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Understanding Photodecarboxylation dynamics of Anti-INflamatory drugs (UnPAIN)

Cel

Non-steroidal anti-inflammatory drugs (NSAIDs) are typically used to reduce inflammation, pain, and fever. However, under UV light, NSAIDs can undergo photochemical reactions in wasterwater, generating toxic radicals that threaten aquatic life and human health. UnPAIN arises as a solution to both understand and avoid this social problem. Previous spectroscopic studies have yielded inconsistent results regarding the mechanism, hindering rational design. UnPAIN will provide time-resolved chemical information to answer some fundamental questions such as the difference in photostability, considering both structural and environmental factors, bringing together advanced quantum chemical methods and computational simulations in the excited state for some representative NSAIDs such as ketoprofen, tiaprofenic acid, suprofen, naproxen and ibuprofen. This challenge includes dealing with multiple electronic states, internal conversion, intersystem crossing, and accurately describing anionic systems and solvents. The knowledge gained from this research could lead to safer drug designs and more stable formulations. Simultaneously, UnPAIN is designed to establish a robust protocol for studying in a general way photodissociative processes, which will be extremely useful for the scientific community. The experienced researcher will share knowledge on non-covalent interactions, and reaction mechanisms to the host group, while acquiring expertise in emerging quantum chemical methods and time-resolved chemical phenomena. UnPAIN will equip the applicant with the foundation needed to pursue an independent career, fostering a unique and highly competitive research profile. Additionally, it will offer excellent training, an enhanced scientific network, and a comprehensive set of essential soft skills, including communication, management, dissemination, and public engagement.

Koordynator

UNIVERSITAT WIEN
Wkład UE netto
€ 214 344,72
Koszt całkowity
Brak danych