Accelerating healthcare & life sciences innovation with generative AI (HLS201)

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Democratizing Access to AI in Healthcare and Life Sciences

Challenges in the Current Landscape

• Researchers often struggle to find and access the data needed to train models or make use of existing models
• Generating new data required for research is often a manual, time-consuming process
• AI is still too technical for most people, requiring expertise in areas like model training, software pipelines, and infrastructure scaling

AWS Initiatives to Address These Challenges

1. General-Purpose AI and Generative AI Services:

   • Amazon Bedrock, Amazon SageMaker, and other less well-known but important services
   • Enabling customers to tackle data access, data generation, and AI democratization challenges

2. Industry-Specific, Fit-for-Purpose Services:

   • Developed over the past 5 years to address the unique needs of healthcare and life sciences customers
   • Helping customers move faster in adopting AI and democratizing access to AI

3. Getting Data to the Cloud:

   • The first step for customers to take advantage of AWS AI and generative AI services
   • Providing the elasticity, security, and availability needed for data science and AI at scale
   • Example: Johnson & Johnson's cloud-first strategy and 5x increase in cloud adoption since 2019

Accelerating Innovation in R&D, Diagnosis, and Treatment

Target Identification

• Requires accessing and harmonizing data from multiple sources, a complex and time-consuming process
• Amazon Data Zone and Bedrock Agents help automate and streamline this process
• Example: Genentech's implementation of a research agent on AWS Bedrock

Lead Identification

• Generative AI and predictive models have significantly sped up key steps in the drug design process
• New models like ESM3 and Amplify offer unprecedented capabilities
• AWS HealthOmics helps orchestrate and automate AI biology workflows

Clinical Trials

• Modernizing data infrastructure and clinical datasets to leverage analytics and AI
• Merck's "Zero Gravity" program to simplify their current architecture and increase agility

Real-World Data and Patient Impact

• Challenges in identifying, licensing, and using real-world data as real-world evidence
• AWS and partner DataVan working to automate metadata cleanup and enable better access to real-world data

Advancements in the Clinical Environment

Electronic Medical Records (EMRs) and Medical Imaging

• Importance of moving EMRs and medical imaging data to the cloud
• AWS services like Health Lake and Health Imaging enabling advanced analytics and AI

Clinical Documentation

• Generative AI and LLMs helping to reduce the clinical documentation burden and improve clinical communication
• Examples of Pieces Technology's work with the Cleveland Clinic

Transforming Patient Access to Therapies

• Barriers to patient access: finding a doctor, affording treatment, and physically obtaining medication
• Lilly Direct: Lilly's initiative to address these barriers and provide a streamlined, accessible experience

Conclusion

• The impact of AI and cloud technologies in healthcare and life sciences is truly realized when it benefits patients
• Continuous progress in democratizing access to these transformative technologies is key to unlocking their full potential