OBJECTIVE: To explore the ability of the nonparametric expectation maximisation (NPEM) method of population pharmacokinetic modelling to deal with sparse data in estimating systemic caffeine clearance for monitoring and evaluation of cytochrome P450 (CYP) 1A2 activity. DESIGN AND PARTICIPANTS: Nonblind, single-dose clinical investigation in 34 non-related adult Bulgarian Caucasians (18 women and 16 men, aged between 18 and 62 years) with normal and reduced renal function. METHODS: Each participant received oral caffeine 3 mg/kg. Two blood samples per individual were taken according to the protocol for measuring caffeine plasma concentrations. A total of 67 measured concentrations were used to obtain NPEM estimates of caffeine clearance. Paraxanthine/caffeine plasma ratios were calculated and correlated with clearance estimates. Graphical methods and tests for normality were applied and parametric and nonparametric statistical tests were used for comparison. RESULTS: NPEM median estimates of caffeine absorption and elimination rate constants, k(a) = 4.54 h(-1) and k(el) = 0.139 h(-1), as well as of fractional volume of distribution and plasma clearance, V(S1) = 0.58 L/kg and CL(S1) = 0.057 L/h/kg, agreed well with reported values from more 'data rich' studies. Significant correlations were observed between paraxanthine/caffeine ratios at 3, 8 and 10 hours and clearance (Spearman rank correlation coefficients, r(s), >0.74, p </= 0.04). Sex or renal function caused no significant differences in clearance. Heavy smokers and drinkers showed 2-fold higher CYP1A2 activity. Normality tests and graphical methods of analysing caffeine clearance supported a non-Gaussian and multicomponent distribution of CYP1A2 activity. CONCLUSIONS: Collectively, the results show that the NPEM method is suitable and relevant for large-scale epidemiological studies of population phenotyping for cancer susceptibility and for abnormal liver function by monitoring CYP1A2 activity based on sparse caffeine data.
OBJECTIVE: To explore the ability of the nonparametric expectation maximisation (NPEM) method of population pharmacokinetic modelling to deal with sparse data in estimating systemic caffeine clearance for monitoring and evaluation of cytochrome P450 (CYP) 1A2 activity. DESIGN AND PARTICIPANTS: Nonblind, single-dose clinical investigation in 34 non-related adult Bulgarian Caucasians (18 women and 16 men, aged between 18 and 62 years) with normal and reduced renal function. METHODS: Each participant received oral caffeine 3 mg/kg. Two blood samples per individual were taken according to the protocol for measuring caffeine plasma concentrations. A total of 67 measured concentrations were used to obtain NPEM estimates of caffeine clearance. Paraxanthine/caffeine plasma ratios were calculated and correlated with clearance estimates. Graphical methods and tests for normality were applied and parametric and nonparametric statistical tests were used for comparison. RESULTS: NPEM median estimates of caffeine absorption and elimination rate constants, k(a) = 4.54 h(-1) and k(el) = 0.139 h(-1), as well as of fractional volume of distribution and plasma clearance, V(S1) = 0.58 L/kg and CL(S1) = 0.057 L/h/kg, agreed well with reported values from more 'data rich' studies. Significant correlations were observed between paraxanthine/caffeine ratios at 3, 8 and 10 hours and clearance (Spearman rank correlation coefficients, r(s), >0.74, p </= 0.04). Sex or renal function caused no significant differences in clearance. Heavy smokers and drinkers showed 2-fold higher CYP1A2 activity. Normality tests and graphical methods of analysing caffeine clearance supported a non-Gaussian and multicomponent distribution of CYP1A2 activity. CONCLUSIONS: Collectively, the results show that the NPEM method is suitable and relevant for large-scale epidemiological studies of population phenotyping for cancer susceptibility and for abnormal liver function by monitoring CYP1A2 activity based on sparse caffeine data.
Authors: Y C Bechtel; H Lelouët; S Hrusovsky; M P Brientini; G Mantion; G Paintaud; J P Miguet; P R Bechtel Journal: Int J Clin Pharmacol Ther Date: 2001-02 Impact factor: 1.366
Authors: A D Kashuba; J S Bertino; G L Kearns; J S Leeder; A W James; R Gotschall; A N Nafziger Journal: Clin Pharmacol Ther Date: 1998-05 Impact factor: 6.875