European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
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Raclopride is a selective antagonist of the dopamine D2 receptor. It is one of the most frequently used in vivo D2 tracers (at low doses) for assessing drug-induced receptor occupancy (RO) in animals and humans. It is also commonly used as a pharmacological blocker (at high doses) to occupy the available D2 receptors and antagonize the action of dopamine or drugs on D2 in preclinical studies. The aims of this study were to comprehensively evaluate its pharmacokinetic (PK) profiles in different brain compartments and to establish a PK-RO model that could predict the brain distribution and RO of raclopride in the freely moving rat using a LC-MS based approach. ⋯ For the first time a predictive model that could describe the quantitative in vivo relationship between dose, PK and D2 RO of raclopride in non-anesthetized rat was established. The PK-RO model could facilitate the selection of optimal dose and dosing time when raclopride is used as tracer or as pharmacological blocker in various rat studies. The LC-MS based approach, which doses and quantifies a non-radiolabeled tracer, could be useful in evaluating the systemic disposition and brain kinetics of tracers.
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Remifentanil based anesthesia is nowadays spread worldwide. This drug is characterized by a rapid onset of the analgesic effects, but also by a rapid onset of the side effects. For this reason, the knowledge of the remifentanil concentration in the human body is a key topic in anesthesiology. ⋯ The pharmacodynamics, in terms of effect of remifentanil on minute ventilation and electroencephalogram, has been implemented in this model. Moreover, the remifentanil concentration in various organs and tissues is predicted, which is a significant improvement with respect to the traditional compartmental models. The availability of the model makes possible the prediction of the effects of remifentanil administration, also accounting for individual parameters.
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The discovery and development of a novel irreversible EGFR/HER2 dual tyrosine kinase inhibitor SHR1258 (pyrotinib) for the treatment of HER2-postive breast cancer is presented. The structure-activity relationship of lead series and their pharmacokinetic properties were evaluated to identify the potential candidates for further in vivo efficacy studies and preclinical safety assessments. ⋯ Overall, the potent and selective EGFR/HER2 dual inhibitor, pyrotinib, displayed robust anti-tumor effects on HER2-overexpressing xenograft models and sufficiently safety windows in animals as well as favorable pharmacokinetic properties in human, which substantially ensures current clinical development. Finally, recent advances of pyrotinib in clinical studies are highlighted with very encouraging outcomes in patients with HER2-postive advanced breast cancer.
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Pain is a complex biopsychosocial phenomenon of which the intensity, location and duration depends on various underlying components. Treatment of pain is associated with considerable inter-individual variability, and as such, requires a personalized approach. However, a priori prediction of optimal analgesic treatment for individual patients is still challenging. ⋯ Moreover, combination of QSP modelling with state-of-the-art metabolomics approaches may offer unique possibilities to identify novel pain biomarkers. Such biomarkers could support both the personalized treatment of pain and translational drug development of novel analgesic agents. In conclusion, a QSP approach will likely improve our ability to predict pain and treatment response, paving the way for personalized treatment of pain.
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In pharmacokinetic modelling, a combined proportional and additive residual error model is often preferred over a proportional or additive residual error model. Different approaches have been proposed, but a comparison between approaches is still lacking. ⋯ Both methods are valid approaches in combined proportional and additive residual error modelling, and selection may be based on OFV. When the result of an analysis is used for simulation purposes, it is essential that the simulation tool uses the same method as used during analysis.