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Description
VIPER streamlines the process of screening by automating remote patient identification right at the diagnosis stage and ensuring qualified enrollment. By leveraging artificial intelligence, VIPER efficiently matches patients to precision trials during a critical enrollment period by utilizing lab-agnostic genomic data, electronic medical records (EMR), and pathology information tailored to both the patient and the research requirements. The system employs a specialized matching engine that searches for the most suitable clinical trials corresponding to a patient's specific diagnosis at the moment they receive it. Additionally, through seamless workflow integration, VIPER provides real-time alerts regarding a patient’s eligibility for available trials, ensuring the entire care team is informed during this narrow enrollment timeframe. Furthermore, VIPER features interactive dashboards that offer extensive data mining capabilities, allowing for the aggregation of site and study-level patient data to effectively meet study key performance indicators (KPIs). This comprehensive approach not only enhances trial recruitment efficiency but also supports researchers in achieving their goals more effectively.
Description
Progressing artificial intelligence to remove the need for trial and error in healthcare, our digital twins facilitate swift and assured clinical trials. We focus on areas such as neuroscience, immunology, and metabolic diseases, among others. TwinRCTs expedite full enrollment by requiring fewer participants to provide equivalent statistical power compared to conventional trial methodologies. This approach significantly reduces the time needed for late-stage study enrollment. Additionally, TwinRCTs enhance the ability to detect treatment effects in early-stage studies by bolstering statistical power without necessitating an increase in participant numbers. They enable researchers to make informed decisions based on initial study outcomes and help attract more participants to trials. By utilizing smaller control groups, TwinRCTs also improve participants' odds of receiving the experimental treatment. Our commitment to positioning clinical trials with digital twins for regulatory success is unwavering. Unlearn is at the forefront of transforming the medical field through the innovative application of artificial intelligence, creating and implementing novel generative models that are trained on vast datasets derived from previous patient studies. This evolution in methodology not only streamlines research but also enhances the overall effectiveness of clinical trials.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Deep Lens
Founded
2017
Country
United States
Website
www.deeplens.ai/deep-lens-healthcare-providers
Vendor Details
Company Name
Unlearn
Country
United States
Website
www.unlearn.ai/
Product 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
Product 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
