Overview
Every year, over two million patients in the U.S. discover they have cancer for the first time, with over eighteen million patients suffering globally (source: National Institutes of Health; World Health Organization). In the case of Brent, a young husband and father sought care following a mountain bike accident that caused pain and discomfort. Unexpectedly, a test revealed atypical cells, and further examination found tumors. After their removal and biopsy, Brent was diagnosed with stage three bladder cancer. He started chemotherapy right away. As part of his treatment plan, Brent’s oncologist introduced him to Natera’s Signatera testing, which tracks cancer indicators over time. Over about a year, the Signatera tests showed steadily rising cancer indicators. Signatera’s ultra-sensitive detection can detect tumor DNA before imaging or clinical signs, and this earlier detection potentially enables earlier intervention. Signatera detected Brent’s recurrence of cancer nine months before traditional CT scans would have found it. Brent and his care team were able to proactively treat the cancer with immunotherapy up to a year earlier than traditional methods would have alerted his care team. Following treatment, his Natera tests showed no cancer, enabling Brent’s recovery and giving Brent and his family peace of mind and space to plan for the future.
Cell-free DNA (cfDNA) testing has become increasingly important in patient care, helping doctors evaluate various health conditions through a standard blood draw—to screen pregnancies for genetic conditions needing treatment, to assessing risk of organ transplant rejection, and monitoring cancer recurrence. Natera is a global leader in cfDNA testing to deliver positive impact for patients like Brent worldwide, across oncology, women’s health, and organ ›health. “Our aim is to transform the management of disease, worldwide. This is a bold statement, but our mission is to make personalized genetic testing a standard of care for patients. We can help our patients live longer, healthier lives with more information about their health, and more targeted interventions," said Buholzer. To reach more patients, faster, Natera is transforming disease management through AI-first modernization of their data infrastructure on Amazon Web Services (AWS).
About Natera
Natera specializes in genetic testing using noninvasive, cell-free DNA technology with a focus on oncology, women’s health, and organ health. Doctors and clinics use Natera’s tests to design treatment plans and provide precision medicine to patients. The company aims to make personalized genetic testing and diagnostics part of the standard of care to protect health and inform earlier, more targeted interventions that help lead to longer, healthier lives.
Challenge | Scaling To Meet Patients’ Needs Worldwide
Since it was founded in 2004, Natera has completed more than 10 million diagnostic tests for patients. Natera currently processes over 54,000 tests weekly, generating approximately 1.6 petabytes of data across two labs. Natera needed to scale rapidly while maintaining high-quality diagnostic operations to continue meeting patient and provider demand while achieving the accuracy of modern technology. "As we grew, we sought to enhance our internal data sharing processes and optimize the use of data for analytics and decision-making to deliver for patients more effectively. So, we turned to accelerate innovation with generative AI on AWS, increasing the speed of providing treatment to patients," said Mirko Buholzer, VP of Software Engineering at Natera.
Data of this size and workload complexity is inherently challenging to manage, especially with the security needs for private patient information. As Natera expanded its genetic testing operations worldwide, it sought to find ways to democratize data access to achieve positive outcomes for patients. "Data silos were a problem because they were eating up resources. We were spending too much time on data management," said Buholzer. For example, with their Signatera test emerging as one of the fastest-growing genomic diagnostic tests globally personalized to test patients for cancer recurrence, Natera needed robust architecture to return results quickly to patients like Brent. Medical research is human labor intensive. To transform diagnostic treatments worldwide, Natera sought to offload manual heavy lifting onto AI to free up researchers time to focus on priority insights to deliver for patients more effectively.
Solution | Modernizing on AWS To Reach More Patients with Precision Medicine
Natera is transforming cancer care for patients worldwide, and AWS HealthOmics is the engine driving this revolution. By automating the complex computational work of processing massive cfDNA datasets, HealthOmics enables Natera's scientists to focus on what matters most: developing breakthrough tests that save lives. The platform handles compute, scalability, scheduling, and orchestration seamlessly, while Natera's scientists write their pipelines in Nextflow without worrying about underlying infrastructure. AWS Step Functions ensures workflow reliability from dataset ingestion to output archival, with full traceability for troubleshooting—making the entire process automated and dependable. This has enabled Natera to scale Signatera Oncology tests to serve over 250,000 patients, with HealthOmics now processing over 54,000 tests and 60,000 pipelines weekly across lab locations. This enables Natera to detect disease recurrence up to 9 months earlier than standard imaging—allowing patients to receive critical treatment sooner when it's most effective.
To unlock critical insights from clinical documents, Natera deployed Amazon Textract to perform the initial text extraction from unstructured documents. Amazon Textract first processes documents to extract structured and unstructured content, which is then segmented using semantic and embedding-aware chunking strategies. The resulting chunks are analyzed in Amazon Bedrock using the Claude 3.5 Sonnet model to generate embeddings and perform document-level parsing and understanding. Embeddings are stored in Amazon Relational Database Service (Amazon RDS) with vector search capabilities, optimized for semantic retrieval. This pipeline enables more precise attribute extraction, increasing the number of extracted elements per test document from 25 to 46. The workflow management is handled by AWS Step Functions, which orchestrates the process flow from document upload.
Amazon SageMaker Unified Studio serves as a comprehensive integrated development environment (IDE) that enables users to perform end-to-end machine learning and data analytics tasks within a single environment. The SageMaker Unified Studio solution enables teams to efficiently manage and analyze clinical and genomic data, helping streamline data discovery and access across the entire domain. For data producers, the system allows transformation of raw data into valuable data products aligned with different lines of business, which can then be published to the SageMaker Catalog for discovery and access. Data consumers, such as data scientists, can leverage published data products through a structured subscription process, where producer projects review and grant access requests to maintain secure data sharing. The solution significantly improves data discovery and access efficiency, reducing time spent by scientists and engineers in searching for relevant datasets while maintaining appropriate governance and access controls. Within this environment, Amazon QuickSuite provides the ability to combine and analyze data from multiple sources in one place. Standard reporting and analytics using pre-built dashboards where users can interact with existing visualizations through filters and controls. It has secure sharing and collaboration features with granular permission controls. The platform helps create tailored datasets that can reduce time-to-insight and ultimately drive improved patient outcomes in genetic testing.
Outcome | Transforming Patient Care Possibilities with AI
Natera nearly doubled data extraction, from 25 to 46 elements per test, enabling more accurate patient care, and it achieved a 150% cost reduction in data processing. But, its work is far from over. To build on the momentum of their innovation thus far, Natera is looking to leverage AI to reinvent what’s possible with precision medicine. Natera’s identified over 200 potential use cases for AI implementation with personalized healthcare delivery. For example, medical research is manual and time intensive. Natera research teams work to access and review the most relevant research papers to stay up-to-date on new insights, best practices, and protocols to deliver high quality care for patients—a process that can take months. “With the pipeline we've built using Amazon Bedrock, Amazon SageMaker UI, and AWS HealthOmics, we see potential to accelerate the time to insights from months to minutes—to enable our researchers to quickly make informed decisions to find the best path forward for tests in development,” said Buholzer.
Natera has the capability to experiment with extracting unstructured data out of clinical data with AI to gain new insights and bring new tests to market for women’s health, oncology, and organ health. For Brent, and the over two million new cancer patients receiving treatment, the Signatera test could mean even faster detection of cancer recurrence. The Signatera test is able to detect cancer recurrence 6-9 months earlier than standard imaging, so imagine what’s possible with further innovation. Natera launched its proprietary AI foundation model platform on AWS to drive innovation across therapeutic development, from early target discovery to real-time clinical decision support. Natera’s innovative testing and analysis solutions have impacted the lives of countless patients and their families, and with AI, Natera sees the potential to bring new tests to market and support patients with insurance coverage for tests to positively impact the patient care journey.
This enables Natera to detect disease recurrence up to 9 months earlier than standard imaging—allowing patients to receive critical treatment sooner when it's most effective
Mirko Buholzer
VP of Software Engineering, NateraAWS Services Used
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