Ibuprofen biodegradation from pharmaceutical wastewater via optimization, kinetics, neuro-fuzzy modelling, and risk assessment study

The persistence of ibuprofen in pharmaceutical wastewater has become an emerging environmental concern because conventional wastewater treatment processes often fail to achieve its complete removal. This study investigated the isolation, identification, and biodegradation potential of indigenous bacterial strains from pharmaceutical wastewater, with an emphasis on optimizing ibuprofen degradation and evaluating microbial growth kinetics. The novelty of this study lies in the integration of microbial isolation, Response Surface Methodology (RSM), Adaptive Neuro-Fuzzy Inference System (ANFIS) modelling, kinetic modelling, and Monte Carlo uncertainty analysis to comprehensively evaluate ibuprofen biodegradation by Cytobacillus solani. Three bacterial isolates were recovered from the wastewater, among which Cytobacillus solani exhibited the highest biodegradation performance, achieving an apparent degradation of 58.59% with a doubling time of 51.34 h. The pharmaceutical wastewater contained an initial ibuprofen concentration of 41.71 mg L –1 . Numerical optimization using the Box–Behnken Design predicted a maximum degradation efficiency of 78%, which was subsequently validated experimentally under optimum conditions of pH 4, 36 °C, and an agitation speed of 194 rpm after 48 h, reducing the ibuprofen concentration to 9.18 mg L –1 . Although a substantial reduction in ibuprofen concentration was achieved, the analytical approach monitored only the disappearance of the parent compound and could not identify degradation intermediates or confirm complete mineralization. Therefore, future investigations should employ advanced analytical techniques such as LC–MS/MS and total organic carbon (TOC) analysis to elucidate degradation pathways and verify complete mineralization. The Box–Behnken Design and ANFIS models demonstrated good predictive capability, with coefficients of determination (R 2 ) of 0.9478 and 0.9999, respectively. Among the microbial kinetic models evaluated, the Monod model provided the best fit to the experimental data, yielding an R 2 value of 0.7823 and a maximum specific growth rate (μ max ) of 0.0370 h –1 . These findings demonstrate the potential of Cytobacillus solani for ibuprofen biodegradation and provide a useful framework for optimizing and predicting biological treatment processes for pharmaceutical wastewater.