Clin Pharmacokinet
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Fentanyl was structurally designed by Paul Janssen in the early 1960s as a potent opioid analgesic (100-fold more potent than morphine). It is a full agonist at μ-opioid receptors and possesses physicochemical properties, in particular a high lipophilicity (octanol:water partition coefficient >700), which allow it to cross quickly between plasma and central nervous target sites (transfer half-life of 4.7-6.6 min). It undergoes first-pass metabolism via cytochrome P450 3A (bioavailability ~30 % after rapid swallowing), which can be circumvented by non-intravenous formulations (bioavailability 50-90 % for oral transmucosal or intranasal formulations). ⋯ Thanks to the development of non-intravenous pharmaceutical formulations, fentanyl has become one of the most successful opioid analgesics, and can be regarded as an example of a successful reformulation strategy of an existing drug based on pharmacokinetic research and pharmaceutical technology. This development broadened the indications for fentanyl beyond the initial restriction to intra- or perioperative clinical uses. The clinical utility of fentanyl could be expanded further by more comprehensive mathematical characterizations of its parametric pharmacokinetic input functions as a basis for the rational selection of fentanyl formulations for individualized pain therapy.
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Since 2007, it is mandatory for the pharmaceutical companies to submit a Paediatric Investigation Plan to the Paediatric Committee at the European Medicines Agency for any drug in development in adults, and it often leads to the need to conduct a pharmacokinetic study in children. Pharmacokinetic studies in children raise ethical and methodological issues. Because of limitation of sampling times, appropriate methods, such as the population approach, are necessary for analysis of the pharmacokinetic data. The choice of the pharmacokinetic sampling design has an important impact on the precision of population parameter estimates. Approaches for design evaluation and optimization based on the evaluation of the Fisher information matrix (M(F)) have been proposed and are now implemented in several software packages, such as PFIM in R. ⋯ PFIM was a useful tool to find an optimal sampling design in children, considering clinical constraints. Even if it was not forecasted initially by the investigators, this approach showed that it was really necessary to include a late sampling time for all children. Moreover, we described an approach to evaluate designs assuming expected proportions of BLQ data are omitted.