Clinical Trials Use Cases

Clinical trial programs can take many years to complete, in part due to protocol complexity and long timelines for patient enrollment. This has led companies to explore AI/ML to help expedite and optimize clinical trials program development and patient recruitment.

Optimize studies by predicting the most productive trial protocols and study locations using the HIPAA-eligible AI/ML service, Amazon SageMaker. More quickly find appropriate patients to enroll for clinical trials by extracting information from medical text, without needing previous experience in machine learning, using the Amazon Comprehend Medical service. Pharma companies can more effectively predict and plan clinical trial design and recruitment using highly scalable computational power and machine learning algorithms in the AWS Cloud.

Case studies

Whitepaper

Modernizing clinical trials with digital technologies and the cloud
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Knowledgent Video

In this video, learn how AWS Life Sciences Competency Partner, Knowledgent, part of Accenture, built its Intelligent Clinical Trial Application.
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Fred Hutch

Read how Comprehend Medical reduces the time required to sift through and label unstructured clinical record data that allows research teams to connect the right patients to clinical trials.
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Related Resources

Blog

Introducing medical language processing with Amazon Comprehend Medical

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Blog

Extract and visualize clinical entities using Amazon Comprehend Medical

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Identifying and working with sensitive healthcare data with Amazon Comprehend Medical

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Map clinical notes to the OMOP Common Data Model and healthcare ontologies using Amazon Comprehend Medical

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Webinar

An introduction to processing unstructured medical data using Amazon Comprehend Medical

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In 2018, the Clinical Trials Transformation Initiative (CTTI) provided recommendations regarding mobile technologies for capturing holistic, high quality, attributable patient data and submission to the Food and Drug Administration (FDA). As more clinical trials have incorporated patient health wearables, mobile devices, and other IoT connected technologies, fast, secure data collection in the cloud has become- and will continue to be- more critical.

AWS IoT services, like AWS IoT Device Management, excels at connecting physical devices to the cloud for secure data collection, management, and analysis. Devices can securely stream data to cloud environments, equipping sponsors to rapidly glean new insights into the safety and efficacy of their drugs. Mobile devices can also enable remote communication, reducing the need for patients to visit study sites and decreasing both the cost of clinical trials and the burdens they place on participants.

Case studies

Whitepaper

Modernizing clinical trials with digital technologies and the cloud

Learn more »

uMotif case study

In this case study, learn how uMotif relied on the wide breadth of HIPAA-eligible AWS services to securely capture more than 38 million data points from 13,500 clinical trial participant mobile devices.

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Infographic

Run faster, smarter clinical trials powered by the AWS Cloud.

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Related resources

Blog

Enhancing clinical trials using AWS technologies 

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Webinar

Clinical Trials Transformation Initiative (CTTI) Comprehensive Guide to Mobile Technologies in Clinical Trials 

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Reference Architecture

View a common, HIPAA-eligible architecture patterns that AWS customers are using to incorporate mobile technologies into their clinical trials.

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Architecture Video

In this video, learn how APN Advanced Consulting Partner Saama’s Life Science Analytics Cloud on AWS is used to accelerate and optimize clinical trials for pharmaceutical companies.

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Managing a clinical trial requires collaboration between trial investigators, contract researchers, and coordinators from the sponsor organization. These groups have historically worked together using email and fax communications, which create security, compliance, and efficiency challenges.

By creating a common platform in the AWS Cloud, sponsor organizations can remove these challenges. The AWS Cloud gives them the ability to set policies and controls covering the data and documents that all collaborators upload to the shared cloud environment, ensuring auditability and traceability.

Case studies

Whitepaper

In this whitepaper, learn how to bring consistency, control, and compliance to collaboration management.

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Sparta Systems case study

In this case study, learn how Sparta systems is helping life science organizations to integrate with supplier and contractor ecosystems while conforming to compliance standards.

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Tracelink case study

In this case study, learn how Tracelink built a collaboration platform on AWS to help life science companies protect product integrity and comply with global track-and-trace regulations.

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