Imagine your body as a complex lock and medicines as keys. Sometimes, taking multiple keys at once or having a unique genetic lock makes the medicine behave unpredictably, leading to dangerous side effects. This project builds a smart digital assistant that predicts these clashes and helps patients and doctors adjust doses to keep people safe.
Patients taking multiple medications often suffer from adverse drug reactions due to complex interactions between drugs and their genes. These reactions lead to high hospitalization rates and death, while traditional clinical trials are too expensive to map every possible interaction.
An AI risk scoring system for adverse drug reactions, a digital Medication Management Center (MMC) for patients, and a web-based dose adaptation decision support system.
If you are a health-tech app developer dealing with low patient adherence in elderly care — this project developed a digital Medication Management Center (MMC) that allows patients to manage therapies and learn about interactions. This increases user engagement and safety.
If you are a precision medicine firm dealing with the high cost of clinical trials for drug-drug-gene interactions — this project developed a risk scoring system using machine learning on real-world datasets. This allows for identifying at-risk patients without expensive combinatorial trials.
If you are a private clinic network dealing with high hospitalization rates due to adverse drug reactions — this project developed a web-based decision support system for individualized dose adaptations. This reduces medical errors and associated healthcare costs.
Based on available project data, no specific pricing or cost information is provided as the project is EU-funded.
The project uses machine learning on large real-world datasets and involves 14 partners across 6 countries, suggesting a design intended for broad European clinical application.
Based on available project data, specific licensing terms are not mentioned; however, the project is a Horizon-RIA research action.
The project developed a web-based decision support system and a digital Medication Management Center to provide tailored information to physicians and citizens.
The project period runs from 2022-06-01 to 2026-08-31, with current work focusing on model refinement and proof-of-principle studies.
The consortium is research-heavy with 8 universities and 2 research institutes, but maintains a 21% industry presence through 3 SMEs. This balance suggests a strong academic foundation in machine learning and pharmacology, supported by small-scale industrial agility for the digital tool development across 6 European countries.
Contact UNIVERSITAT DES SAARLANDES in Germany
Contact us to explore licensing the risk scoring AI or the MMC tool.
