Precision medicine

Sonrai built an end-to-end MLOps framework on Amazon SageMaker AI for precision medicine biomarker discovery.The workflow helps evaluate many omic combinations while preserving traceability and reproducibility required for regulated clinical use.

SonraiHealthcare

Novo Nordisk, a global pharmaceutical leader, is revolutionizing drug development through strategic integration of AI and advanced analytics. Spearheaded by Dr. Faisal M. Khan, the company's corporate vice president of AI and analytics, Novo Nordisk leverages partnerships with Valo Health, Microsoft, MIT, and NVIDIA. They invest heavily in AI talent, infrastructure, and the establishment of innovation hubs such as the national AI Innovation Centre in Denmark and a new AI research hub in London. Key AI applications include accelerating the identification of drug candidates for chronic diseases and designing personalized treatment plans to improve patient outcomes. Infrastructure improvements include leveraging Microsoft's cloud technology for scaled computational power and NVIDIA hardware for supercomputing. Challenges include managing vast data, navigating complex regulations, and attracting top AI talent. The company remains committed to advancing global collaborations and ensuring sustainable, renewable-powered data center operations for long-term pharmaceutical innovation.

Novo NordiskPharma

SOPHiA GENETICS, in collaboration with Città della Salute e della Scienza di Torino, leverages Microsoft Azure to power its SOPHiA DDM™ platform. This platform enables advanced genomic analysis and precision medicine practices, focusing on cancer and rare diseases. By optimizing workflows and employing AI-powered analytics, the solution enhances researchers' ability to analyze next-generation sequencing (NGS) data. Microsoft Azure provides a secure and scalable cloud infrastructure to manage the vast datasets involved.

Città della Salute e della Scienza di TorinoHealthcare

Microsoft’s AI for Health program tackles global health issues using AI technologies to enhance critical areas like disease prediction, cancer identification, and health equity. Over 200 projects since 2020 show real-world impact, including advancements in imaging technologies and chatbot tools for behavior change.

Stanford Center for Genomics and Personalized Medicine (SCGPM) at Stanford University built a mega-scale genetic variation analysis pipeline on Google Cloud Platform using Google Genomics and BigQuery to analyze large DNA sequencing datasets faster than on-premises clusters and enable secure sharing of genomic data.The team processed hundreds of whole genomes for the Million Veteran Program pilot and established security best practices for storing and sharing genomic data in the cloud.

Stanford Center for Genomics and Personalized MedicineHealthcare

AZ Delta, one of Belgium's largest hospitals, faced challenges in analyzing complex and diverse patient medical records to enable personalized treatment while ensuring data security.The hospital's on-premises infrastructure was inadequate for large-scale medical data analytics, causing slow query times and difficulty handling vast, varied data.AZ Delta migrated its medical data to Google Cloud, utilizing BigQuery for fast querying, Google Kubernetes Engine for ML model deployment, Virtual Private Cloud for security, Cloud Identity for authentication, and Apache Airflow for ETL processes.AZ Delta collaborated with ML6 for AI expertise and security to build a scalable, secure medical data analytics platform.The solution reduced data query times from 15 minutes to 15 seconds, enabling rapid insights for clinical decision-making and personalized treatment planning, with plans to expand the platform with additional data types like electrocardiograms and pathology images.

AZ DeltaHealthcare

Svaas Wellness Ltd developed MyFlexa, an app providing personalized exercise plans for musculoskeletal pain patients, leveraging MediaPipe AI for real-time posture and movement feedback via computer vision.The app collects detailed patient data for healthcare provider review, helping improve pain management beyond pharmacological approaches.Currently piloted with 3,000+ patients in Russia, with plans to scale to 50,000, the app aims to enhance adherence and effectiveness in pain treatment using AI-driven digital coaching and performance analysis through Google BigQuery.