Adverse Drug Reactions

This study develops a multi-agent collaborative prediction model to forecast adverse drug reactions using real-world clinical medical records. It validates model performance via evidence-based data and compares decision outputs between the AI model and clinical physicians, aiming to improve early identification of drug adverse events. Only de-identified historical medical data will be analyzed; no new clinical interventions will be conducted, with no additional risks to participants.

Ofloxacin is a gold standard antibiotic for the treatment of bone and joint infections due to sensible staphylococcus strains. However, in the elderly, inter-individual variability of the pharmacokinetics may reduce the efficacy or increase toxicity. The occurrence of ofloxacin side effects is likely to be increased in case of higher exposition. However, the serum concentration-toxicity relationship has not yet been determined. The purpose of this project is to assess the association between the residual serum concentration of ofloxacin at day 3 and the occurrence of at least one adverse effect attributable to ofloxacin, and determine a threshold toxicity concentration if this association exists.