Imagine shrinking a human organ's functions onto a tiny plastic chip to test how a new medicine works without needing animals or people. It's like a high-tech flight simulator for drugs, using AI and sensors to predict reactions accurately. This allows scientists to see if a treatment is safe for specific groups, like children or women, before it ever reaches a patient.
Drug development relies on animal models that often fail in humans, leading to 197,000 EU deaths annually from adverse reactions and €79 billion in societal costs.
The project is building ECS-based hardware and software, including a data acquisition system for micropumps and microfluidic instrument modules.
If you are a drug discovery firm dealing with high failure rates in clinical trials—this project developed ECS-based hardware and software tools that simulate human organ responses. This can lead to cost reductions of up to $169M and $706M per new drug reaching the market.
If you are a beauty product manufacturer dealing with ethical bans on animal testing—this project developed OOC-models that replace animal tests. This allows for the creation of cosmetics without animal testing while maintaining safety standards.
If you are a personalized medicine provider dealing with the lack of patient-specific testing—this project developed AI-assisted multi-sensor systems. This enables the creation of personalized medicine models to gain new insights into specific disease mechanisms.
Based on available project data, these solutions can result in cost reductions of up to $169M and $706M per new drug reaching the market.
Yes, the project specifically aims for parallelized test set-ups to meet efficient high-throughput demands and standardized procedures for reliable results.
Based on available project data, the project develops embedded software and AI-assisted algorithms, but specific licensing terms are not provided.
The project aims to create new release procedures and tools for releasing chemicals and drugs by reducing reliance on animal testing.
The project period runs from 2024-05-01 to 2027-04-30, indicating the tools are currently in development and validation.
The consortium is heavily industry-driven with 29 industrial partners (55% ratio), including 23 SMEs. This strong commercial presence, combined with 10 universities and 14 research centers across 10 countries, suggests a high focus on commercial viability and industrial application rather than purely academic research.
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