What challenges did Novartis face before AI implementation?

Need for faster and cost-effective drug discovery and manufacturing. High prevalence of undetected health conditions in underserved areas. Need to analyze vast amounts of healthcare data for actionable insights. Obstacles in reaching underserved populations with quality care. Complexities of integrating AI ethically and efficiently into the workflows.

What was the impact of the AI solution?

Accelerated disease detection through AI-enabled tools. Improved global health outcomes by addressing underserved regions. Enhanced resource allocation and reduced healthcare costs. Proactive and predictive healthcare delivery improvements. Streamlined pharmaceutical R&D processes leading to innovative treatments.

Source

MicrosoftExpandedEvidence: Low35/100

Novartis and Microsoft revolutionize healthcare with AI-driven collaboration

Use case typeTherapeutics researchUpdated Jun 13, 2026

Novartis collaborates with Microsoft to leverage AI for enhancing drug discovery and improving healthcare delivery. This partnership includes deploying AI-enabled digital health tools to accelerate detection of diseases like leprosy by analyzing medical images. The joint efforts aim to transition healthcare systems from reactive to proactive approaches. AI applications are integrated across the pharmaceutical pipeline, covering early discovery, development, manufacturing, and patient care. By extracting insights from real-world data, advancing research, and ensuring ethical adoption of AI, this initiative marks a revolutionary turning point for healthcare delivery, especially in underserved regions.

Organization: Novartis
Industry: Healthcare
Location: Switzerland
Published: September 2019

Reported outcomes

Strategic outcomes

Ecosystem & partnershipsFormed an AI healthcare partnershipNew product / capabilityDeployed AI disease-detection toolsNew product / capabilityIntegrated AI across drug pipelineCustomer experience & trustImproved care for underserved regions

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Novartis
Provider: Microsoft
Maturity: Unknown
Linked source: novartis.com

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 2 of 2

1AI-driven disease detection
2Drug discovery and optimization

Need for faster and cost-effective drug discovery and manufacturing.
High prevalence of undetected health conditions in underserved areas.
Need to analyze vast amounts of healthcare data for actionable insights.
Obstacles in reaching underserved populations with quality care.
Complexities of integrating AI ethically and efficiently into the workflows.

Partnership with Microsoft to develop AI-enabled digital tools for healthcare.
Use of an AI-based tool to detect leprosy via medical image analysis.
Integration of AI to improve drug molecule discovery and enhance workflows.
Application of AI in analyzing data to predict risk factors and optimize healthcare processes.
Deployment of scalable platforms to ensure widespread benefits of AI applications.

Technologies

Azure AI Azure ML

Accelerated disease detection through AI-enabled tools.
Improved global health outcomes by addressing underserved regions.
Enhanced resource allocation and reduced healthcare costs.
Proactive and predictive healthcare delivery improvements.
Streamlined pharmaceutical R&D processes leading to innovative treatments.

Architecture

The leprosy detection system enables users to upload images of skin lesions to the Cloud for AI analysis, and returns actionable advice on healthcare specialist visits. Microsoft Azure is the Cloud platform supporting this AI inference workflow, integrating seamlessly with Novartis' pharmaceutical pipeline to monitor processes from drug discovery to patient care.

Sources & evidence1

Evidence: Low35/100Evidence strength