Artificial intelligence (AI) and machine learning (ML) are revolutionizing cancer diagnosis and treatment, leading to faster and more accurate patient decisions. Artera, a precision medicine company, is at the forefront of this transformation, developing an AI-powered platform for cancer treatment planning. The U.S. Food and Drug Administration (FDA) has granted De Novo authorization for ArteraAI Prostate, making it the first and only AI-powered software authorized to predict long-term outcomes for patients with nonmetastatic prostate cancer. ArteraAI Prostate is now recognized as an FDA-regulated software as a medical device (SaMD). This article explores how Artera leveraged Amazon Web Services (AWS) to develop and scale its AI-powered prostate cancer test, reducing time to results and enabling personalized treatment recommendations.
Customer Overview
Artera provides AI-enabled predictive and prognostic cancer tests, including the ArteraAI Prostate Test. This innovative test analyzes patient biopsy images to accurately predict the risk of localized cancer spreading and the likelihood of benefiting from specific therapies. It is the first test capable of predicting therapeutic benefit for patients with localized prostate cancer, allowing physicians to make treatment decisions with greater confidence and ultimately improving patient outcomes.
Artera is making significant advancements in precision medicine, operating in multiple regions. The FDA’s De Novo authorization for the ArteraAI Prostate platform underscores its potential to address critical needs in cancer care. Since 2024, the ArteraAI Prostate Test has been integrated into the National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology, establishing it as a standard of care for localized prostate cancer. This technology’s De Novo authorization creates a new product code category for future AI-powered digital pathology risk-stratification tools, enabling its implementation at the point of diagnosis in qualified pathology labs globally. This capability fills a crucial gap in prostate cancer care by providing actionable insights at diagnosis without delay, helping clinicians and patients make informed treatment decisions more confidently.
The Challenge of Matching Treatment to Patient
Upon a cancer diagnosis, patients face the critical decision of choosing a therapy course for the best outcome. More aggressive cancers typically require more aggressive treatment, but the potential progression of the cancer is not always clear. Additionally, patients respond differently to therapies based on their unique biological makeup. This can lead to overtreatment for some patients with less aggressive disease, resulting in unnecessary therapies and side effects, while others with more aggressive cancers may be undertreated, potentially leading to worse outcomes.
Before Artera’s solution, AI-based tools for personalized, timely cancer treatment decisions were unavailable. Physicians typically sent patient biopsy tissue samples to labs for chemical assays to measure gene expression levels, which were then used to assess patient risk. These traditional tests had several limitations:
- The entire process could take up to 6 weeks—a significant waiting period for high-stress decisions about cancer therapy.
- These tests usually identified only a small number of key genes linked to cancer risk, often lagging behind scientific advancements.
- They consumed the original tissue samples, limiting a physician’s ability to order additional tests and a patient’s ability to participate in future clinical trials or long-term monitoring.
Developing an AI-powered diagnostic tool for cancer treatment also presented unique technical challenges. Artera needed to manage and process a large volume of high-resolution biopsy image files to power its AI-driven diagnostics. These images can be enormous, sometimes reaching 8 GB, requiring them to be broken down into tens of thousands of smaller patches for model processing. Training Artera’s foundation models (FMs) necessitates serving millions of image patches at high volume to AWS servers.
Furthermore, as a healthcare company handling sensitive patient data, Artera had to ensure compliance with data residency and regulatory requirements across multiple countries, including the Health Insurance Portability and Accountability Act (HIPAA) in the United States. A robust, scalable storage solution was essential, allowing ML engineers to focus on core cancer research rather than infrastructure management.
Modern, Scalable Design Delivers Fast Results
Artera implemented a comprehensive AWS-based solution to address these challenges. The architecture features a modern, scalable design that enables secure processing of sensitive medical data and delivers rapid results to healthcare providers. The solution incorporates AI model training, advanced workflow orchestration, and data locality principles crucial for the global deployment of clinical AI models.
The following architecture diagram illustrates Artera’s secure, scalable solution built on AWS. Artera’s AI products are fundamentally composed of many individual steps within a complex workflow, often involving multiple AI models performing specialized tasks. This sophisticated workflow orchestration facilitates faster development and abstracts complexity in building their compound AI system.
This comprehensive AWS architecture diagram illustrates the integration of cloud services for a medical professionals’ portal with AI inference capabilities, including data flow from end users through global acceleration services to compute, storage, and security infrastructure in a VPC within Region A.
Medical professionals access the Artera Portal to upload biopsy images and receive diagnostic results. AWS Global Accelerator enhances availability and performance by directing traffic through the AWS global network, positioned in front of the Application Load Balancer. Amazon CloudFront provides a fast, secure content delivery network for the portal’s static assets, ensuring low-latency access globally.
Within a virtual private cloud (VPC), Elastic Load Balancing distributes incoming traffic across application servers. Amazon Elastic Container Service (Amazon ECS) hosts the web portal containers, providing the user interface for healthcare professionals. An Amazon Elastic Kubernetes Service (Amazon EKS) cluster runs the AI/ML inference workloads that analyze biopsy images using computer vision models.
Amazon Elastic File System (Amazon EFS) offers shared file storage, accessible by both Amazon ECS and Amazon EKS for storing and processing biopsy images. Amazon Relational Database Service (Amazon RDS) provides a managed relational database for patient records, diagnostic results, and application data with high availability. Amazon ElastiCache delivers in-memory caching to improve application performance and reduce latency for frequently accessed data.
AWS Identity and Access Management (IAM) ensures proper access controls and permissions. AWS Key Management Service (AWS KMS) manages encryption keys for sensitive patient data. Amazon CloudWatch monitors the entire infrastructure for performance and health. Amazon Simple Storage Service (Amazon S3) provides durable, secure storage for biopsy images and analysis results.
This architecture supports a complete workflow:
- Data ingestion – Biopsy images are securely uploaded through the portal and stored in Amazon S3.
- Processing pipeline – The EKS cluster orchestrates containerized preprocessing applications that prepare images for analysis.
- ML model training and execution – The AI models are trained and deployed on Amazon EKS, accessing preprocessed images from Amazon EFS. They then run Artera’s proprietary ML algorithms, with metadata and results stored in Amazon RDS. The company’s ML teams utilize EKS to train their massive pan-tumor FM, capable of assessing patient risk and therapy benefit across any cancer sample.
- Results storage and delivery – Analysis results are stored in Amazon S3 and made available to healthcare providers through the secure web portal.
Data Locality and Global Scalability
A significant challenge for Artera was maintaining data locality while serving AI globally. The company employs multiple AWS services to create a comprehensive solution that addresses both performance and compliance requirements.
AWS global infrastructure allows Artera to deploy Region-specific resources, ensuring sensitive patient data remains within appropriate jurisdictional boundaries. Amazon S3 provides secure, Region-specific storage buckets, and Amazon EKS enables containerized workloads to run locally in each Region.
The combination of Amazon S3, Amazon EKS, Amazon EFS, and other AWS networking services establishes a robust foundation for Artera’s global operations. This integrated approach helps Artera accelerate time to market in new regions while upholding the highest standards of data security and compliance with regional regulations.
Results and Patient Impact
By utilizing AWS Cloud services, Artera has transformed cancer diagnostics, delivering tangible benefits for patients:
- Accelerated results – Patients receive personalized treatment recommendations in just 1–2 days, a dramatic reduction compared to the 6 weeks required for traditional genomic tests, significantly shortening the waiting period for critical treatment decisions.
- Improved clinical decisions – The speed and accuracy of Artera’s AI-powered diagnostics empower physicians to make more informed treatment decisions, potentially improving outcomes for prostate cancer patients.
- Tissue preservation – Unlike traditional tests that consume tissue samples through chemical assays, the ArteraAI Prostate Test uses only digital imagery, preserving the original tissue for additional tests or clinical trials.
In 2024, nearly 300,000 Americans were diagnosed with prostate cancer. For these patients, timely and accurate diagnostics are essential.
There are over 3.5 million prostate cancer survivors in the United States. By recommending personalized treatment plans, Artera assists patients in determining the best therapeutic options to achieve progression-free survival while minimizing unnecessary side effects.
Operational Benefits
Using AWS services has provided Artera with significant operational advantages:
- Enhanced focus on innovation – With AWS managing the infrastructure, Artera’s engineers can dedicate more time to refining their ML algorithms and expanding diagnostic capabilities.
- Global scalability – Artera has successfully expanded operations while maintaining compliance with regional data regulations across multiple countries.
- Efficient processing – The test processes tens of thousands of image files through ML workflows per biopsy slide, completing in hours instead of weeks. This efficiency stems from Artera’s sophisticated workflow orchestration, which breaks down large input images (sometimes reaching 8 GB) into many small patches processed in parallel across EKS clusters.
The FDA’s De Novo authorization for the ArteraAI Prostate Test highlights the potential impact of this technology on cancer care. With AWS powering its infrastructure, Artera is well-positioned to continue revolutionizing cancer diagnosis and treatment.
Future Innovations
As Artera continues to innovate in AI-powered cancer diagnostics, its AWS-based infrastructure provides a foundation for future growth. The company’s ultimate goal is a massive pan-tumor FM capable of assessing patient risk and therapy benefit across any cancer sample. Utilizing elastic, scalable solutions on AWS, Artera has a solid foundation for developing ML models for additional cancer tests. The company has announced plans for a breast cancer product, with several more products expected soon.
Artera plans to expand its AI capabilities in several ways:
- Analyze additional biomarkers
- Integrate genomic data with imaging analysis
- Create more comprehensive diagnostic tools
- Partner with major healthcare systems to integrate diagnostic tools directly into clinical workflows
With the scalability of AWS services, Artera is positioned to handle increasing data demands as it expands to new cancer types and regions globally.
Conclusion
Artera’s journey demonstrates how AWS Cloud services can empower healthcare innovators to develop and scale life-changing technologies. By utilizing Amazon EKS, Amazon ECS, Amazon EFS, Amazon RDS, Amazon S3, AWS Global Accelerator, and Amazon ElastiCache, Artera built a robust, scalable infrastructure. This allows the company to maintain focus on its core mission: improving cancer treatment through AI-powered diagnostics.
