Abstract
Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models.
Highlights
Global initiatives such as the IUPS Physiome project [1,2] and the Virtual Physiological Human (VPH) project [3,4] aim to quantitatively understand human physiology at all levels from gene to organism through the use of mathematical modelling
We present a sensitivity analysis of the 1992 version of the Guyton model [24,30,37], with a focus on the multiple interactions involved in blood pressure regulation
The results suggest that perturbations typically exert larger effects on urine production than on mean arterial pressure and cardiac output, since at all times shown in Figure 2b the elementary effects on VUD are much larger than the effects on MAP and QAO at any time
Summary
Global initiatives such as the IUPS Physiome project [1,2] and the Virtual Physiological Human (VPH) project [3,4] aim to quantitatively understand human physiology at all levels from gene to organism through the use of mathematical modelling. Mathematical models are appropriate tools for developing our understanding of human physiology, since they can be used to represent and analyse the combinatorial number of interactions between parameters in a rigorous and systematic manner [6]. Gaining a real quantitative understanding of the phenotypic variation in humans as a function of genes and environment in a mechanistic sense E., understanding the genotype-phenotype map in both the explanatory and predictive sense [8,9,10]) is a tremendous challenge that awaits technological, conceptual and methodological breakthroughs [11] Gaining a real quantitative understanding of the phenotypic variation in humans as a function of genes and environment in a mechanistic sense (i. e., understanding the genotype-phenotype map in both the explanatory and predictive sense [8,9,10]) is a tremendous challenge that awaits technological, conceptual and methodological breakthroughs [11]
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