Michaelis–Menten pharmacokinetics based on uncertain differential equations

• Published in: Journal of ambient intelligence and humanized computing Vol. 14; no. 8; pp. 10403 - 10415
• Main Authors: Liu, Zhe, Kang, Rui
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2023; Springer Nature B.V
• Subjects: Artificial Intelligence; Brownian motion; Computational Intelligence; Data analysis; Differential equations; Engineering; Enzymes; Epistemology; Ethanol; Expected values; Integral equations; Metabolism; Ordinary differential equations; Original Research; Parameter uncertainty; Pharmacokinetics; Pharmacology; Random variables; Robotics and Automation; Stochastic models; User Interfaces and Human Computer Interaction; Michaelis–Menten kinetics; Generalized moment estimation; Pharmacokinetics; Uncertain differential equation

Michaelis–Menten kinetics are commonly used to represent enzyme-catalysed reactions in pharmacokinetics. Obviously, metabolizing organs and tissues are subject to various internal and external noises that change over time. However, both deterministic and stochastic modelling approaches can not accou...