This work presents a multivariate methodology combining principal component analysis, the Mahalanobis distance and decision trees for the selection of process factors and their levels in early process development of generic molecules. It is applied to a high throughput study testing more than 200 conditions for the production of a biosimilar monoclonal antibody at microliter scale. The methodology provides the most important selection criteria for the process design in order to improve product quality towards the quality attributes of the originator molecule. Robustness of the selections is ensured by cross-validation of each analysis step. The concluded selections are then successfully validated with an external data set. Finally, the results are compared to those obtained with a widely used software revealing similarities and clear advantages of the presented methodology. (c) 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:181-191, 2017