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2017 (v.25 no.1)

Translational and Clinical Pharmacology

Korean Society for Clinical Pharmacology and Therapeutics
Quarter
ISSN: 2289-0882

  • Forensic science meets clinical pharmacology: pharmacokinetic model based estimation of alcohol concentration of a defendant as requested by a local prosecutor’s office

    Hyeong-Seok Lim, Jea Hyen Soung, Kyun-Seop Bae

    TCP | v.25, no.1, pp.05-09, Mar, 2017

    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.

    Keyword

    Alcohol, Estimation, Defendant, NONMEM, Bayesian