What was the impact of the AI solution?

At least 30% reduction in research times. Increased case review capacity by freeing genetic experts to focus on complex cases. Proof of concept completed in 6 weeks and tools spent about 1 year reaching production readiness.

Source

Proof of conceptEvidence: Medium65/100

Exact Sciences (PreventionGenetics) accelerates variant curation and clinical note abstraction with Amazon Bedrock

Use case typeMedical document automationUpdated Jun 13, 2026

Exact Sciences, through its PreventionGenetics subsidiary, uses AWS to accelerate variant curation and phenotype abstraction for genetic testing. The company manually reviewed scientific literature and patient clinical notes to interpret genetic variants that may cause rare disease or indicate elevated risk, and needed to speed turnaround for clinicians and patients. Working with the AWS Generative AI Innovation Center, Exact Sciences built the Variant Curation Accelerator and a phenotype abstraction tool on Amazon Bedrock, with human review, citations, source PDFs, and highlighted supporting text to improve trust and accuracy.

Organization: Exact Sciences
Industry: Healthcare
Location: United States
Published: May 2026

Reported outcomes

−30%

timeTime & speed

Strategic outcomes

Speed & agilityAccelerated variant curation workflowsCustomer experience & trustImproved trust and accuracy in reviewsScale & capacityIncreased case review capacity

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 30% decrease

AWSMay 13, 2026Customer storyInferred claimMedium evidence strength

At least 30% reduction in research times.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Exact Sciences, PreventionGenetics
Provider: AWS
Maturity: PoC
Linked source: AWS

Proof of concept completed in 6 weeks and tools spent about 1 year reaching production readiness

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Document Intelligence
2Knowledge Extraction
3Clinical Decision Support

Genetic experts manually reviewed large volumes of literature and clinical notes to interpret variants, a process that could take days and delay reporting for rare disease cases.

Built the Variant Curation Accelerator and phenotype abstraction tool with the AWS Generative AI Innovation Center.
Used Amazon Bedrock and Claude to search for relevant papers, analyze content, and present results in a UI for human review.
Added guardrails including phenotype-match checks, citations, and source PDF highlighting for traceability.
Used a machine learning document extraction capability for clinical notes to create markdown text for LLM input.

Technologies

Amazon Bedrock Amazon Textract Claude

At least 30% reduction in research times.
Increased case review capacity by freeing genetic experts to focus on complex cases.
Proof of concept completed in 6 weeks and tools spent about 1 year reaching production readiness.

Architecture

The solution uses Amazon Bedrock to run LLM analysis on searched scientific papers and clinical-note content, integrates outputs into a user interface via API for human review, and adds guardrails such as phenotype-matching checks, citations, and source-PDF highlighting. Clinical notes were converted into markdown text via an AWS document extraction capability before LLM processing.

Implementation partners1

AWS Generative AI Innovation Center

Sources & evidence1

Evidence: Medium65/100Evidence strength