Data-driven medicine with Insaas.ai

Insaas.ai harnesses patient feedback for faster and better treatments and a healthier society

The goals

Today, physicians rely on their judgment without using real-time data. With Insaas.ai, physicians and patients benefit from targeted, data-driven analytics

Collection of high quality data from patients
Findings for specific disease patterns and patient groups
Prediction of side effects for personalized medicines and therapies

Our approach

Insaas.ai analyzes large volumes of written communication to predict the QALY (quality-adjusted life year)

High volume data analysis (GDPR compliant)
Summary of texts from different sources and enrichment
Dashboard and API to enable personalization of therapies

The result

Sustained gain of knowledge on the topic of “Patients Reported Outcome”

Free-form text contains valuable insights into the patient's condition
Patient feedback can be analyzed and evaluated over time
Side effects and well-being of patients can be transparently tracked
Specific side effects can be predicted for patient groups
QALY and Patient Reported Outcome become transparent and measurable

Feedback from our customer

In collaboration with LMU München, over 30,000 patient opinions on colon cancer were evaluated and presented in a dashboard.

It could be shown that the fatigue syndrome is the most common side effect for patients and is perceived as particularly severe compared to pain and weight loss.

"With this method it is possible to "lift a treasure" that is documented in patient forums and could not be systematically processed so far. Similar to a phase IV study, various patient statements on side effects of the drugs are documented and evaluated. This method thus makes it possible to identify very quickly, for example, (side) effects of drugs and interventions that have not yet been shown in phase III trials."
Prof. Michael Schoenberg
Rotkreuzklinikum München

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