Challenge:

• Siloed manual case in-take process
• Dependency on the specialist on the initial stages due to large volume of e-mails
• Management issues (labour intensive and susceptible to human errors)
• Scalability issues due to manual screening and increasing data volume
• Higher cost and potential delays in safety case processing and reporting

Introducing Pharma Co-vigilance:

Tech Mahindra’s Pharma Co-vigilance brings the power of Azure AI services to provide unified and automated techniques, which enables pharma companies for critical cases in-takes to automatically prioritize valid cases based on the severity of reported events, using configurable criteria and rules.

An application that enhances existing pharma co-vigilance (PV) case intake processes by utilizing open-source generative AI models and AI frameworks. This application integrates with the company's email system to automate the monitoring, classification, prioritization, and verification of PV emails using LLM-based Multi AI agents.

Our Advisory & Consulting Services:

1. Customized GenAI Studio
2. Enterprise knowledge Search
3. Data augmentation for models
4. Responsible AI adoption
5. AE Case Classification Agent
6. Email- monitoring and classification
7. Prioritization, QC and validation

Possible Scenarios:

• Pharma case log automation
• Real time notification of the cases
• Valid case identification scenarios
• Prioritization of valid cases based on the severity of reported events, using configurable criteria and rules
• Verify the classification and prioritizations for human review
• In case of the requirement for Daily, weekly and monthly metrics to help customers track performance and compliance

Business Benefits:

• Collaborative environment for Pharma case identification, validation and monitoring
• Increased efficiency in the case in-take process
• Low-cost scale up on case prioritization and resolution
• Faster time to address cases