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Updated: Dec 27, 2025

The Motivation for Alcohol Reward: Predictors of Progressive-Ratio Intravenous Alcohol Self-Administration in Humans
Published on: April 28, 2022
Forensic science meets clinical pharmacology: pharmacokinetic model based estimation of alcohol concentration of a
Hyeong-Seok Lim1, Jea Hyen Soung2, Kyun-Seop Bae1
1Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, Ulsan University College of Medicine, Seoul 05505, Republic of Korea.
Abstract:
Drunk driving is a serious social problem. We estimated the blood alcohol concentration of a defendant on the request of local prosecutor's office in Korea. Based on the defendant's history, and a previously constructed pharmacokinetic model for alcohol, we estimated the possible alcohol concentration over time during his driving using a Bayesian method implemented in NONMEM®. To ensure generalizability and to take the parameter uncertainty of the alcohol pharmacokinetic models into account, a non-parametric bootstrap with 1,000 replicates was applied to the Bayesian estimations. The current analysis enabled the prediction of the defendant's possible blood alcohol concentrations over time with a 95% prediction interval. The results showed a high probability that the alcohol concentration was ≥ 0.05% during driving. The current estimation of the alcohol concentration during driving by the Bayesian method could be used as scientific evidence during court trials.
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