Therapeutics research

Protein researchers face a time-consuming challenge: manually searching through thousands of peptide sequences to find structurally similar candidates is slow, error-prone, and requires deep domain expertise to interpret results.A conversational protein research copilot combines natural-language query parsing, protein embedding generation, vector similarity search, and AI-generated scientific summaries in a single interface.

Henry Schein OneHealthcare

Giles AI leverages Google Cloud's unified AI ecosystem to accelerate clinical research and improve compliance.The platform uses Document AI to parse unstructured medical literature and Gemini for complex reasoning to ensure high accuracy and trustworthiness.The infrastructure includes Google Kubernetes Engine and Cloud Run to provide low latency, scalable real-time features.Model Garden on Vertex AI enables specialized model deployment for different healthcare use cases.

Giles AIHealthcare

Phagos, a Paris-based biotech startup, is pioneering AI-powered phage therapy to combat antibiotic-resistant bacterial infections using generative AI models on Amazon SageMaker to match bacteriophages to specific bacteria.The challenge addressed is the inefficiency and slowness of traditional antibiotic development amid rising antibiotic resistance causing millions of deaths annually.Phagos developed predictive AI models trained on genomic data using Amazon SageMaker, and utilizes Amazon EC2 for computation, Amazon S3 and RDS for scalable and secure data storage, enabling rapid phage-bacteria matching.The AI platform reduced treatment development time from over 10 years to about two months, achieved 99.5% time savings in phage screening, and allowed deployment in animal farming with plans for human use by 2030.

PhagosHealthcare

Moderna, a global biotech leader, has pioneered the use of AI across its R&D, manufacturing, and commercialization, fueling its rapid response to COVID-19 and driving breakthroughs in mRNA medicine discovery. The company's CIO, Brad Miller, describes an organizational vision centered on data and AI, treating mRNA as the 'software of life.' By building a proprietary data ecosystem and integrating AI algorithms throughout every business process, Moderna enables personalized drug design, rapid therapy development, and optimized manufacturing. To ensure company-wide adoption, Moderna launched the Moderna AI Academy, democratizing AI upskilling at all levels. Today, Moderna claims its 5,000-employee workforce operates at the capacity of 50,000 through AI-powered digital transformation. AI is leveraged in everything from autonomous design of personalized therapies to supply chain optimization, supporting Moderna's ambitious goals to bring 15 new products to market within five years. This cultural and technological shift aims to maximize patient impact and efficiency using Microsoft's data and AI platforms.The company's experience highlights how end-to-end AI integration can redefine timelines, productivity, and innovation in life sciences. Moderna's journey illustrates benefits for both workforce upskilling and direct business value—faster development, enhanced precision, and new medicine modalities.

ModernaPharma

Pharmaceutical customers faced a challenge of automating detection of adverse drug events from diverse sources like social media, calls, emails, and handwritten notes to support pharmacovigilance efficiently and cost-effectively.The solution involved fine-tuning transformer-based large language models using Amazon SageMaker and Hugging Face Transformers on the Adverse Drug Reaction dataset, employing synthetic data generation with Falcon models to address data skew, and ensuring HIPAA compliance with encryption.This ML solution improved classification accuracy of adverse events, enabled automated real-time detection supporting safer pharmacovigilance workflows for unnamed pharmaceutical customers, and was implemented using AWS Cloud Development Kit.

Unnamed pharmaceutical customersPharma

Sanofi, a global pharmaceutical leader based in France, is leveraging advanced AI and Microsoft Azure technologies to transform two core areas: cancer treatment optimization and drug discovery acceleration. In partnership with AI-driven firms like Owkin, BioMap, and Exscientia, Sanofi employs large-scale federated learning, multimodal medical data analysis, and protein large language models (LLMs) to: 1) discover prognostic biomarkers and novel therapeutic targets in aggressive cancer subtypes; and 2) automate protein engineering and minor molecule candidate discovery for new drugs. Their Responsible AI framework guides transparent, ethical implementation. While most AI-enabled pipelines are recently launched or ongoing, the company has announced faster drug identification timelines, expansion into immunology, and progress of novel therapeutic agents to preclinical phases—all enabled by secure, scalable Azure cloud services. The implementation involves collaborations and integration between proprietary data, cloud AI services, and advanced analytics for precision medicine.

SanofiPharma

Syneos Health has formed a multi-year strategic partnership with Microsoft to enhance clinical trials and commercial processes for biopharma clients. Utilizing the Microsoft Azure platform, including services such as Azure Synapse Analytics, Data Factory, and SQL Database, and incorporating advancements from OpenAI, Syneos developed an AI-enabled analytics platform aimed at streamlining site selection, reducing enrollment timelines, and accelerating treatment delivery. This collaboration combines Microsoft's AI leadership and Syneos Health's biopharma expertise to deliver critical advancements in health sciences.

Syneos HealthHealthcare

Novartis has partnered with Microsoft to enhance its drug discovery processes by leveraging AI technologies provided by Azure. This collaboration enables Novartis scientists to analyze extensive datasets and effectively use machine learning tools, significantly expediting the identification of viable drug candidates. The use of advanced analytical methods allows researchers to transform tasks traditionally taking months or years into processes executed within weeks or even days.

NovartisHealthcare

Novartis collaborates with Microsoft to leverage AI for enhancing drug discovery and improving healthcare delivery. This partnership includes deploying AI-enabled digital health tools to accelerate detection of diseases like leprosy by analyzing medical images. The joint efforts aim to transition healthcare systems from reactive to proactive approaches. AI applications are integrated across the pharmaceutical pipeline, covering early discovery, development, manufacturing, and patient care. By extracting insights from real-world data, advancing research, and ensuring ethical adoption of AI, this initiative marks a revolutionary turning point for healthcare delivery, especially in underserved regions.

NovartisHealthcare

Almirall, a leading pharmaceutical company, faced significant challenges in manually reviewing medical research papers to extract relevant information, resulting in a time-consuming and error-prone process.NTT DATA designed and implemented a platform for Almirall that leverages Microsoft Azure OpenAI Service to provide advanced question-answering and semantic search capabilities for medical literature.The platform automates the extraction of pertinent data, enabling researchers to ask scientific questions and get accurate answers from a vast array of real-world evidence papers.By pre-processing and indexing research articles and automating spreadsheet data population, Almirall's research teams benefit from much faster data retrieval and significantly reduced human errors.Azure OpenAI models used in the solution reach over 90% accuracy in responses, modernizing how pharmaceutical knowledge is managed and driving industry transformation.Almirall’s partnership with NTT DATA and Microsoft not only supports advanced research but also positions the company as a leader in digital health innovation.The collaboration demonstrates the substantial value of integrating AI and cloud solutions in pharmaceutical research for global competitiveness.

AlmirallPharma