Predicting blood-brain barrier (BBB) permeability is essential to drug development, as a molecule cannot exhibit pharmacological activity within the brain parenchyma without first transiting this barrier. Understanding the process of permeation, however, is complicated by a combination of both limited passive diffusion and active transport. Our aim here was to establish predictive models for BBB drug permeation that include both active and passive transport. A database of 153 compounds was compiled using in vivo surface permeability product (logPS) values in rats as a quantitative parameter for BBB permeability. The open source Chemical Development Kit (CDK) was used to calculate physico-chemical properties and descriptors. Predictive computational models were implemented by machine learning paradigms (decision tree induction) on both descriptor sets. Models with a corrected classification rate (CCR) of 90% were established. Mechanistic insight into BBB transport was provided by an Ant Colony Optimization (ACO)-based binary classifier analysis to identify the most predictive chemical substructures. Decision trees revealed descriptors of lipophilicity (aLogP) and charge (polar surface area), which were also previously described in models of passive diffusion. However, measures of molecular geometry and connectivity were found to be related to an active drug transport component.

AIMSThe anthelminthic ivermectin is receiving new attention as it is being repurposed for new indications such as mass drug administrations for the treatment of scabies or in malaria vector control. As its pharmacokinetics are still poorly understood, we aimed to characterize the population pharmacokinetics of ivermectin in plasma and dried blood spots (DBS), a sampling method better suited to field trials, with special focus on the influence of body composition and enterohepatic circulation. METHODSWe performed a clinical trial in 12 healthy volunteers who each received a single oral dose of 12 mg ivermectin, and collected peripheral venous and capillary DBS samples. We determined ivermectin concentrations in plasma and DBS by liquid chromatography tandem mass spectrometry using a fully automated and scalable extraction system for DBS sample processing. Pharmacokinetic data were analysed using non-linear mixed effects modelling. RESULTSA two-compartment model with a transit absorption model, first-order elimination, and weight as an influential covariate on central volume of distribution and clearance best described the data. The model estimates (inter-individual variability) for a 70 kg subject were: apparent population clearance 7.7 (25%) l h À1 , and central and peripheral volumes of distribution 89 (10%) l and 234 (20%) l, respectively. Concentrations obtained from DBS samples were strongly linearly correlated (R 2 = 0.97) with plasma concentrations, and on average 30% lower. CONCLUSIONThe model accurately depicts population pharmacokinetics of plasma and DBS concentrations over time for oral ivermectin. The proposed analytical workflow is scalable and applicable to the requirements of mass drug administrations. British Journal of Clinical Pharmacology Br J Clin Pharmacol (2019) 85 626-633 626

In today's pharmaceutical research and development, physiologically-based pharmacokinetic (PBPK) modeling plays an important role in the design, evaluation and interpretation of pharmacokinetic, toxicokinetic and formulation studies. PBPK models incorporate in vitro physicochemical and biochemical data in a physiologically based model framework to simulate in vivo exposure. The comparison of simulated concentrations to those measured in in vivo studies can be used to gain insights into compound behavior and to inform PBPK based human pharmacokinetic predictions. The Göttingen minipig is gaining importance as a large animal model in pharmaceutical research due to its physiological and anatomical similarities to human and is increasingly replacing dog and non-human primate in preclinical studies. However, no PBPK model for minipig has yet been published. This review discusses the information available to establish the physiological database for this species and highlights the gaps in current knowledge. A preliminary PBPK model is created from this database and simulations for two drugs dosed both intravenously and orally are compared to measured plasma concentrations. Results support the validity of the model with simulated plasma concentrations within the range of the observations. In conclusion, the model will need to be refined as additional physiological data become available, but it can already provide useful simulations to assist pharmaceutical research and development in the minipig.

Background Activities of hepatic cytochrome P450 enzymes (CYPs) are relevant for hepatic clearance of drugs and known to be decreased in patients with liver cirrhosis. Several studies have reported the effect of liver cirrhosis on CYP activity, but the results are partially conflicting and for some CYPs lacking. Objective In this study, we aimed to investigate the CYP activity in patients with liver cirrhosis with different Child stages (A-C) using the Basel phenotyping cocktail approach. Methods We assessed the pharmacokinetics of the six compounds and their CYP-specific metabolites of the Basel phenotyping cocktail (CYP1A2: caffeine, CYP2B6: efavirenz, CYP2C9: flurbiprofen, CYP2C19: omeprazole, CYP2D6: metoprolol, CYP3A: midazolam) in patients with liver cirrhosis ( n = 16 Child A cirrhosis, n = 15 Child B cirrhosis, n = 5 Child C cirrhosis) and matched control subjects ( n = 12). Results While liver cirrhosis only marginally affected the pharmacokinetics of the low to moderate extraction drugs efavirenz and flurbiprofen, the elimination rate of caffeine was reduced by 51% in patients with Child C cirrhosis. For the moderate to high extraction drugs omeprazole, metoprolol, and midazolam, liver cirrhosis decreased the elimination rate by 75%, 37%, and 60%, respectively, increased exposure, and decreased the apparent systemic clearance (clearance/bioavailability). In patients with Child C cirrhosis, the metabolic ratio (ratio of the area under the plasma concentration–time curve from 0 to 24 h of the metabolite to the parent compound), a marker for CYP activity, decreased by 66%, 47%, 92%, 73%, and 43% for paraxanthine/caffeine (CYP1A2), 8-hydroxyefavirenz/efavirenz (CYP2B6), 5-hydroxyomeprazole/omeprazole (CYP2C19), α-hydroxymetoprolol/metoprolol (CYP2D6), and 1′-hydroxymidazolam/midazolam (CYP3A), respectively. In comparison, the metabolic ratio 4-hydroxyflurbiprofen/flurbiprofen (CYP2C9) remained unchanged. Conclusions Liver cirrhosis affects the activity of CYP isoforms differently. This variability must be considered for dose adjustment of drugs in patients with liver cirrhosis. Clinical Trial Registration NCT03337945. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-022-01119-0.