Synthetic Data–Driven Early Prediction Framework for Acute Kidney Injury in Patients Receiving Vancomycin and Ceftazidime/Avibactam

This study introduces a novel approach that integrates IPTW with synthetic data generation to evaluate drug-associated AKI risk in small-sample cohorts. Although our findings demonstrate a lower incidence of de novo AKI in the VAN-AVI group, the use of synthetic data and augmented ML models significantly improved early AKI prediction. These findings support the potential utility of synthetic data frameworks for scalable drug safety evaluations, although further validation is warranted.