Model selection and averaging of nonlinear mixed-effect models for robust phase III dose selection

Population model-based (pharmacometric) approaches are widely used for the analyses of phase IIb clinical trial data to increase the accuracy of the dose selection for phase III clinical trials. On the other hand, if the analysis is based on one selected model, model selection bias can potentially spoil the accuracy of the dose selection process. In this paper, four methods that assume a number of pre-defined model structure candidates, for example a set of dose-response shape functions, and then combine or select those candidate models are introduced. The key hypothesis is that by combining both model structure uncertainty and model parameter uncertainty using these methodologies, we can make a more robust model based dose selection decision at the end of a phase IIb clinical trial. These methods are investigated using realistic simulation studies based on the study protocol of an actual phase IIb trial for an oral asthma drug candidate (AZD1981). Based on the simulation study, it is demonstrated that a bootstrap model selection method properly avoids model selection bias and in most cases increases the accuracy of the end of phase IIb decision. Thus, we recommend using this bootstrap model selection method when conducting population model-based decision-making at the end of phase IIb clinical trials

Dose-Response Mixed Models for Repeated Measures – a New Method for Assessment of Dose-Response

Purpose In this paper we investigated a new method for dose-response analysis of longitudinal data in terms of precision and accuracy using simulations. Methods The new method, called Dose-Response Mixed Models for Repeated Measures (DR-MMRM), combines conventional Mixed Models for Repeated Measures (MMRM) and dose-response modeling. Conventional MMRM can be applied for highly variable repeated measure data and is a way to estimate the drug effect at each visit and dose, however without any assumptions regarding the dose-response shape. Dose-response modeling, on the other hand, utilizes information across dose arms and describes the drug effect as a function of dose. Drug development in chronic kidney disease (CKD) is complicated by many factors, primarily by the slow progression of the disease and lack of predictive biomarkers. Recently, new approaches and biomarkers are being explored to improve efficiency in CKD drug development. Proteinuria, i.e. urinary albumin-to-creatinine ratio (UACR) is increasingly used in dose finding trials in patients with CKD. We use proteinuria to illustrate the benefits of DR-MMRM. Results The DR-MMRM had higher precision than conventional MMRM and less bias than a dose-response model on UACR change from baseline to end-of-study (DR-EOS). Conclusions DR-MMRM is a promising method for dose-response analysis

Estrogen attenuates vascular expression of inflammation associated genes and adhesion of monocytes to endothelial cells

Objective: Investigate effects of estrogen at gene expression and functional levels in vascular wall cells treated with bacterial lipopolysaccharide (LPS). Materials and methods: Aortic segments from ovariectomized mice were treated with LPS for 24 h in the absence or presence of 17 beta-estradiol (E-2). Gene activity was determined by Affymetrix microarray analysis and real-time RTPCR. Adhesion of [H-3]-thymidine labelled human THP-1 monocytes to mouse bEnd.3 endothelial cells was determined by measuring radioactivity of DNA from co-culture homogenates. Results: Analysis of global gene expression profiles revealed that 10 nM E-2 attenuates LPS-induced (10 ng/ml) expression of genes coding for well-known acute-phase proteins, such as alpha-trypsin inhibitor heavy chain 4, serum amyloid A3 and lipocalin 2. The E-2-induced down-regulation of these three genes observed by microarray was confirmed by realtime RT-PCR. Treatment with 500ng/ml LPS increased adhesion of monocytes to endothelial cells more than two fold. Importantly, LPS-induced monocyte adhesion was fully prevented by 50nM E-2. Conclusion: Estrogen reduces expression of acute-phase protein genes and inhibits LPS-induced moncocyte adhesion to endothelial cells, suggesting that estrogen might have a vasculoprotective effect via this mechanism