|Articles|June 29, 2020

snapIoT Announces AI-Powered Automated IRB Packaging and UAT Reporting for Patient Engagement Solutions

snapIoT Inc., a San Diego-based company, announces Automated AI-powered IRB Packaging and UAT Reporting feature to assemble all patient-facing visual assets and expedite the submission process for IRB and ethics approvals. Traditionally, this time-consuming process of IRB and ethics packaging is prone to human error and performed manually at the end of app development stages.

snapClinical™’s AI-powered Automated Documentation Engine creates key patient facing documentation assets for IRB Package setup and submission as well as UAT Reporting. With one single click, an AI-powered automation engine will: execute the app, go through all screens and generate screenshots, traverse all protocol flows and gather forms data information and auto-generate the needed materials within a single report. Annotations can be documented and exported to various file formats for further editing and processing. Pharma and CRO companies now have a faster, more efficient, and reliable method to help launch digitally enabled clinical trials.

“We have worked very closely with an early stage User Group comprised of many of the Top 10 Pharmaceutical and CRO companies as well as several IRB and Ethics SME’s to rapidly deploy this modern feature. Our Automated AI-powered IRB Packaging and UAT Reporting feature achieves the objectives of a better streamlined process to reduce time, costs and human error,” said Isaac Eteminan, CEO of snapIoT.

Related to this article

The Human Side of Clinical Trials: Why Fuzzy Mental Models Undermine Clinical Trial Execution
In Episode 3 of The Human Side of Clinical Trials, hosts Brian S. McGowan, PhD, FACEHP, chief learning officer and co-founder of ArcheMedX, Inc., and Kelly Ritch, chief operating officer of ArcheMedX, Inc., speak with Jason Riis, PhD, CEO and chief behavioral scientist at Behavioralize, about why a well-written protocol doesn’t always translate into consistent execution, and how designing for the way people actually think and learn can reduce site burden and the need for costly unlearning.