Efficient and cost‐effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

Abstract

Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the e⁄ciency and cost-e¡ectiveness by reducing the necessary amount of experiments and data points measured.

Computational Biology Approaches to Plant Metabolism and Photosynthesis: Applications for Corals in Times of Climate Change and Environmental Stress

“…With all of the examples tested, the error decreases with an increasing number of replicates up to three as shown in Figure 1; increasing the numbers of replicates beyond three produces no improvement in the standard error of parameter estimation (Murphy et al 2003, 2004). As the number of measurements required is based on the number of model parameters to be fitted rather than the actual equation, it is possible to design and also differentiate through fitting between kinetic models with the same number of parameters.…”

“…It is clear that this method of Bayesian design and the rules are potentially applicable to other kinetic systems, particularly where it is important to have rapid but accurate and cost‐effective methods in clinical or industrial research. We have shown (Murphy et al 2004) here how four kinetic experiments for different systems can be markedly improved by designing using the rules. Definite improvements can be made by designed choices of features such as the concentration range, percentage distribution of points and the individual selection of points.…”

“…Data simulation was achieved using a program written into a Mathematica workbook. This generates experimental data for different designs so each set can be fitted and the results compared (Murphy et al 2003, 2004). All data were fitted using Simfit (http://www.simfit.man.ac.uk/).…”

“…Two different kinetic systems are compared: cell transport, and continuous culture. Modified from Murphy et al 2004.…”

Sequential model-based A- and V-optimal design of experiments for building fundamental models of pharmaceutical production processes

“…(1.6), requires an invertible FIM. However, for complex chemical and biochemical models with M A N U S C R I P T 9 many unknown parameters, the FIM may not be invertible (Barz et al, 2013;Ben-Zvi et al, 2004;Cui et al, 2015;Issanchou et al, 2003;Karimi et al, 2012;Kou et al, 2005a;Littlejohns et al, 2010;López C. et al, 2015;López C et al, 2013;Murphy et al, 2004;Nguyen et al, 2017;Thompson et al, 2010;Yue et al, 2006;Zhao et al, 2017). A singular FIM causes problems in both designing experiments and parameter estimation (S. .…”