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Prior research has found that exposure to natural hazards and infectious disease are associated with adverse mental health outcomes. Less studied are the ways that individual-level and community-level resilience can protect against problematic mental health outcomes following exposure to successive disaster events. In the current study, we examine the role of individual and community resilience on mental health outcomes among 412 adults in Nashville, Tennessee exposed to an EF-3 tornado followed by the COVID-19 pandemic. Results found the cumulative impact of exposure to the tornado and COVID-19 was related to higher levels of PTS and depression symptoms. Individual resilience had a protective, inverse relationship with PTS and depression symptoms and mediated the relationship between community resilience and adverse mental health outcomes. Findings support the development of a multi-system disaster resilience framework that links individual resilience capacities to broader community resilience capacities to activate and sustain healthy adaptation following exposure to successive disasters.

This paper reviews children’s reactions to disasters and the personal and situational factors that influence their reactions. Posttraumatic stress disorder (PTSD) and posttraumatic stress reactions are the most commonly studied outcomes, though other conditions also occur including anxiety, depression, behavior problems, and substance use. More recently, traumatic grief and posttraumatic growth have been explored. New research has delineated trajectories of children’s posttraumatic stress reactions and offered insight into the long-term consequences of their disaster experiences. Risk factors for adverse outcomes include pre-disaster vulnerabilities, perception of threat, and loss and life disruptions post-disaster. Areas in need of additional research include studies on the timing and course of depression and anxiety post-event and their interactions with other disorders, disaster-related functional and cognitive impairment, positive outcomes, and coping.

Purpose To apply physiologically-based pharmacokinetic (PBPK) modeling to investigate the consequences of reduction in activity of hepatic and intestinal uptake and efflux transporters by cyclosporine and its metabolite AM1. Methods Inhibitory potencies of cyclosporine and AM1 against OATP1B1, OATP1B3 and OATP2B1 were investigated in HEK293 cells +/− pre-incubation. Cyclosporine PBPK model implemented in Matlab was used to assess interaction potential (+/− metabolite) against different processes (uptake, efflux and metabolism) in liver and intestine and to predict quantitatively drug-drug interaction with repaglinide. Results Cyclosporine and AM1 were potent inhibitors of OATP1B1 and OATP1B3, IC 50 ranging from 0.019–0.093 μM following pre-incubation. Cyclosporine PBPK model predicted the highest interaction potential against liver uptake transporters, with a maximal reduction of >70% in OATP1B1 activity; the effect on hepatic efflux and metabolism was minimal. In contrast, 80–97% of intestinal P-gp and CYP3A4 activity was reduced due to the 50-fold higher cyclosporine enterocytic concentrations relative to unbound hepatic inlet. The inclusion of AM1 resulted in a minor increase in the predicted maximal reduction of OATP1B1/1B3 activity. Good predictability of cyclosporine-repaglinide DDI and the impact of dose staggering are illustrated. Conclusions This study highlights the application of PBPK modeling for quantitative prediction of transporter-mediated DDIs with concomitant consideration of P450 inhibition.

This review examines family (demographics, parent reactions and interactions, and parenting style) and social (remote effects, disaster media coverage, exposure to secondary adversities, and social support) factors that influence children’s disaster reactions. Lower family socioeconomic status, high parental stress, poor parental coping, contact with media coverage, and exposure to secondary adversities have been associated with adverse outcomes. Social support may provide protection to children in the post-disaster environment though more research is needed to clarify the effects of certain forms of social support. The interaction of the factors described in this review with culture needs further exploration.

ABSTRACT Purpose To investigate the effect of OATP1B1 genotype as a covariate on repaglinide pharmacokinetics and drug-drug interaction (DDIs) risk using a reduced physiologically-based pharmacokinetic (PBPK) model. Methods Twenty nine mean plasma concentration-time profiles for SLCO1B1 c.521T>C were used to estimate hepatic uptake clearance (CL uptake ) in different genotype groups applying a population approach in NONMEM v.7.2. Results Estimated repaglinide CL uptake corresponded to 217 and 113 μL/min/10 6 cells for SLCO1B1 c.521TT/TC and CC, respectively. A significant effect of OATP1B1 genotype was seen on CL uptake (48% reduction for CC relative to wild type). Sensitivity analysis highlighted the impact of CL met and CL diff uncertainty on the CL uptake optimization using plasma data. Propagation of this uncertainty had a marginal effect on the prediction of repaglinide OATP1B1-mediated DDI with cyclosporine; however, sensitivity of the predicted magnitude of repaglinide metabolic DDI was high. In addition, the reduced PBPK model was used to assess the effect of both CYP2C8*3 and SLCO1B1 c.521T>C on repaglinide exposure by simulations; power calculations were performed to guide prospective DDI and pharmacogenetic studies. Conclusions The application of reduced PBPK model for parameter optimization and limitations of this process associated with the use of plasma rather than tissue profiles are illustrated.

The aim of this study is to compare the accuracy of five methods for predicting in vivo intrinsic clearance (CL(int)) and seven for predicting hepatic clearance (CL(h)) in humans using in vitro microsomal data and/or preclinical animal data. The human CL(int) was predicted for 33 drugs by five methods that used either in vitro data with a physiologic scaling factor (SF), with an empirical SF, with the physiologic and drug-specific (the ratio of in vivo and in vitro CL(int) in rats) SFs, or rat CL(int) directly and with allometric scaling. Using the estimated CL(int), the CL(h) in humans was calculated according to the well-stirred liver model. The CL(h) was also predicted using additional two methods: using direct allometric scaling or drug-specific SF and allometry. Using in vitro human microsomal data with a physiologic SF resulted in consistent underestimation of both CL(int) and CL(h). This bias was reduced by using either an empirical SF, a drug-specific SF, or allometry. However, for allometry, there was a substantial decrease in precision. For drug-specific SF, bias was less reduced, precision was similar to an empirical SF. Both CL(int) and CL(h) were best predicted using in vitro human microsomal data with empirical SF. Use of larger data set of 52 drugs with the well-stirred liver model resulted in a best-fit empirical SF that is 9-fold increase on the physiologic SF. Overall, the empirical SF method and the drug-specific SF method appear to be the best methods; they show lower bias than the physiologic SF and better precision than allometric approaches. The use of in vitro human microsomal data with an empirical SF may be preferable, as it does not require extra information from a preclinical study.

Purpose To assess the extent of intestinal and hepatic glucuronidation in vitro and resulting implications on glucuronidation clearance prediction. Methods Alamethicin activated human intestinal (HIM) and hepatic (HLM) microsomes were used to obtain intrinsic glucuronidation clearance (CLint,UGT) for nine drugs using substrate depletion. The in vitro extent of glucuronidation (fmUGT) was determined using P450 and UGT cofactors. Utility of hepatic CLint for the prediction of in vivo clearance was assessed. Results fmUGT (8-100%) was comparable between HLM and HIM with the exception of troglitazone, where a nine-fold difference was observed (8% and 74%, respectively). Scaled intestinal CLint,UGT (per g tissue) was six- and nine-fold higher than hepatic for raloxifene and troglitazone, respectively, and comparable to hepatic for naloxone. The remaining drugs had a higher hepatic than intestinal CLint,UGT (average five-fold). For all drugs with P450 clearance, hepatic CLint,CYP was higher than intestinal (average 15-fold). Hepatic CLint,UGT predicted on average 22% of observed in vivo CLint; with the exception of raloxifene and troglitazone, where the prediction was only 3%. Conclusion Intestinal glucuronidation should be incorporated into clearance prediction, especially for compounds metabolised by intestine specific UGTs. Alamethicin activated microsomes are useful for the assessment of intestinal glucuronidation and fmUGT in vitro.

To compare three liver models (well-stirred, parallel tube, and dispersion) for the prediction of in vivo intrinsic clearance (CL(int)), hepatic clearance (CLh). and hepatic availability (Fh) of a wide range of drugs in the rat using in vitro data from two in vitro sources. In vitro CL(int) was obtained from studies using isolated rat hepatocytes (35 drugs) or rat liver microsomes (52 drugs) and used to predict in vivo CL(int) using reported scaling factors, and subsequently CLh and Fh were predicted based on the three liver models. In addition, in vivo CL(int) values were calculated from the reported values of CLh based on each of the three models. For all of the parameters, predictions from hepatocyte data were consistently more accurate than those from microsomal data. Comparison of in vitro and in vivo CL(int) values demonstrated that the dispersion model and the parallel tube model were comparable and more accurate (less bias, more precise) than the well-stirred model. For CLh and Fh prediction, the three models performed similarly. Considering the statistics of the predictions for three liver models, the use of parallel tube model is recommended for the evaluation of in vitro CL(int) values both from microsomes and hepatocytes. However, for the prediction of the in vivo drug (hepatic) clearance from in vitro data, as there are minimal differences between the models, the use of the well-stirred liver model is recommended.

Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug‐metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO‐mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO‐CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug–drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO‐DDIs with known AO inhibitors, the fraction metabolized by AO (fmAO) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4‐fold versus up to fivefold with physiologically‐based scaling only). Observed fmi from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fmAO (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fmCYP3A4, with predicted ratios of the area under the concentration–time curve (AUCR) within 1.5‐fold of the observations. In conclusion, this study provides a novel PBPK‐based framework for predicting AO‐mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO‐CYP substrates within a totality‐of‐evidence approach.

The literature on children’s responses to disasters is well developed with increasing attention to the confounding experiences of displacement. This paper presents an overview of the emotional and behavioral effects of displacement on children and adolescents and describes their educational adjustment in terms of both academic achievement and school behavior. A summary of family effects elucidates how children’s functioning is influenced through the family system in which they are embedded. The psychosocial impact of displacement reflects the myriad social losses that children and their families may face. Information from this review of the current literature on the effects of displacement may inform the design and delivery of support and intervention services for children and families following disasters.