AWS re:Invent 2025 - From Lab to Market - AstraZeneca's Enterprise-Wide AI Success Story (IND214)

AWS re:Invent 2025 - From Lab to Market - AstraZeneca's Enterprise-Wide AI Success Story

Overview

• AstraZeneca, a leading pharmaceutical company, is leveraging AI and machine learning across its entire drug development and commercialization pipeline to accelerate time-to-market and improve patient outcomes.
• In partnership with AWS, AstraZeneca has implemented a comprehensive AI-powered platform and suite of agent-based solutions to transform key areas of their business, including R&D, clinical trials, manufacturing, and commercial operations.

Driving Transformation in R&D and Clinical Development

• AstraZeneca's bold ambition for 2030 is to deliver 20 new medicines and achieve $80 billion in revenue, which requires significant acceleration and optimization of their R&D and clinical development processes.
• Key challenges include:
  • Disparate data sources and siloed information across clinical, regulatory, and safety domains
  • Manual, time-consuming processes for tasks like site selection, patient recruitment, and adverse event reporting
• AstraZeneca built an "Agentive Development Assistant" powered by AWS technologies:
  • Integrates 16 different data products across clinical, safety, regulatory, and quality domains
  • Leverages 9 intelligent agents to provide natural language-based insights and recommendations
  • Reached over 1,000 users across 21 countries in just 6 weeks
  • Enables scientists and clinicians to make faster, more informed decisions throughout the development pipeline

Delivering Precision Commercial at Scale

• AstraZeneca's commercial organization faces the challenge of ensuring their life-changing medicines reach the right patients at the right time, requiring a "precision commercial" approach.
• Key pillars of their precision commercial strategy:
  1. Helping strategy: Deep understanding of patient journeys, HCP behaviors, and care gaps to inform commercial planning
  2. Planning: Identifying early adopters, forecasting, and optimizing resource allocation
  3. Execution: Providing personalized, data-driven insights and recommendations to field teams, marketing, and medical affairs
• AstraZeneca built the "EasyBrain" platform on AWS to unify data sources, deploy AI models, and deliver agent-powered applications:
  • Combines claims, EMR, market research, clinical data, and internal CRM data into a unified data foundation
  • Leverages predictive models and AI services to enable precision targeting, patient eligibility prediction, and automated workflows
  • Deploys agent-based solutions to accelerate content creation, reimbursement dossier authoring, and market research processes

Accelerating Agent-Based AI Capabilities

• AWS is investing heavily in building the core infrastructure and services to enable enterprise-grade agent-based AI solutions:
  • "Bedrock Agent Core" provides a secure runtime, deployment architecture, authentication, and memory management for agent-based applications
  • Open-source "Healthcare and Life Sciences Toolkit" provides templates, examples, and deployment scripts to accelerate agent-based solution development
  • AI Portal offers pre-built, production-ready agent-based solutions for common pharmaceutical use cases
• These capabilities allow AstraZeneca and other customers to rapidly build, deploy, and scale agent-based AI solutions to drive transformation across their organizations.

Key Results and Business Impact

• AstraZeneca's agent-powered "Development Assistant" and "EasyBrain" commercial platform have delivered significant benefits:
  • 2x increase in prescription volumes for users of the commercial agent-based solutions
  • Reduced market research and reimbursement dossier authoring timelines from 3 months to 2 weeks
  • Enabled faster, more informed decision-making across the R&D and commercial organizations
• By leveraging agent-based AI, AstraZeneca is accelerating its bold ambition to deliver 20 new medicines and $80 billion in revenue by 2030, while transforming patient outcomes.