Objective: To compare associations between individual antidepressants and newborn outcomes.Design: Retrospective cohort study.Setting: Deliveries in a large, US medical system.Population: Women who received at least one antidepressant prescription 3 months prior to conception through delivery.Methods: Eligible women had maternal characteristics and newborn outcomes extracted from medical record data. Exposure was defined by the timing of the prescription during pregnancy.

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INTRODUCTION: Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage. METHODS: We performed 18F-FDG Positron Emission Tomography (PET) imaging in 4, 6, and 12 month old 5XFAD and littermate controls (WT) of both sexes, and analyzed region data via brain metabolic covariance analysis. RESULTS: 5XFAD model mice show age related changes glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model. DISCUSSION: The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.

Aims Physiologically based pharmacokinetic (PBPK) models have been previously developed for betamethasone and buprenorphine for pregnant women. The goal of this work was to replicate and reassess these models using data from recently completed studies. Methods Betamethasone and buprenorphine PBPK models were developed in Simcyp V19 based on prior publications using V17 and V15. Ability to replicate models was verified by comparing predictions in V19 to those previously published. Once replication was verified, models were reassessed by comparing predictions to observed data from additional studies in pregnant women. Model performance was based upon visual inspection of concentration vs. time profiles, and comparison of pharmacokinetic parameters. Models were deemed reproducible if parameter estimates were within 10% of previously reported values. External validations were considered acceptable if the predicted area under the concentration–time curve (AUC) and peak plasma concentration fell within 2‐fold of the observed. Results The betamethasone model was successfully replicated using Simcyp V19, with ratios of reported (V17) to reproduced (V19) peak plasma concentration of 0.98–1.04 and AUC of 0.95–1.07. The model‐predicted AUC ratios ranged from 0.98–1.79 compared to external data. The previously published buprenorphine PBPK model was not reproducible, as we predicted intravenous clearance of 70% that reported previously (both in Simcyp V15). Conclusion While high interstudy variability was observed in the newly available clinical data, the PBPK model sufficiently predicted changes in betamethasone exposure across gestation. Model reproducibility and reassessment with external data are important for the advancement of the discipline. PBPK modelling publications should contain sufficient detail and clarity to enable reproducibility.