A method for increasing process performance in a biological process comprising at least one process step, the method comprising: (a) an identification phase, in which at least seven factors are identified by a user selection and/or automatically selected by a processor, wherein a factor is defined as a feature of or within a process that when modified will affect the performance of the process, and wherein the factors are selected from at least two process factors and at least two genetic factors, wherein process factors are selected from a group comprising of features of the equipment, environment, protocol, reagents, handling of cells and process design, and genetic factors are qualitative and quantitative features associated with any genetic material involved in the process; (b) a factor screening phase, in which individual and combined contributions to process performance of each of the at least seven factors as described in (a) are determined by a laboratory automation apparatus and a processor controlling the laboratory automation apparatus to acquire experimental data using a fractional factorial design of experiments, wherein the experimental data is used by the processor to define the factors of most importance for further investigation and identify the presence of multifactorial interactions by estimating at least some of the coefficients of a first order polynomial model of the performance of the process as a function of the at least seven factors, the model comprising a term for each single factor and a term for each two factor and three factor interaction between the at least seven factors; and (c) a refinement phase, in which interactions that result in an increase in process performance between the at least seven factors are identified and tested by the processor controlling a laboratory automation apparatus to perform further experiments to acquire better parameter estimates for the interactions that were determined in the screening phase to result in an increase in process performance. (a) an identification phase, in which at least seven factors are identified by a user selection and/or automatically selected by a processor, wherein a factor is defined as a feature of or within a process that when modified will affect the performance of the process, and wherein the factors are selected from at least two process factors and at least two genetic factors, wherein process factors are selected from a group comprising of features of the equipment, environment, protocol, reagents, handling of cells and process design, and genetic factors are qualitative and quantitative features associated with any genetic material involved in the process; (b) a factor screening phase, in which individual and combined contributions to process performance of each of the at least seven factors as described in (a) are determined by a laboratory automation apparatus and a processor controlling the laboratory automation apparatus to acquire experimental data using a fractional factorial design of experiments, wherein the experimental data is used by the processor to define the factors of most importance for further investigation and identify the presence of multifactorial interactions by estimating at least some of the coefficients of a first order polynomial model of the performance of the process as a function of the at least seven factors, the model comprising a term for each single factor and a term for each two factor and three factor interaction between the at least seven factors; and (c) a refinement phase, in which interactions that result in an increase in process performance between the at least seven factors are identified and tested by the processor controlling a laboratory automation apparatus to perform further experiments to acquire better parameter estimates for the interactions that were determined in the screening phase to result in an increase in process performance. <EOS>