Get valid data to your decision makers.

Flaskdata.io gets interpretable data directly to the decision makers in your clinical trials.

From patients at home to the CEO, the stakeholders in your clinical trials get an immediate picture.

This immediate picture enables executive leadership to take decisions in a timely fashion - whether to expand a trial, to kill a project or to amend the study protocol to reduce protocol violations.

Valid and relevant feedback helps patients stay on track with the protocol and helps clinops team sustain high levels of protocol compliance.

The flaskdata.io platform achieves all this with a 3 part cloud-native API architecture:
Collect, Detect and Act.

For an overview of the Flask API see Flask API.

For a clinops perspective see Flask API for clinical operations.

For a developers perspective see Flask API Developer program.

For a researcher perspective see Flask API for clinical research.

For an overview of Flask Alerts and Analytics see Flask Alerts and Analytics

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Patients

Flask for Patients

Flask for Patients is a mobile ePRO application that runs on Android devices and Windows, MacOS desktops.  You can create an app for your patients in minutes using a friendly drag and drop UI.

Devices

Flask  Device API

Flask API is a powerful secure mobile/device API service that enables you to collect data from mobile medical devices, and connected medical devices at home or worn by the subject.

Collect

Flask Collect

Perhaps the biggest challenge for connected devices, decentralized trials and digital therapeutics is having a robust capability to digitally ingest data from a wide variety of sources.

Flask API ingests data at 100K events/second from any or all data sources in your digital study; investigators, devices and patients.

 

Detect and respond

Flask Detect & Respond

Detect & Respond processes the continuous data feed to provide an immediate picture of protocol compliance in your trial.

You can use any trial model – decentralized trials, site-centric or virtual analysis of real-world data.

Automated detection and response enables you to define your own metrics and automate a playbook response when metrics go over threshold.

Decision makers can subscribe to receive alerts.

Automated playbooks can provide adaptive reinforcement messages  or call a Web hook.