Life sciences innovation

Researchers in the biotech and pharmaceutical industries grapple daily with the complexity and volume of single-cell RNA sequencing (scRNA-seq) datasets, which are crucial for understanding diseases and developing targeted therapies.Sonrai sought to use generative AI to simplify and streamline interpretation of scRNA-seq data and reduce the manual burden on immunologists.Sonrai Discovery uses large language models through Amazon Bedrock to automate cluster annotation, generate consistent text reports, and support faster analysis on AWS.

SonraiPharma

PozeSCAF Discovery Solutions (formerly Immunocure Discovery Solutions) turned to AWS for scalable, high-performance infrastructure to optimize molecular dynamics workloads.The company cut simulation runtimes by more than half, reduced compute costs, and accelerated its drug discovery pipeline.It also began exploring generative AI/agentic workflows with Amazon Bedrock to build knowledge graphs from project data and flag potential side effects earlier.

PozeSCAF Discovery SolutionsPharma

Genentech uses Amazon Bedrock Agents with Anthropic Claude Sonnet 3.5 to automate complex biomedical research workflows for biomarker validation.The gRED Research Agent processes and synthesizes information from millions of scientific data sources using multi-agent collaboration and Retrieval Augmented Generation (RAG).This automation reduces manual research time from weeks to minutes, freeing scientists to focus on high-impact tasks and accelerating drug discovery.

GenentechHealthcare

BenchSci transforms fragmented biomedical evidence into a graph-native model of disease biology, empowering 9 of the top 10 pharmaceutical companies to de-risk and accelerate discovery.BenchSci’s ASCEND platform combines large language models with the Biological Evidence Knowledge Graph (BEKG), an experimentally grounded knowledge system that integrates open-access literature, closed-access publications, and proprietary pharmaceutical datasets.Its LENS extraction engine uses Google Cloud Vertex AI and Gemini models to interpret scientific papers with contextual awareness and validate claims against associated imagery before materializing structured assertions into Neo4j.

BenchSciPharma

EY guides pharmaceutical companies through adopting generative AI (GenAI) to accelerate and automate early-stage drug discovery processes.GenAI enables significant breakthroughs in molecule creation, compound screening, and toxicity prediction, previously requiring extensive time and costs.EY collaborates with life sciences industry leaders, providing strategy and change management for successful GenAI implementation.The solution leverages deep learning algorithms for virtual screening, target identification, and optimal resource allocation.Predictions point toward cost savings from 44% to 67% and time reductions up to 50% for critical research phases, as GenAI adoption accelerates.The methodology streamlines clinical trial design and data analysis, improves regulatory submission, and automates documentation and compliance.EY works with both large and small biopharma companies to extend the benefits industry-wide, including for organizations lacking in-house AI capabilities.The approach helps CDMOs and CROs differentiate using advanced AI for outsourced drug research steps.Results reported by EY clients and survey respondents describe speed-to-market and cost reduction as primary impacts.The article describes a transformation in research and development operating models for faster patient benefit and broader treatment diversity.

EYPharma

Microsoft Discovery is a new enterprise AI agent platform designed to transform research and development (R&D) across sectors. By orchestrating specialized AI agents with a sophisticated graph-based knowledge engine, researchers and scientists can reason contextually through complex data, simulate experiments, and iterate research plans faster than ever before. Built on Azure High Performance Computing (HPC) and Azure AI Foundry, it emphasizes trust, compliance, and extensibility. Real-world impact is demonstrated by Microsoft researchers rapidly developing a sustainable immersion datacenter coolant, a process that normally takes years, in just 200 hours. GSK aims to accelerate medicinal chemistry, while The Estée Lauder Companies focuses on faster product innovation. The platform integrates partner technology from NVIDIA, Synopsys, and PhysicsX to enable advances in pharma, materials, semiconductor design, and industrial engineering. Strategic alliances with Accenture and Capgemini are helping scale deployments. Microsoft Discovery is positioned as a future-proof system for solving the most challenging R&D problems using AI agents and Microsoft’s secure cloud foundation.

GSKPharma

TetraScience collaborated with Microsoft to enable pharmaceutical organizations to extract greater value from their scientific data by leveraging enterprise AI.The partnership involved integrating TetraScience’s Scientific Data and AI Cloud with the Microsoft Azure platform, providing secure, scalable infrastructure and advanced AI capabilities to biopharmaceutical customers.The solution harmonizes scientific data across siloed and heterogeneous sources, replatforming the data into AI-ready formats and enabling multimodal analytics and fast AI model training.This empowers scientists to accelerate the entire drug discovery and development lifecycle, reducing phenotype screening times and increasing efficiency in quality control and manufacturing.Biopharma organizations reported accelerated drug safety assessment, faster phenotype screening in oncology research, and automated anomaly detection applied to manufacturing and quality control processes.Microsoft Azure supplies the computational backbone and enterprise security, while TetraScience’s platform delivers context-aware scientific data unification and automation.The collaboration is set to transform biopharma by enabling more AI-driven scientific use cases and making sophisticated analytics accessible to research organizations of all sizes.

TetraSciencePharma

Adaptyv Bio, a biotech startup from Switzerland, harnesses generative AI and Microsoft Azure AI to transform protein engineering and pharmaceutical drug discovery. Addressing the need for faster, more cost-efficient innovation in drug development, Adaptyv Bio developed a platform that leverages advanced algorithms, robotics, and synthetic biology underpinned by Azure cloud services.Utilizing AI-driven analytics and generative design, the platform can optimize protein sequences, accelerate molecular discovery, and increase the precision of drug design efforts. This approach shortens the time typically required for drug pipelines and can potentially enable novel treatments for previously intractable diseases.By partnering with expert consulting firms and leveraging modern cloud infrastructure, Adaptyv Bio streamlines drug development processes, overcoming challenges typical of the regulated pharma environment. Their efforts reflect a broader trend of generative AI adoption in the biopharma sector, improving R&D timelines and contributing to significant potential cost savings across the industry.The project illustrates how Microsoft technology is accelerating new treatment modalities, with a particular focus on synthetic biology, protein engineering, and scalable AI-powered research.

Adaptyv BioPharma

The deployment of Copilot in Azure Quantum Elements marks a significant step forward for research and development teams, particularly in chemistry, materials science, and drug discovery. Scientists are now able to interact with complex computational challenges using natural language, which streamlines tasks such as generating simulation code and extracting technical insights from vast datasets. Built on Azure OpenAI and incorporating Retrieval Augmented Generation (RAG), this implementation allows researchers to automate tedious workflows, from density functional theory calculations to summarizing and referencing scientific articles. Copilot also visualizes molecular structures and aids learning in quantum computing through interactive exercises. By lowering technical barriers, it makes advanced quantum and AI tools accessible to R&D and innovation teams. Especially beneficial for the pharmaceutical industry, it supports safer and more sustainable product development and faster time-to-discovery. The solution combines AI-driven conversation, code generation, RAG-based literature search, molecular visualization, and quantum computing in one platform. Both enterprise and academic users benefit from a seamless research experience and improved productivity.

Research and pharmaceutical R&D teamsPharma

Oxygen Finance, a UK-based firm specializing in pre-procurement intelligence, collaborated with SoftwareOne and Microsoft to deploy an AI-powered solution. They aimed to automate the process of gathering data on UK public sector spending decisions. This data previously required immense manual effort but was essential for their Oxygen Insights product. The new system leverages Microsoft Azure and generative AI expertise to augment researchers' abilities, enabling them to broaden their data collection without sacrificing quality. This empowered the research team to discover new opportunities in public sector procurement, thereby increasing customer value. The partnership between Oxygen Finance, SoftwareOne, and Microsoft highlights the transformative role of AI in procurement intelligence.

Oxygen FinanceFinance