Abstract
Dynamic modeling has played an important role in advancing and integrating the fields of pharmacokinetics and pharmacodynamics. However, the vast majority of models in the literature do not take into account the fact that pharmacological responses are frequently affected by the homeostatic mechanisms inherent in physiological control systems. This article provides a short tutorial presenting examples that illustrate the basic properties of closed-loop control and how these can influence model predictions of drug responses in both the steady-state and under dynamic conditions. Physiological control systems can be modeled using two basic approaches: (a) “minimal modeling”, in which all model parameters for individuals can be estimated from experiment; and (b) “structured modeling ”, in which the model parameters are isomorphic to key physiological entities, but not all can be identified from the measurements. A discussion of these two approaches is presented, along with a case study of how minimal modeling can be applied to extend a larger structured model. Finally, the importance of modeling functional linkages and interactions across organ systems and across scales is highlighted through a brief exposition of a recently developed structured model of cardiorespiratory, sleep-wake state and metabolic control .
Keywords
- Minimal modeling
- Structured modeling
- Sleep-wake state
- Metabolic control
- Homeostasis
- Open-loop system
- Closed-loop system
- Total peripheral resistance (TPR)
- Central sleep apnea (CSA)
- PNEUMA
- Cardiovascular control
- Hypothermia
- Windkessel model
- Baroreflex components
- Mechanical effect of respiration (MER)
- Mean arterial pressure (MAP)
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Khoo, M.C.K., Hu, WH., Chalacheva, P. (2016). Mechanistic Models of Physiological Control Systems. In: Mager, D., Kimko, H. (eds) Systems Pharmacology and Pharmacodynamics. AAPS Advances in the Pharmaceutical Sciences Series, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-44534-2_7
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