Model-based optimization techniques play a key role in achieving a sustainable operation of biochemical processes. Models are an approximation of the real process under study, hence, uncertainty is inherently present and for a sustainable process operation this uncertainty should be accounted for. In practice, optimality with respect to different conflicting objectives is required and multi-objective optimization is a valuable tool. In this article the sigma point approach is applied to account for parametric uncertainty in the frame of interactive multi-objective bioprocess optimization.