Forensic science meets clinical pharmacology: pharmacokinetic model based estimation of alcohol concentration of a defendant as requested by a local prosecutor's office
Translational and Clinical Pharmacology
;
: 5-9, 2017.
Artigo
em Inglês
| WPRIM
| ID: wpr-196854
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.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Farmacologia Clínica
/
Problemas Sociais
/
Teorema de Bayes
/
Incerteza
/
Ciências Forenses
/
Concentração Alcoólica no Sangue
/
Dirigir sob a Influência
/
Coreia (Geográfico)
Tipo de estudo:
Estudo prognóstico
País/Região como assunto:
Ásia
Idioma:
Inglês
Revista:
Translational and Clinical Pharmacology
Ano de publicação:
2017
Tipo de documento:
Artigo
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