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What is Unlearn?

Advancing artificial intelligence to eliminate the necessity for trial and error in healthcare, our digital twins enable rapid and reliable clinical trials. We prioritize research in fields such as neuroscience, immunology, and metabolic disorders, among others. TwinRCTs accelerate full enrollment by requiring fewer participants to achieve the same statistical power as traditional trial methods. This innovative strategy drastically cuts down on the time needed for late-stage study enrollment. Furthermore, TwinRCTs improve the detection of treatment effects in early-stage research by increasing statistical power without needing more participants. They allow researchers to make well-informed decisions based on initial findings and assist in attracting additional participants to clinical trials. By utilizing smaller control groups, TwinRCTs also enhance the likelihood of participants receiving the experimental treatment. Our dedication to ensuring that clinical trials with digital twins achieve regulatory approval remains steadfast. Unlearn is leading the charge in revolutionizing the healthcare industry through the pioneering use of artificial intelligence, crafting and applying cutting-edge generative models that utilize extensive datasets gathered from prior patient studies. This shift in methodology not only optimizes research efficiency but also significantly improves the effectiveness of clinical trials. The future of medicine is being reshaped as we continue to refine these innovative approaches.

What is CSAM Studies?

CSAM Studies, previously referred to as MedSciNet Studies, is a powerful and flexible online platform that has effectively facilitated the management of clinical research for the past twenty years. This internet-based resource for medical studies offers an extensive array of applications aimed at the hosting, administration, and supervision of projects of various sizes and complexities. CSAM MedSciNet's standard offerings encompass all critical components needed to launch a fully functional study or clinical trial. Moreover, this exemplary solution is enhanced with features that support dynamic and interactive data entry forms, customizable workflow designs, and advanced tools for data validation, analysis, and exportation. By utilizing these capabilities, researchers can adopt a thorough and efficient strategy for overseeing their clinical trials. As a result, CSAM Studies continues to evolve, meeting the changing demands of medical research with innovative solutions.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Unlearn

Company Location

United States

Company Website

www.unlearn.ai/

Company Facts

Organization Name

CSAM Health

Date Founded

2005

Company Location

Norway

Company Website

www.csamhealth.com/solutions/health-analytics/csam-studies/

Categories and Features

Clinical Trial Management

21 CFR Part 11 Compliance
Document Management
Electronic Data Capture
Enrollment Management
HIPAA Compliant
Monitoring
Patient Database
Recruiting Management
Scheduling
Study Planning

Categories and Features

Clinical Trial Management

21 CFR Part 11 Compliance
Document Management
Electronic Data Capture
Enrollment Management
HIPAA Compliant
Monitoring
Patient Database
Recruiting Management
Scheduling
Study Planning

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