Category: Healthcare

Healthcare organizations are being asked to widen access, protect increasingly thin margins, and keep clinicians from burning out. Telehealth is one of the most effective levers on all three, and it’s no longer a pandemic stopgap: 71.4 percent of physicians now use it weekly, nearly triple the pre-pandemic rate, and 72 percent of hospitals offer at least one telemedicine service (AMA, 2024). Adoption varies widely by specialty, from 68 percent of psychiatrists conducting more than a fifth of visits virtually to under 5 percent for surgical specialties, and behavioral health accounts for roughly two-thirds of telehealth claims nationally (FAIR Health, 2024), with primary care and chronic disease management as the next growth frontier. But telehealth’s promise is undercut by a growing burden: documentation is now the leading driver of clinician burnout, and that’s where agentic AI demonstrates its value.

Read how the 2026 AWS Life Sciences Symposium, the Clinical Trials track brought a shift into focus that’s well underway. Six global life sciences leaders—Novartis, Merck (with BCG), Novo Nordisk, Labcorp, Eli Lilly, and Bayer—took the stage to demonstrate what AI in drug development looks like in practice across every stage of a clinical trial.

Thousands of biomedical research papers are published every day, and no single researcher can keep pace without automated analysis. For researchers in genomics and biotechnology, staying current means manually reading through dozens of dense PDFs, extracting relevant findings about genetic variations, biomarkers, and disease associations one paper at a time. It’s slow, error-prone, and ultimately limits how much literature a researcher can realistically incorporate into their work. When the goal is discovering life-saving treatments, that bottleneck matters.

In this post, we describe how the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School built mindLAMP, an open source digital psychiatry platform running on Amazon Web Services (AWS). Now deployed at 65 sites across 17 countries, mindLAMP enables continuous patient monitoring, digital phenotyping, and AI-augmented clinical workflows—all powered by serverless AWS infrastructure that a small academic group can operate without a dedicated site reliability engineering team.

In this post, we show how you can use AWS HealthLake to meet CMS-0057-F requirements while building a FHIR data solution that accelerates your broader digital transformation.

Dr. Boris Bogdan, Director of Life Sciences at AWS, addressed the pilot-to-production challenge head on, sharing four strategic differentiators that set successful organisations apart from those stuck in pilot mode.

We are excited to announce resource matching for AWS HealthLake, now available in gated preview. Resource matching is a built-in capability that automatically identifies FHIR resources representing the same real-world entity and links them without modifying or merging the original data.

Across R&D organizations, AI agents are beginning to design molecules, plan syntheses, execute assays, and analyze experimental data. But these systems often operate without awareness of prior experiments, failed approaches, or parallel work happening across the organization. In this blog, learn how Sanofi recognized this limitation early and partnered with Amazon Web Services (AWS) to reimagine the foundation for AI-enabled discovery.

Novo Nordisk, a leading global healthcare company, and Amazon Web Services (AWS) today announced a strategic partnership to accelerate drug discovery and modernize operations through AI and cloud technologies.

In this post, we build on that foundation by constructing specialized AI agents for each data modality along with a supervisor agent that orchestrates cross-modal analysis using Amazon Bedrock AgentCore and Strands Agents SDK. We also train predictive AI models with Amazon SageMaker AI to predict patient outcomes from multimodal features. To further explore the implementation details and get hands-on experience, refer to the accompanying code repository.