What tech stack does AstraZeneca use?

Amazon Web Services is AstraZeneca's primary cloud provider, confirmed across multiple AWS case studies covering genomics, AI/ML, and drug discovery. The Centre for Genomics Research (CGR) uses AWS at population scale: a workflow using AWS Lambda for orchestration, AWS Batch for parallel compute, and Amazon S3 for storage can process over 1,600 exomes per hour and run more than 51 billion statistical tests in under 24 hours — feeding directly into AstraZeneca's drug discovery pipeline and underpinning its goal to analyze up to two million genomes by 2026. Amazon SageMaker is the ML training and deployment platform of record: AstraZeneca has used it to fine-tune HyenaDNA, a genomic foundation model capable of analyzing sequences of up to one million tokens, achieving a 20.9% improvement in pathogenicity prediction over baseline models. SageMaker adoption also cut AstraZeneca's time-to-insights in R&D from over six months to under 2.5 months.

For generative AI, AstraZeneca's 'Development Assistant' is a multi-agent generative AI platform built on Amazon Bedrock. It enables clinical data teams to query structured and unstructured trial data in natural language, with plans to scale to over 1,000 users in 2025. This positions AWS Bedrock as AstraZeneca's foundational generative AI infrastructure layer — not a pilot, but a scaling production deployment.

On the ERP side, the Axial Business Transformation Program is a six-year greenfield implementation of SAP S/4Hana, described as the largest SAP project in Europe. A team of 1,200 professionals across 19 countries is consolidating seven legacy SAP ECC finance and manufacturing instances plus three regional SAP warehouse management systems into a single S/4Hana core, spanning 27 manufacturing sites and five R&D hubs. AstraZeneca noted it is not a SAP Rise customer, citing that for regulated life sciences environments, SAP's cloud-only approach is not yet sufficiently mature. The Axial program is run through AstraZeneca's Chennai IT hub as a primary delivery engine.

For enterprise collaboration, AstraZeneca migrated its entire global workforce to Microsoft Office 365 (completed in seven months — highlighted in CIO press as one of the most rapid large-scale cloud migrations in the industry), alongside Box for cloud content management and Workday for HR and finance management processes. For learning and development, AstraZeneca built a global learning technology ecosystem on Degreed to support its ~95,100-employee workforce.

The most commercially significant recent stack change is the December 2025 selection of Salesforce Agentforce Life Sciences for Customer Engagement as AstraZeneca's unified global CRM platform. This replaces prior Veeva CRM infrastructure — a departure described by industry analysts as one of the largest Veeva defections in pharmaceutical history. AstraZeneca will implement Agentforce 360 for Life Sciences to consolidate healthcare professional (HCP) insights across its Oncology, BioPharmaceuticals, and Rare Disease commercial teams, scaling operations with AI-powered next-best action recommendations and data-driven digital campaigns. Salesforce has cited this deal as its flagship life sciences win and a proof point of the Salesforce vs. Veeva competitive shift.

For data science and bioinformatics, Python and R are the primary languages used across AstraZeneca's R&D teams, with AWS-native pipelines at the Centre for Genomics Research. AstraZeneca has also partnered with Snowflake (via the SAP-Snowflake Business Data Fabric integration announced November 2025) for data platform modernization alongside the Axial SAP transformation, suggesting a Snowflake data cloud layer is being introduced at enterprise scale.

AstraZeneca's technology footprint signals a company that has moved well past cloud adoption into deep cloud-native integration — particularly on AWS. Vendors pitching AI, data analytics, or bioinformatics solutions should expect AstraZeneca's technical teams to be sophisticated, AWS-native evaluators. Solutions that cannot integrate natively with SageMaker, S3, Bedrock, or AWS Lambda will face significant architectural objections from a team that has demonstrated production-scale AWS engineering capability. The AWS relationship is strategic and long-term; AWS is the presumptive preferred hyperscaler for new workloads.

The Salesforce Agentforce selection — displacing Veeva — is the clearest indicator of commercial stack direction. Vendors with Salesforce Life Sciences integrations, or those building on the Salesforce / Data Cloud / Agentforce platform, are optimally positioned for AstraZeneca's commercial technology budget. Veeva-first vendors should prepare for material pushback at AstraZeneca, as the CRM migration will take years to fully execute and may introduce integration complexity that deprioritises Veeva-adjacent tools.

For ERP-adjacent vendors — manufacturing execution systems (MES), quality management software (QMS), supply chain planning — SAP S/4Hana compatibility is a near-mandatory integration requirement given the Axial consolidation and the 27 manufacturing sites being standardised onto a single ERP core. Companies offering SaaS tools should also be prepared for AstraZeneca's enterprise procurement cycle: security reviews aligned to life sciences regulatory frameworks (GxP, 21 CFR Part 11, GDPR), multi-stakeholder approval processes, and multi-year contract structures negotiated centrally from Cambridge or Wilmington.