This article reviews the present state of the art regarding the toxicokinetics and metabolism of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). The absorption, body distribution, and metabolism can vary greatly between species and also may depend on the congener and dose. In biota, the 2,3,7,8-substituted PCDDs and PCDFs are almost exclusively retained in all tissue types, preferably liver and fat. This selective tissue retention and bioaccumulation are caused by a reduced rate of biotransformation and subsequent elimination of congeners with chlorine substitution at the 2,3,7, and 8 positions. 2,3,7,8-Substituted PCDDs and PCDFs also have the greatest toxic and biological activity and affinity for the cytosolic arylhydrocarbon (Ah)-receptor protein. The parent compound is the causal agent for Ah-receptor-mediated toxic and biological effects, with metabolism and subsequent elimination of 2,3,7,8- substituted congeners representing a detoxification process. Congener-specific affinity of PCDDs and PCDFs for the Ah-receptor, the genetic events following receptor binding, and toxicokinetics are factors that contribute to the relative in vivo potency of an individual PCDD or PCDF in a given species. Limited human data indicate that marked species differences exist in the toxicokinetics of these compounds. Thus, human risk assessment for PCDDs and PCDFs needs to consider species-, congener-, and dose-specific toxicokinetic data. In addition, exposure to complex mixtures, including PCBs, has the potential to alter the toxicokinetics of individual compounds. These alterations in toxicokinetics may be involved in some of the nonadditive toxic or biological effects that are observed after exposure to mixtures of PCDDs or PCDFs with PCBs.

Mechanism-based PK-PD models differ from conventional PK-PD models in that they contain specific expressions to characterize, in a quantitative manner, processes on the causal path between drug administration and effect. This includes target site distribution, target binding and activation, pharmacodynamic interactions, transduction, and homeostatic feedback mechanisms. As the final step, the effects on disease processes and disease progression are considered. Particularly through the incorporation of concepts from receptor theory and dynamical systems analysis, important progress has been made in the field of mechanism-based PK-PD modeling. This has yielded models with much-improved properties for extrapolation and prediction. These models constitute a theoretical basis for rational drug discovery and development.

AimsIt is well established that there is a wide intra-and interindividual variability in dose requirements for lorazepam and midazolam in intensive care patients. The objective of this study was to compare the population pharmacokinetics of lorazepam and midazolam after long-term continuous infusion in mechanically ventilated critically ill patients. MethodsForty-nine critically ill patients randomly received either lorazepam (n = 28) or midazolam (n = 21) by continuous infusion for at least 24 h. Multiple blood samples were obtained for determination of the drug and metabolite concentrations by H PLC. Population pharmacokinetic models were developed using the Non-Linear Mixed Effect Modelling (NONMEM) program. The influence of selected covariates was investigated. The prospective performance of the models was evaluated on the basis of results in separate groups of patients for lorazepam (n = 31) and midazolam (n = 33).

AIMSMany physiological changes take place during pregnancy and labour. These might change the pharmacokinetics of amoxicillin, necessitating adjustment of the dose for prevention of neonatal infections. We investigated the influence of labour on the pharmacokinetics of amoxicillin. METHODSPregnant women before and during labour were recruited and treated with amoxicillin intravenously. A postpartum dose was offered. Blood samples were obtained and amoxicillin concentrations were determined using high-pressure liquid chromatography. The pharmacokinetics were characterized by nonlinear mixed-effects modelling using NONMEM. RESULTSThe pharmacokinetics of amoxicillin in 34 patients was best described by a three-compartment model. Moderate interindividual variability was identified in CL, central and peripheral volumes of distribution. The volume of distribution (V) increased with an increasing amount of oedema. Labour influenced the parameter estimate of peripheral volume of distribution (V2). V2 was decreased during labour, and even more in the immediate postpartum period. For all patients the population estimates (mean Ϯ SE) for CL and V were 21.1 Ϯ 4.1 l h -1 (CL), 8.7 Ϯ 6.6 l (V1), 11.8 Ϯ 7.7 l (V2) and 20.5 Ϯ 15.4 l (V3) respectively. CONCLUSIONSThe peripheral distribution volume of amoxicillin in pregnant women during labour and immediately postpartum is decreased. However, these changes are not clinically relevant and do not warrant deviations from the recommended dosing regimen for amoxicillin during labour in healthy pregnant patients.

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Bioconcentration is generally assumed to be similar to the partitioning of compounds between an aqueous and lipoid phase. In the case of bioconcentration lipoid phase is thought to consist of the lipid and lipoid tissues of an organism, e.g. a fish. However, it is frequently observed that for highly lipophilic compounds, defined as compounds with a high octanol−water partition coefficient, or log K ow, that simple view seems to break down. At low and intermediate log K ow there seems to be a linear relationship between bioconcentration, expressed as log BCF, and log K ow. At high log K ow deviations are seen, generally indicating that for these compounds BCF increases less than proportionally with increasing log K ow. Many different explanations and accompanying correlation models have been proposed to date. We present here a model that is capable of explaining the different shapes of the BCF/K ow relationships empirically observed, based on the effect of the presence of tiny amounts of different types of organic material in the aqueous phase. The actual shape of the nonlinear curve simply depends on the amount of organic material in the water, the difference in “affinity” for hydrophobic compounds of the organic material in water and lipid in fish, and to a lesser extent the amount of lipid in fish. The model presented also fits a large dataset of experimental BCF values with fitted parameter values that are consistent with the biology and physical chemistry of the described system.

The population pharmacodynamic model shows a similarly wide intra- and inter-individual variability in the pharmacodynamics of both lorazepam and midazolam. Thus, the previously observed differences in "ease of titration" between lorazepam and midazolam are unrelated to pharmacodynamic factors.

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