Response surface methodology to determine optimal cytokine responses in human peripheral blood mononuclear cells after smallpox vaccination

Feasibility, amount of sample aliquots, processing time and cost are critical considerations for optimizing and conducting assays for large-population based studies. Well designed statistical approaches that quickly identify optimal conditions for a given assay could assist efficient completion of the laboratory assays for such studies. For example, assessment of the profile of secreted cytokines is important in understanding the immune response after vaccination. To characterize the cytokine immune response following smallpox vaccination, PBMC obtained from recently vaccinated subjects were stimulated with varying doses of live or UV-inactivated vaccinia virus and cultured for up to 8 days. In this paper, we describe a novel statistical method to identify optimal operating conditions for length in culture and virus MOI in order to measure a panel of secreted Th1, Th2, and inflammatory cytokines. This statistical method is comprised of two components. It first identifies a subset of the possible time in culture by virus MOI combinations to be studied. It then utilizes response surface analysis techniques to predict the optimal operating conditions for the measurement of each secreted cytokine. This method was applied, and the predicted optimal combinations of length in culture and virus MOI for maximum vaccinia-specific cytokine secretion were identified. The use of the response surface methodology can be applied to the optimization of other laboratory assays; especially when the number of PBMC available limits the testing of all possible combinations of parameters.