Brief Exposure to Pictures Depicting Poor Environments Leads to Increased Consumption of Beer in Adult Social Drinkers

Previous studies have suggested a trait-like association between neighborhood deprivation and alcohol consumption. However, it is not known whether temporarily manipulating poverty and affluence states by exposure to stimuli signifying resource-scarcity or resource-wealth would influence alcohol-seeking behavior. Here, we aimed to investigate whether implicit exposure to affluence and poverty-related pictures would influence beer consumption. Participants in a “poverty” group viewed pictures depicting impoverished environments, and participants in an “affluence” group viewed images of wealthy environments. After priming, participants were provided with nonalcoholic beer (which they were told was alcohol-containing beer) and orange juice under the guise of a bogus taste test, to measure their alcohol-seeking behavior. Results showed that priming participants with a resource-scarce environment led to an increase in beer consumption (as a percentage of total fluid consumed), compared to priming with a resource-rich environment. The same pattern of results was obtained in both a Western European sample (Experiment 1) and a West Indian sample (Experiment 2). In Experiment 2, we also tested whether risk-taking behavior, measured by the Balloon Analogue Risk Task, was influenced by the environmental priming; no differences between groups were observed. These results provide the first experimental evidence that manipulation of poverty-affluence state, by brief exposure to pictures of impoverished or wealthy neighborhoods, can influence alcohol-seeking behavior in adult social drinkers.     

Prediction of drug‐drug interactions using physiologically‐based pharmacokinetic models of CYP450 modulators included in Simcyp software

In recent years, physiologically based PharmacoKinetic (PBPK) modeling has received growing interest as a useful tool for the assessment of drug pharmacokinetics. It has been demonstrated to be informative and helpful to quantify the modification in drug exposure due to specific physio‐pathological conditions, age, genetic polymorphisms, ethnicity and particularly drug–drug interactions (DDIs). In this paper, the prediction success of DDIs involving various cytochrome P450 isoenzyme (CYP) modulators namely ketoconazole (a competitive inhibitor of CYP3A), itraconazole (a competitive inhibitor of CYP3A), clarithromycin (a mechanism‐based inhibitor of CYP3A), quinidine (a competitive inhibitor of CYP2D6), paroxetine (a mechanism‐based inhibitor of CYP2D6), ciprofloxacin (a competitive inhibitor of CYP1A2), fluconazole (a competitive inhibitor of CYP2C9/2C19) and rifampicin (an inducer of CYP3A) were assessed using Simcyp^® software. The aim of this report was to establish confidence in each CYP‐specific modulator file so they can be used in the future for the prediction of DDIs involving new victim compounds. Our evaluation of these PBPK models suggested that they can be successfully used to evaluate DDIs in untested scenarios. The only noticeable exception concerned a quinidine inhibitor model that requires further improvement. Additionally, other important aspects such as model validation criteria were discussed.