Guidelines for the design of (optimal) isothermal inactivation experiments. (December 2019) - Peñalver-Soto, Jose Lucas; Garre, Alberto; Esnoz, Arturo; Fernández, Pablo S.; Egea, Jose A.
Graphical abstract: Highlights: We develop a methodology for OED of isothermal inactivation. The OED considers a two-dimensional design space and the detection limit. The optimal designs calculate more precise parameter than uniform designs. An intermediate reference temperature increases the precision of parameter estimates. We provide guidelines that combine results from OED and experimental limitations. Abstract: Kinetic models are nowadays a basic tool to ensure food safety. Most models used in predictive microbiology have model parameters, whose precision is crucial to provide meaningful predictions. Kinetic parameters are usually estimated based on experimental data, where the experimental design can have a great impact on the precision of the estimates. In this sense, Optimal Experiment Design (OED) applies tools from optimization and information theory to identify the most informative experiment under a set of constrains (e.g. mathematical model, number of samples, etc). In this work, we develop a methodology for the design of optimal isothermal inactivation experiments. We consider the two dimensions of the design space (time and temperature), as well as a temperature-dependent maximum duration of the experiment. Functions for its application have been included in the bioOED R package. We identify design patterns that remain optimum regardless of the number of sampling points for three inactivation models (Bigelow, Mafart and Peleg) and three model microorganisms ( Escherichia coli, Salmonella Senftenberg and Bacillus coagulans ). Samples at extreme temperatures and close to the maximum duration of the experiment are the most informative. Moreover, the Mafart and Peleg models require some samples at intermediate time points due to the non-linearity of the survivor curve. The impact of the reference temperature on the precision of the parameter estimates is also analysed. Based on numerical simulations we recommend fixing it to the mean of the maximum and minimum temperatures used for the experiments. The article ends with a discussion presenting guidelines for the design of isothermal inactivation experiments. They combine these optimum results based on information theory with several practical limitations related to isothermal inactivation experiments. The application of these guidelines would reduce the experimental burden required to characterize thermal inactivation.