A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions

All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies

Time spent on work-related activities, social activities and time pressure as intermediary determinants of health disparities among elderly women and men in 5 European countries: a structural equation model

Background Psychosocial factors shape the health of older adults through complex inter-relating pathways. Besides socioeconomic factors, time use activities may explain gender inequality in self-reported health. This study investigated the role of work-related and social time use activities as determinants of health in old age. Specifically, we analysed whether the impact of stress in terms of time pressure on health mediated the relationship between work-related time use activities (i.e. housework and paid work) on self-reported health. Methods We applied structural equation models and a maximum-likelihood function to estimate the direct and indirect effects of psychosocial factors on health using pooled data from the Multinational Time Use Study on 11,168 men and 14,295 women aged 65+ from Italy, Spain, UK, France and the Netherlands. Results The fit indices for the conceptual model indicated an acceptable fit for both men and women. The results showed that socioeconomic status (SES), demographic factors, stress and work-related time use activities after retirement had a significant direct influence on self-reported health among the elderly, but the magnitude of the effects varied by gender. Social activities had a positive impact on self-reported health but had no significant impact on stress among older men and women. The indirect standardized effects of work-related activities on self-reported health was statistically significant for housework (β = − 0.006; P  0.05 among women), which implied that the paths from paid work and housework on self-reported health via stress (mediator) was very weak because their indirect effects were close to zero. Conclusions Our findings suggest that although stress in terms of time pressure has a direct negative effect on health, it does not indirectly influence the positive effects of work-related time use activities on self-reported health among elderly men and women. The results support the time availability hypothesis that the elderly may not have the same time pressure as younger adults after retirement

The association of neighbourhood and individual social capital with consistent self-rated health: a longitudinal study in Brazilian pregnant and postpartum women.

BACKGROUND: Social conditions, social relationships and neighbourhood environment, the components of social capital, are important determinants of health. The objective of this study was to investigate the association of neighbourhood and individual social capital with consistent self-rated health in women between the first trimester of pregnancy and six months postpartum. METHODS: A multilevel cohort study in 34 neighbourhoods was performed on 685 Brazilian women recruited at antenatal units in two cities in the State of Rio de Janeiro, Brazil. Self-rated health (SRH) was assessed in the 1st trimester of pregnancy (baseline) and six months after childbirth (follow-up). The participants were divided into two groups: 1. Good SRH--good SRH at baseline and follow-up, and, 2. Poor SRH--poor SRH at baseline and follow-up. Exploratory variables collected at baseline included neighbourhood social capital (neighbourhood-level variable), individual social capital (social support and social networks), demographic and socioeconomic characteristics, health-related behaviours and self-reported diseases. A hierarchical binomial multilevel analysis was performed to test the association between neighbourhood and individual social capital and SRH, adjusted for covariates. RESULTS: The Good SRH group reported higher scores of social support and social networks than the Poor SRH group. Although low neighbourhood social capital was associated with poor SRH in crude analysis, the association was not significant when individual socio-demographic variables were included in the model. In the final model, women reporting poor SRH both at baseline and follow-up had lower levels of social support (positive social interaction) [OR 0.82 (95% CI: 0.73-0.90)] and a lower likelihood of friendship social networks [OR 0.61 (95% CI: 0.37-0.99)] than the Good SRH group. The characteristics that remained associated with poor SRH were low level of schooling, Black and Brown ethnicity, more children, urinary infection and water plumbing outside the house. CONCLUSIONS: Low individual social capital during pregnancy, considered here as social support and social network, was independently associated with poor SRH in women whereas neighbourhood social capital did not affect women's SRH during pregnancy and the months thereafter. From pregnancy and up to six months postpartum, the effect of individual social capital explained better the consistency of SRH over time than neighbourhood social capital

Evaluation of Calibration Curve-Based Approaches to Predict Clinical Inducers and Noninducers of CYP3A4 with Plated Human Hepatocytes

Cytochrome P450 (P450) induction is often considered a liability in drug development. Using calibration curve-based approaches, we assessed the induction parameters R3 (a term indicating the amount of P450 induction in the liver, expressed as a ratio between 0 and 1), relative induction score, Cmax/EC50, and area under the curve (AUC)/F2 (the concentration causing 2-fold increase from baseline of the dose-response curve), derived from concentration-response curves of CYP3A4 mRNA and enzyme activity data in vitro, as predictors of CYP3A4 induction potential in vivo. Plated cryopreserved human hepatocytes from three donors were treated with 20 test compounds, including several clinical inducers and noninducers of CYP3A4. After the 2-day treatment, CYP3A4 mRNA levels and testosterone 6beta-hydroxylase activity were determined by real-time reverse transcription polymerase chain reaction and liquid chromatography-tandem mass spectrometry analysis, respectively. Our results demonstrated a strong and predictive relationship between the extent of midazolam AUC change in humans and the various parameters calculated from both CYP3A4 mRNA and enzyme activity. The relationships exhibited with non-midazolam in vivo probes, in aggregate, were unsatisfactory. In general, the models yielded better fits when unbound rather than total plasma Cmax was used to calculate the induction parameters, as evidenced by higher R(2) and lower root mean square error (RMSE) and geometric mean fold error. With midazolam, the R3 cut-off value of 0.9, as suggested by US Food and Drug Administration guidance, effectively categorized strong inducers but was less effective in classifying midrange or weak inducers. This study supports the use of calibration curves generated from in vitro mRNA induction response curves to predict CYP3A4 induction potential in human. With the caveat that most compounds evaluated here were not strong inhibitors of enzyme activity, testosterone 6beta-hydroxylase activity was also demonstrated to be a strong predictor of CYP3A4 induction potential in this assay mode