The responses of the ultrasound-mediated disruption of Pseudomonas putida KT2440 were modelled as the function of biomass concentration in the cell suspension; the treatment time of sonication; the duty cycle and the acoustic power of the sonicator. For the experimental data, the response surface (RSM), the artificial neural network (ANN) and the support vector machine (SVM) models were compared for their ability to predict the performance parameters. The satisfactory prediction of the unseen data of the responses implied the proficient generalization capabilities of ANN. The extent of the cell disruption was mainly dependent on the acoustic power and the biomass concentration. The cellmass concentration in the slurry most strongly influenced the ADI and total protein release. Nearly 28 U/mL ADI was released when a biomass concentration of 300 g/L was sonicated for 6 min with an acoustic power of 187.5W at 40% duty cycle. Cell disruption obeyed first-order kinetics. (C) 2017 Elsevier Ltd. All rights reserved.