Pharmacokinetic model for extravascular administration based on uncertain differential equation

Pharmacokinetics studies the time course of drug concentration in body compartments, and one of the commonly used methods of administration is extravascular administration. Undoubtedly, biological systems are subject to various internal and external noises that change over time. To rationally deal w...

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Bibliographic Details
Published inJournal of ambient intelligence and humanized computing Vol. 14; no. 10; pp. 13887 - 13899
Main Authors Liu, Zhe, Kang, Rui
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2023
Springer Nature B.V
Subjects
Artificial Intelligence
Bioavailability
Computational Intelligence
Data analysis
Differential equations
Drugs
Engineering
Epistemology
Expected values
Medicine
Ordinary differential equations
Original Research
Parameter uncertainty
Pharmacokinetics
Pharmacology
Principles
Reliability
Robotics and Automation
System theory
Uncertainty principles
User Interfaces and Human Computer Interaction
Liu process
Extravascular administration
Belief reliability
Pharmacokinetics
Uncertain differential equation
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Summary:Pharmacokinetics studies the time course of drug concentration in body compartments, and one of the commonly used methods of administration is extravascular administration. Undoubtedly, biological systems are subject to various internal and external noises that change over time. To rationally deal with these dynamic noises, this paper deduces a pharmacokinetic model for extravascular administration using uncertain differential equations for the first time. Some essential pharmacokinetic indexes such as drug concentration, area under the curve, and maximum drug concentration are investigated. Based on the three basic principles of reliability science, i.e., margin-based reliable principle, eternal degradation principle and uncertainty principle, the belief reliability for drug is investigated. The minimum cover estimation for the set of unknown parameters in this uncertain pharmacokinetic model is provided. Numerical example and a real data analysis illustrate our method in detail. Finally, the paradox of a stochastic pharmacokinetic model is presented.
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content type line 14
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-022-04100-8