Accelerating Real-World Evidence with AWS

In the rapidly evolving world of Healthcare and Life Sciences, real-world data (RWD) has become a powerful catalyst for innovation. Sourced from electronic health records, insurance claims, registries, and even wearable devices, RWD offers a window into how therapies perform in everyday clinical settings. When analyzed effectively, it leads to real-world evidence (RWE)—the clinical insights that help inform regulatory decisions, shape clinical trial design, and improve patient care.

A study of FDA-approved drugs (including biologics) revealed that 85 percent of approvals between 2019–2021 leveraged RWE. Despite its potential, turning raw data into actionable evidence remains a significant challenge. Data is often fragmented, siloed, and difficult to access or harmonize. Traditional workflows can stretch across months, delaying insight generation and increasing costs.

Amazon Web Services (AWS) is tackling this head-on. By streamlining and securing the RWD-to-RWE workflows, AWS is helping Healthcare and Life Sciences (HCLS) organizations discover, evaluate, access, and generate insights across diverse RWD sources. It can potentially shorten the process from several months down to a couple of weeks. Our set of integrated, modular offerings help HCLS organizations move quickly while protecting sensitive health and proprietary data from discovery to insights—within a secure, compliant AWS environment.

Module 1: Streamlining Data Discovery

Discovering relevant, high-quality RWD is one of the most time-consuming stages in the evidence development process. AWS, in collaboration with Datavant Connect, is transforming this phase.

Built on AWS Clean Rooms, this HIPAA-eligible, cloud-focused solution allows researchers to securely discover and evaluate patient-level, linked datasets without exposing or moving sensitive data. Data producers retain full control, and privacy is preserved throughout the entire data collaboration process.

Tasks, like feasibility analysis and dataset evaluation, that once took months can now be completed in days. Pharmaceutical leaders like Boehringer Ingelheim are already leveraging this technology to scale their RWE strategies—unlocking deeper insights into treatment effectiveness, economic impact, and long-term health outcomes.

Paul Petraro, Executive Director and Head of the Real-World Evidence Analytics Center of Excellence at Boehringer Ingelheim, emphasized the significance of this initiative: “Our investment in real-world data underscores Boehringer Ingelheim’s commitment to using cutting-edge technologies to advance medical research. By expanding this approach across more trials and commercial launches, we are positioned to drive more personalized and cost-effective treatments, ultimately transforming patient care.”

Module 2: Harmonizing Data at Scale

For biostatisticians and technical users, harmonizing complex, disparate datasets are essential—but traditionally labor-intensive. AWS has partnered with industry leaders like Aetion Inc., Norstella, Panalgo (a Norstella company), EPAM Systems Inc., and Atropos Health to deploy scalable analytic platforms that streamline this process.

These platforms support open-source tools like R and Python and enable users to:

• Build patient cohorts
• Define inclusion and exclusion criteria
• Analyze longitudinal patient journeys
• Accelerate regulatory submissions

This significantly shortens the timeline for producing study-ready datasets and evidence packages.

Module 3: Rapid Insights Generation

Even after access and harmonization, deriving insights from RWD can be a slow, technical process. That’s where Agents come in.

Using a multi-agent ReAct framework, the agent enables researchers, analysts, and business users to query complex datasets (like those in Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Snowflake, or Databricks) using natural language. The result—actionable, auditable insights in minutes instead of weeks, with no coding required, all while enforcing responsible AI safeguards and confirming regulatory compliance.

Features include:

• Role-specific experiences for different user types
• Integration with medical literature and clinical trial data
• Built-in compliance and responsible AI safeguards
• ReAct Agents able to decipher complex input questions and consult with users to generate the best experience
• Integrates reference data, ontologies, dataset specific code sets
• Integration with custom protocols for question evaluation
• Customer environment integration for multi-dataset access controls by inheriting the access controls of the user interacting with the Chatbot
• Reference catalog, human-in-the-loop, approval process and AI-generated visualizations
• Maintaining the knowledge base to log all the integrations and SQL queries generated
• Standard ingestion process helps to integrate new datasets quickly and with no manual work

The Future of Real-World Evidence is Here

The modular, secure approach of AWS to managing real-world data is transforming the way the Healthcare and Life Sciences industries generate clinical evidence. From faster trial design to better understanding of treatment effectiveness, organizations are now empowered to move from discovery to insight with unprecedented speed and confidence.

By helping to reduce the RWD-to-RWE cycle (from potentially several months down to a couple of weeks), AWS is not only helping accelerate drug development—it’s enabling a more data-driven, patient-centered future for Healthcare and Life Sciences.

Ready to learn more? Sign up on the Datavant Lighthouse Partner Program website to stay informed or contact an AWS Healthcare or Life Sciences Representative to know how we can help accelerate your business.