Monte Carlo Simulation of an Ethanol Pharmacokinetic Model

Background One challenge of using even relatively simple pharmacokinetic models is valuation of model parameters. Unknown model parameter values can be determined by fitting the model to measured data. Goals of the present study were to (1) obtain ethanol pharmacokinetic data from a cohort of dogs, (2) propose a physiologic ethanol pharmacokinetic model, (3) and perform Monte Carlo simulation to determine model parameter values. The rationale for the particular model proposed here was to account for the interrelationship between blood ethanol concentration and gastrointestinal physiology.Methods To each of five fasted dogs, 1 g of ethanol/kg body weight was administered as a gavage of 20% w/v ethanol solution. Developed was an ethanol pharmacokinetic model that comprised a gastric emptying mechanism, a body water compartment, ethanol diffusion through the stomach mucosa, gastric alcohol dehydrogenase (GADH) oxidation of ethanol, diffusion through the small intestine epithelia to the villi, a countercurrent exchanger model of the villi, and liver alcohol dehydrogenase oxidation of ethanol. Monte Carlo simulation was used to estimate model parameter values and standard deviations by minimization of the χ2 function.Results Fitting the experimental data to the model using Monte Carlo simulation yielded reasonable values for model parameters. The model predicted that the capacity for ethanol absorption in the intestine was 6.79‐fold greater than the ethanol absorption capacity in the stomach. The model indicated that 23.8 ± 8.3% of the ethanol dose was actually absorbed in the stomach, and an insignificant amount of ethanol was metabolized by GADH.Conclusions Ethanol metabolism by GADH is insignificant in the present case. The blood ethanol profile was strongly determined by gastric emptying. Differences between experimental data and simulation results largely result from the gastric emptying model selected. Therefore, accuracy of the complete pharmacokinetic model can be improved significantly by improving the gastric emptying model.