AstraZeneca

AstraZeneca has 5 source-linked AI deployments documented in AIUseCaseHub, across 1 industry and 3 countries. Key partners include BenevolentAI, Exscientia, Insilico Medicine.

5
Use Cases
1
Industries
3
Countries
2
Agent Cases
2
RAG Cases

Hyperscaler mix

See whether AstraZeneca's cases are powered by Microsoft, AWS, GCP, or multiple providers.

How AstraZeneca builds AI

Build / Buy / Compose across this company's documented cases

BuildBuyComposeMixed

5 of 5 cases classified (100%) · Compare all use-case types

Reported outcomes

1 case reports measurable results

−75%

Time & speed

median · 2 metrics

Medians of results published in AstraZeneca cases, normalized for comparability. See all benchmarks →

Evidence persistence

3 of 3 judgeable cases are still publicly referenced · 3 show the organization expanding AI use.

Durability of public evidence, not whether systems remain in production. How this is measured →

Technology snapshot

What AstraZeneca uses across visible cases

Capability flags and technologies mentioned in the indexed use cases on this page.

Top use case
Agent
Tagged cases
4/5
Tech names
13

All Use Cases (5)

AstraZeneca on AWS: Amazon Bedrock agentic Development Assistant for clinical trials

AstraZeneca is a global, science-led biopharmaceutical company focused on discovery, development and commercialization of prescription medicines.The company uses AWS to support research through commercialization, and specifically applies Amazon Bedrock to accelerate clinical trials by combining structured and unstructured data.An agentic AI-powered Development Assistant gives clinical, regulatory, safety, and quality teams conversational access to trusted insights in seconds.

Pharma
AgentMulti-agentRAG

AstraZeneca Accelerates Drug Development with Amazon Bedrock Agents

AstraZeneca developed Development Assistant, an AI tool using Amazon Bedrock Agents with multi-agent architecture for fast natural language querying of clinical, regulatory, safety, and quality data.The solution unifies structured and unstructured data sources to provide transparent, actionable insights supporting faster decision-making in drug development.Multi-agent AI architecture routes queries to specialized agents for context-aware, high-performance responses across clinical trial and R&D domains.Development Assistant reduced insight generation time from hours to minutes and scaled to 1,000+ users, breaking down domain silos across pharmaceutical R&D.The tool provides transparent data source referencing and is progressing toward expansion across broader R&D functions to accelerate medicine development pipeline.

Pharma
AgentMulti-agentRAG
Microsoft

AstraZeneca and Novartis Scale AI Across Pharma Value Chain

This article provides a comprehensive overview of how leading pharmaceutical firms—including AstraZeneca, Novartis, Sanofi, GSK, Genentech, and AbbVie—are integrating Microsoft technologies such as Azure AI, Machine Learning, Cognitive Services, and Power Platform to transform drug development and operations. Real-world examples cover AI-powered drug target identification, generative molecule design, clinical trial acceleration, pharmacovigilance, supply chain optimization, and patient engagement via chatbots. The piece details both the tangible business benefits (shortened timelines, reduced costs, improved trial precision, and better patient outcomes) and persistent challenges such as data fragmentation, legacy systems, regulatory complexities, and change management. Strategic priorities for CIOs and IT leaders on how to industrialize AI, ensure enterprise-wide adoption, and promote responsible, cross-functional scaling of Microsoft technologies are emphasized. The article highlights collaborations like AstraZeneca’s enterprise AI roadmap, Novartis-Microsoft innovation lab, and Sanofi’s infrastructure modernization to demonstrate mature, scalable uses of cloud-based AI.Challenges with data interoperability, legacy infrastructure, talent and cultural adoption, and regulatory risk are addressed alongside solutions such as human-in-the-loop designs, explainable AI, and real-time learning cycles aligned with scientific and compliance goals.

PharmaGlobal
Fine-tuning
Microsoft

AstraZeneca accelerates drug discovery and clinical insights with AI

AstraZeneca, a global pharmaceutical leader, uses advanced AI and generative AI models on Microsoft Azure to fast-track drug discovery and development at its R&D center in India. L...

Pharma
Fine-tuning
Microsoft

Pharma Investment in AI for Drug Discovery

Pharma companies are increasingly investing in AI to enhance computer-aided drug design (CADD) and reduce drug development time and costs, creating a multibillion-dollar market. Fi...

PharmaUnknown
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