CPMF2(1) Flemish Cluster Predictive Microbiology in Foods, BioTeC - Chemical and Biochemical Process Technology and Control, Department of Chemical Engineering, Katholieke Universiteit Leuven, W de Croylaan 46, B-3001 Leuven, Belgium.
J Theor Biol. 2010 May 21;264(2):347-55. doi: 10.1016/j.jtbi.2010.01.003. Epub 2010 Jan 11.
Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable.
最优实验设计用于参数估计 (OED/PE) 已成为一种高效、准确估计动力学模型参数的流行工具。当研究的动力学模型包含多个参数时，可以构建不同的优化策略。最直接的方法是从一个最优实验中同时估计所有参数（单 OED/PE 策略）。然而，由于优化问题的复杂性或系统动力学的严格限制，实验信息可能会受到限制，并且可能会出现参数估计收敛问题。作为替代方案，我们建议将优化问题简化为一系列双参数估计问题，即设计一个最优实验来组合两个参数，同时假定其他参数已知。可以遵循两种不同的方法：(i) 基于相同的初始参数估计设计所有双参数最优实验，并同时从所有得到的实验数据中估计参数（全局 OED/PE 策略），以及 (ii) 依次计算和实施最优实验，中间更新参数值（顺序 OED/PE 策略）。这项工作利用 OED/PE 来识别具有拐点的卡方温度模型 (CTMI)（Rosso 等人，1993 年）。这个动力学模型描述了温度对微生物生长速率的影响，包含四个参数。考虑了三种 OED/PE 策略，并评估了 OED/PE 设计策略对 CTMI 参数估计准确性的影响。基于模拟研究，观察到顺序方法得出的参数值与真实参数相比偏差更大，而单和全局策略估计则偏差更小。基于在生物反应器中实施设计获得的实验数据，进一步比较了单和全局 OED/PE 策略。得到了可比的估计，但全局 OED/PE 估计通常更准确和可靠。
