Imagine if we could design medicine that breaks down naturally in water instead of lingering in the environment. This work uses AI to predict which chemical structures are 'earth-friendly' and finds faster, cleaner ways to make them in a continuous stream rather than in slow batches. It's like switching from a slow home-cook method to a high-tech automated assembly line for medicine.
European pharmaceutical companies rely heavily on third-country API production and struggle with high environmental footprints and non-biodegradable waste in water systems.
Four digital toolboxes containing AI predictive tools for molecule biodegradability and guidelines for continuous flow synthesis.
If you are an API producer dealing with high waste and reliance on non-EU suppliers — this project developed digital toolboxes that optimize synthesis routes in continuous flow to reduce the environmental footprint.
If you are a water treatment company dealing with pharmaceutical residues in surface water — this project developed predictive AI tools to identify and create biodegradable compounds that degrade more completely.
If you are a biotech startup dealing with expensive trial-and-error in molecule design — this project developed AI methods to predict solubility and biodegradability before physical production begins.
Based on available project data, the project focuses on reducing the footprint of synthesis and creating shortcuts in synthetic schemes, which typically lowers resource expenditure, though specific price reductions are not listed.
Yes, the project specifically focuses on continuous flow and telescoped methods, which are designed for industrial efficiency and higher productivity compared to batch processing.
Based on available project data, the project delivers four toolboxes consisting of digital tools and guidelines, but the specific licensing terms are not provided.
The project develops a Life Cycle Assessment and predicts biodegradability to ensure pharmaceuticals meet stricter water quality and environmental standards.
The project period runs from 2022-06-01 to 2026-05-31, suggesting that final tools will be ready by mid-2026.
The project features a strong industrial base with a 33% industry ratio, including 4 SMEs. With 12 partners across 9 countries, the group balances academic research (5 universities, 3 research centers) with commercial application, ensuring the resulting AI tools and flow-chemistry methods are grounded in market reality.
Contact Universiteit Gent regarding the four digital toolboxes for green API production.
Contact us to identify which of the 4 TransPharm toolboxes fits your production line.
