What challenges did Pharma Companies face before AI implementation?

Manual case intake processes are siloed and labor-intensive. High volume of incoming emails overwhelms specialists at initial triage. Susceptibility to human error and delayed detection of critical cases. Difficulties in scaling operations as data volumes grow. High costs and risk of compliance delays due to manual handling.

What was the impact of the AI solution?

Reduced manual effort for case intake processes. Improved speed and accuracy of adverse event reporting. Increased compliance with safety and regulatory standards. Scalable solution supports growing data volumes. Enhanced patient safety through real-time prioritization.

Source

MicrosoftLive source

Automated Adverse Event Email Triage Transforms Pharmacovigilance Operations

Use case typePatient engagementUpdated Jun 13, 2026

Pharma Co-vigilance by Tech Mahindra offers an automated system for processing pharmacovigilance case intake, particularly for adverse event reporting, utilizing Azure AI and large language model (LLM)-based agentic frameworks. Traditionally, pharma companies have relied on manual and labor-intensive processes for triaging large volumes of safety-related emails, risking human error and delays in regulatory compliance. The solution integrates directly with corporate email systems, leveraging generative AI and multiple AI agents to monitor, classify, prioritize, and verify incoming emails for valid pharmacovigilance cases. Case automation, real-time notifications, configurable prioritization rules, and compliance tracking allow organizations to reduce workload, improve case accuracy, and meet reporting deadlines more efficiently. Available as a consulting service through the Azure Marketplace, this showcases a direct, real-world application of Microsoft technology in pharmaceutical safety workflows.

Organization: Pharma Companies
Industry: Pharma
Location: India
Published: May 2025

Reported outcomes

Strategic outcomes

Scale & capacitySupported growing data volumesRisk & complianceIncreased compliance with safety standardsSpeed & agilityImproved speed and accuracy of reportingCustomer experience & trustEnhanced patient safety

Primary read

Use case focus

Showing 3 of 3

1Automated Pharmacovigilance Email Intake Agent
2Adverse Event Reporting Automation
3Safety Case Triage Using Multi-Agent AI

Manual case intake processes are siloed and labor-intensive.
High volume of incoming emails overwhelms specialists at initial triage.
Susceptibility to human error and delayed detection of critical cases.
Difficulties in scaling operations as data volumes grow.
High costs and risk of compliance delays due to manual handling.

Integrated generative AI/LLM-based agents for email monitoring and classification.
Automation of case intake, prioritization, and verification using agentic frameworks on Azure AI.
Configurable criteria and rules for valid case identification and severity-based triage.
Automated notifications and real-time case tracking.
Dashboards and metrics for compliance and performance monitoring.

Technologies

Azure AI Azure OpenAI Microsoft Azure

Reduced manual effort for case intake processes.
Improved speed and accuracy of adverse event reporting.
Increased compliance with safety and regulatory standards.
Scalable solution supports growing data volumes.
Enhanced patient safety through real-time prioritization.

Architecture

The application integrates with enterprise email systems, where emails are monitored and classified using LLM-based multi-agent frameworks on Azure AI. Automated workflows classify, validate, and prioritize cases, triggering real-time notifications and metrics dashboards, with optional human review.

Implementation partners1

Tech Mahindra

Sources & evidence1

Live sourceStill referenced

The case's original source is still reachable.