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Updated: Jan 13, 2026

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Published on: January 31, 2014
Optimal design of dynamic experiments for scalar-on-function linear models with application to a biopharmaceutical
Damianos Michaelides1, Maria Adamou2, David C Woods2
1Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, 1683 Nicosia, Cyprus.
Abstract:
A Bayesian optimal experimental design framework is developed for experiments where settings of one or more variables, referred to as profile variables, can be functions. For this type of experiment, a design consists of combinations of functions for each run of the experiment. Within a scalar-on-function linear model, profile variables are represented through basis expansions. This allows finite-dimensional representation of the profile variables and optimal designs to be found. The approach enables control over the complexity of the profile variables and model. The method is illustrated on a real application involving dynamic feeding strategies in an Ambr250 modular bioreactor system.
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