Application of the queueing theory with Monte Carlo simulation to inhalation toxicology.
Various models have been developed in modelling of inhalation toxicology. The deterministic approach, which has been used to date in most of the models, needs to consider numerous factors, e.g. anatomical structure, breathing frequency, humidity, metabolism rate, partition coefficients, pulmonary ventilation, perfusion rates, unidirectional/cyclic air flow, non-steady-state, steady-state, etc. In the present study, a stochastic approach was used in the modelling of inhalation toxicology, because there is a phenomenological analogy between the queueing system and respiratory system dealing with inhaled toxicants. Using the queueing theory, the amounts of toxicants in the respiratory system, the time needed to remove the accumulated amounts of toxicants from the respiratory system, etc. can be estimated. The Monte Carlo simulation of queueing process was performed to analyse cigarette smoking, and shows the potential use of the queueing theory in inhalation toxicology.
Wu
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Department of Clinical Pharmacology, Faculty of Medicine, Russian State Medical University, Moscow.
D000280:Administration, Inhalation; D003198:Computer Simulation; D009010:Monte Carlo Method; D012907:Smoking / Q000009:adverse effects*; D013269:Stochastic Processes; D013598:Systems Theory; D018675:Toxicity Tests