The pharmaceutical industry is rapidly embracing artificial intelligence, and Novo Nordisk is taking another major step toward integrating AI into drug discovery and research. The Danish healthcare company is expanding its use of Amazon Web Services (AWS) artificial intelligence technologies to support scientific research, target identification, therapy design, biological analysis, and other research workflows.
Under a newly announced agreement, AWS will become Novo Nordisk’s preferred cloud provider and strategic AI partner. The collaboration is designed to combine Novo Nordisk’s expertise in chronic diseases and pharmaceutical research with AWS cloud infrastructure, artificial intelligence services, and life sciences technologies.
A central part of the partnership is the creation of a co-innovation hub at Novo Nordisk’s existing London facility. The hub will bring together Novo Nordisk scientists and research teams with AWS engineers, AI specialists, applied scientists, and professional services experts. By placing these teams together, the companies aim to reduce the traditional separation between computational research and laboratory experimentation.
The broader objective is ambitious: using AI and agentic technologies to help shorten the journey from identifying a promising drug target to delivering a potential medicine into human testing.
Novo Nordisk and AWS Expand Strategic AI Partnership
The partnership represents an expansion of Novo Nordisk’s existing relationship with AWS. While the pharmaceutical company has already been using AWS technologies for internal artificial intelligence applications, the new agreement takes AI deeper into the scientific side of drug development.
Thilde Hummel Bøgebjerg, executive vice president of Enterprise IT & Quality at Novo Nordisk, said the combination of advanced AI technology and scientific expertise could have a significant impact on medicine discovery and development.
According to Bøgebjerg, artificial intelligence has the potential to change how medicines are discovered, developed, and delivered. However, she emphasized that meaningful results depend on combining advanced technology with scientific knowledge and a clear focus on patients.
The London co-innovation hub is intended to provide exactly this combination. Novo Nordisk researchers can contribute pharmaceutical and disease-specific expertise, while AWS teams provide cloud computing capabilities, artificial intelligence technologies, and engineering resources.
Instead of moving research between separate computational and laboratory teams, the companies aim to create a more connected workflow in which data analysis, AI-driven predictions, candidate selection, and experimental testing can work together.
AI Agents Could Transform Drug Discovery
One of the most important developments in the partnership is the planned use of AI agents in drug discovery.
Traditional AI applications generally perform a specific task based on information provided to them. Agentic AI systems are designed to take a more active role by coordinating multiple steps, using tools, accessing information, and completing complex workflows.
In drug discovery, this approach could allow AI systems to support researchers across several stages of the process.
AWS is providing technologies including Amazon Bio Discovery, a platform designed to support computational biology and drug development through AI models and agents.
According to AWS, Amazon Bio Discovery provides researchers with access to more than 40 biological AI models. AI agents can help select and coordinate appropriate models depending on the research problem.
Organizations can also combine AWS-hosted models with their own proprietary models to create multi-step computational workflows.
For Novo Nordisk, these capabilities are expected to support activities such as:
- Identifying potential drug targets
- Designing potential therapies
- Analysing biological information
- Generating potential drug candidates
- Ranking potential candidates
- Supporting laboratory synthesis and testing
- Analysing experimental results
- Refining computational models
This creates a potentially continuous research loop. AI can help generate and rank candidates, researchers can select promising candidates for laboratory testing, and experimental results can then be returned to the computational workflow.
The resulting information can be used for additional analysis and model refinement.
Connecting Computational Research With Laboratory Testing
One of the biggest challenges in modern drug discovery is managing the large amount of information generated during research.
Scientists can use computational methods to predict promising biological targets or molecules, but those predictions ultimately need to be tested experimentally. Connecting the computational and laboratory stages more closely could help researchers identify useful candidates more efficiently.
Novo Nordisk and AWS intend to use the new AI infrastructure to create this connection.
Potential drug candidates identified through computational workflows can be selected for laboratory synthesis and testing. Once experimental results become available, they can be fed back into the computational process.
This approach could create a feedback loop between AI models and physical experiments.
Instead of treating computational analysis and laboratory research as completely separate stages, the workflow can allow each stage to inform the other.
The companies said the overall objective is to shorten the path from identifying a drug target to a first human dose.
For a pharmaceutical company working across chronic diseases, reducing the time required to evaluate potential treatments could have significant implications for future drug development.
Novo Nordisk Already Has Thousands of Employees Using Generative AI
The new drug discovery initiative builds on Novo Nordisk’s existing use of generative artificial intelligence.
According to an AWS case study, more than 25,000 Novo Nordisk employees have used a generative AI platform built on Amazon Bedrock.
The platform has been used to create chatbots covering more than 2,500 use cases.
These applications include information retrieval and document drafting for non-regulated processes.
One major deployment reportedly uses a collection of approximately 140,000 documents and processes more than 26,000 prompts every month, according to AWS.
The scale of this existing deployment demonstrates how Novo Nordisk has already incorporated generative AI into parts of its workforce.
The new agreement expands that strategy beyond employee-facing applications and into research, drug development, and other scientific workflows.
AI Reduces Clinical Documentation Time
Novo Nordisk has also explored generative AI for clinical-study documentation.
According to the AWS case study, the company used Anthropic’s Claude 3.5 through Amazon Bedrock to support certain clinical documentation processes.
The system reportedly reduced the time required to generate some clinical documentation by more than 90%.
Work that previously required between 40 and 50 people and could take as long as 15 weeks was reduced to minutes for a team of three.
However, the use of AI does not eliminate professional oversight. Medical professionals continue to review and validate the generated material.
This example illustrates the role AI can play in pharmaceutical operations: rather than replacing scientific and medical professionals, AI can assist with time-consuming information-processing and documentation tasks.
The same philosophy is now being extended into drug discovery, where AI agents and biological models could help researchers manage complex computational workflows.
Amazon Bedrock Will Support Multiple Research Data Types
Another important element of the partnership is the planned use of Amazon Bedrock to develop AI applications capable of working across different types of research information.
These include:
- Clinical datasets
- Genomic datasets
- Imaging datasets
Bringing these different sources of information together could provide researchers with a broader view of disease biology and potential treatment responses.
According to the companies, insights from early-stage research could also be used to inform clinical trial design.
This creates another connection between laboratory research and clinical development.
Instead of treating genomic, imaging, clinical, and early research data as isolated information sources, AI applications can potentially help researchers identify relationships across these datasets.
For a pharmaceutical company working on chronic diseases, the ability to analyse large and diverse datasets could become increasingly important as research becomes more data-intensive.
Novo Nordisk to Expand Its Use of AI Agents
The partnership also includes Amazon Bedrock AgentCore, AWS infrastructure designed to help organizations deploy and operate AI agents.
AWS describes AgentCore as infrastructure that allows AI agents to work across enterprise data, connect with existing systems, and execute multi-step workflows.
Novo Nordisk has not provided detailed information about the specific AgentCore functions that will be used in individual research projects.
However, the company said it intends to deploy the technology across research and operational processes.
This suggests that agentic AI will not be limited to one particular stage of drug discovery.
AI agents could potentially support different tasks across the organization, depending on how individual applications are developed and deployed.
Dan Sheeran, vice president and general manager of Healthcare and Life Sciences at AWS, said the Novo Nordisk collaboration demonstrates what can happen when artificial intelligence is combined with deep life-sciences expertise.
The companies are focused on using agentic AI to address bottlenecks across the drug discovery process rather than simply analysing those bottlenecks.
AWS Engineers Will Work Directly With Novo Nordisk
Another distinctive aspect of the agreement is the involvement of AWS Forward Deployed Engineers.
These AWS technical professionals will work directly with Novo Nordisk teams on systems developed through the collaboration.
The programme is designed to place AWS technical staff alongside customers as they work on AI projects, including agent-based applications.
This direct collaboration could help Novo Nordisk move AI concepts from experimentation into practical systems more quickly.
Instead of developing technologies independently and handing them over later, scientists, engineers, AI specialists, and professional services teams can work together during development.
The London co-innovation hub provides a physical environment for this collaboration.
Partnership Builds on Broader Amazon Relationship
The AWS agreement is part of a wider relationship between Novo Nordisk and Amazon.
The two companies also have relationships involving Amazon Pharmacy, Amazon Ads, and One Medical.
AWS has separately announced life sciences AI collaborations with Flagship Pioneering and Johnson & Johnson in 2026.
These developments reflect the growing role of cloud computing and artificial intelligence in pharmaceutical research.
Drug discovery increasingly depends on large datasets, sophisticated computational models, high-performance computing, and machine learning systems.
Cloud platforms can provide the infrastructure required to manage these workloads while AI technologies can help researchers analyse information and explore potential solutions.
Novo Nordisk Is Also Working With OpenAI
The company’s AI strategy is not limited to AWS.
Novo Nordisk has also pursued artificial intelligence projects with OpenAI, including efforts involving drug discovery, manufacturing, and commercial operations.
This indicates that the company is exploring AI across multiple areas rather than relying on one technology platform or provider.
The pharmaceutical company has also signed on to use Denmark’s Gefion supercomputer.
Gefion provides computing capacity for workloads including AI model development and other data-intensive scientific research.
The combination of cloud infrastructure, AI platforms, specialized models, and high-performance computing gives Novo Nordisk access to different technological approaches for different research and business requirements.
What This Means for the Future of Drug Discovery
The Novo Nordisk and AWS partnership highlights how the next stage of pharmaceutical AI may move beyond individual generative AI tools.
Earlier implementations often focused on tasks such as document creation, information retrieval, or employee assistance.
The new generation of AI applications is increasingly focused on multi-step scientific workflows.
Agentic AI can potentially help coordinate different models, analyse multiple datasets, connect systems, and assist researchers with complex sequences of tasks.
In drug discovery, this could mean using AI to move from biological information to potential targets, from targets to therapeutic designs, and from computational predictions to laboratory testing.
However, pharmaceutical research remains highly dependent on scientific validation. AI-generated predictions and candidate molecules still need to be assessed through appropriate laboratory and clinical processes.
The Novo Nordisk approach therefore combines AI capabilities with scientists, medical professionals, engineers, and researchers.
Novo Nordisk and AWS Aim to Accelerate Medicine Development
Novo Nordisk CEO Mike Doustdar said the AWS partnership is intended to accelerate drug discovery and increase the use of AI throughout the company’s work on chronic diseases.
AWS CEO Matt Garman similarly said the companies intend to use the technology to shorten drug discovery timelines, process complex research datasets, and apply insights across therapeutic areas.
The partnership therefore represents more than a conventional cloud computing agreement.
It brings together pharmaceutical research, artificial intelligence, cloud infrastructure, biological models, AI agents, high-performance computing, and laboratory experimentation.
The London co-innovation hub will serve as an important part of this strategy by bringing Novo Nordisk scientists and AWS technical teams together.
With more than 25,000 employees already using a generative AI platform based on Amazon Bedrock and more than 2,500 chatbot use cases, Novo Nordisk has established a substantial foundation for AI adoption.
The next stage is to apply these technologies directly to the scientific challenges involved in discovering and developing new medicines.
Conclusion
Novo Nordisk and AWS are expanding the role of agentic AI from everyday enterprise applications into the core processes of drug discovery.
Through the new strategic partnership, AWS will become Novo Nordisk’s preferred cloud provider and AI partner, while a new London co-innovation hub will connect AWS engineers and AI specialists with Novo Nordisk scientists.
Technologies such as Amazon Bio Discovery, Amazon Bedrock, and Amazon Bedrock AgentCore are expected to support drug target identification, therapy design, biological analysis, candidate ranking, clinical and genomic data workflows, and other research processes.
The companies aim to create stronger connections between computational predictions and laboratory testing, with the broader goal of shortening the path from a potential drug target to a first human dose.
Novo Nordisk’s existing work with AWS, OpenAI, and Denmark’s Gefion supercomputer shows that the company is pursuing a broad artificial intelligence strategy.
As AI becomes increasingly capable of coordinating complex research workflows, partnerships such as this one could play an important role in shaping how pharmaceutical companies approach future drug discovery.
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