Next generation toolbox for greener pharmaceuticals design & manufacturing towards reduced environmental impact

ended

Pharmaceuticals have undoubtably made our world a better place, ensuring longer and healthier lives. However, pharmaceuticals and their active metabolites are rapidly emerging environmental toxicants. It is thus critical that we fully understand, and mitigate where nec-essary, the environmental impact resulting from their production, use and disposal. In this direction, ENVIROMED addresses two aspects of the environmental impact of pharmaceuticals, a) impact of the processes in manufacturing the compound, and b) impact of the compound itself, during its lifecycle. The project narrows the knowledge gap when it comes to the effect of pharmaceutical compounds, and their derivatives, in the environment as it enables the better understanding the environmental impact of such compounds, throughout their lifecycle. It aims to offer (via extensive monitoring campaigns & scientific studies) information regarding occurrence of pharmaceuticals in the environment, their persistence, environmental fate, and toxicity (via in-vitro & in-vivo models) as well as application of in-silico methods to provide information about the basic risk management and fate prediction in the environment. Brief ideas about toxicity endpoints, available ecotoxicity databases, and expert systems employed for rapid toxicity predictions of ecotoxicity of pharmaceuticals will also be taken into account, in order to have a comprehensive approach to pharmaceuticals' Lifecycle Assessment (LCA). Moreover, the project aims at developing a set of technologies that enable greener and overall, more efficient pharmaceuticals production, which include: a) Green-by-design in-silico drug development; b) Novel sensing to allow reduction of rinsing chemicals and cycles; c) a robust Continuous Biomanufacturing line (CBM), which makes use of AI-enabled process optimisation and prediction, using data assimilation based on chemical sensing and energy disaggregation/monitoring. Training activities and a robust exploitation