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Bern, Switzerland

Sampling from a finite population on multiple occasions introduces dependencies between the successive samples when overlap is designed. Such sampling designs lead to efficient statistical estimates, while they allow estimating changes over time for the targeted outcomes. This makes them very popular in real-world statistical practice. Sampling with partial replacement can also be very efficient in biological and environmental studies where estimation of toxicants and its trends over time is the main interest. Sampling with partial replacement is designed here on two occasions in order to estimate the median concentration of chemical constituents quantified by means of liquid chromatography coupled with tandem mass spectrometry. Such data represent relative peak areas resulting from the chromatographic analysis. They are therefore positive-valued and skewed data, and are commonly fitted very well by the log-normal model. A log-normal model is assumed here for chemical constituents quantified in mainstream cigarette smoke in a real case study. Combining design-based and model-based approaches for statistical inference, we seek for the median estimation of chemical constituents by sampling with partial replacement on two time occasions. We also discuss the limitations of extending the proposed approach to other skewed population models. The latter is investigated by means of a Monte Carlo simulation study. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

Boulenc X.,Sanofi S.A. | Barberan O.,Product Development
Drug Metabolism and Drug Interactions

Prediction of in vivo drug-drug interactions (DDIs) from in vitro and in vivo data, also named in vitro in vivo extrapolation (IVIVE), is of interest to scientists involved in the discovery and development of drugs. To avoid detrimental DDIs in humans, new drug candidates should be evaluated for their possible interaction with other drugs as soon as possible, not only as an inhibitor or inducer (perpetrator) but also as a substrate (victim). DDI risk assessment is addressed along the drug development program through an iterative process as the features of the new compound entity are revealed. Both in vitro and preclinical/clinical outcomes are taken into account to better understand the behavior of the developed compound and to refine DDI predictions. During the last decades, several equations have been proposed in the literature to predict DDIs, from a quantitative point of view, showing a substantial improvement in the ability to predict metabolism-based in vivo DDIs. Mechanistic and dynamic approaches have been proposed to predict the magnitude of metabolic-based DDIs. The purpose of this article is to provide an overview of the current equations and methods, the pros and cons of each method, the required input data for each of them, as well as the mechanisms (i.e., reversible inhibition, mechanism-based inhibition, induction) underlying metabolic-based DDIs. In particular, this review outlines how the methods (static and dynamic) can be used in a complementary manner during drug development. The discussion of the limitations and advantages associated with the various approaches, as well as regulatory requirements in that field, can give the reader a helpful overview of this growing area. © 2011 by Walter de Gruyter Berlin Boston 2011. Source

Coffey R.J.,Neuromodulation Clinical and Emerging Therapies | Miesel K.,Product Development | Billstrom T.,Medtronic
Stereotactic and Functional Neurosurgery

Background and Objective: Intrathecal drug delivery catheter malfunctions are a principal cause of therapy interruption. We determined that normal baseline intrathecal cerebrospinal fluid (CSF) pressure recordings could be obtained in an ovine model and in a catheter dislodgement scenario. Methods: Two sheep were implanted with spinal catheters: 2 in the T6 epidural space in sheep No. 1; 1 T6 intrathecal catheter plus 1 L2 epidural catheter with a deliberate CSF leak to simulate dislodgement in sheep No. 2. Pressure waves were recorded intraoperatively and at multiple times after the implantation in the awake condition. On day 21, the animals were anesthetized for pressure recordings while on and temporarily off mechanical ventilation. They were then necropsied. Results: CSF pressure waves were obtained in this animal model under anesthesia with or without mechanical ventilation and in the awake state. Fluid accumulation at the tip of a dislodged (epidural) catheter temporarily caused apparent coupling of fluid pressures across the dura. An unintentional extraspinal fluid collection in sheep No. 2 was associated with a raised baseline epidural pressure. Conclusions: These findings support the notion that pressure sensors can play a role in determining the status of intraspinal drug delivery catheters. Copyright © 2010 S. Karger AG, Basel. Source

Murphy T.F.,Research and Development | Lindsley B.A.,Product Development | Schade C.T.,Hoeganaes Corporation
International Journal of Powder Metallurgy

The effect of pearlite spacing and chemical composition on the axial-fatigue behavior of fully pearlitic powder metallurgy steels is was investigated. A mixture of an atomized iron powder and graphite was used as the base alloy for the study with a second alloy incorporating copper as the elemental alloying additive and a combination of silicon and vanadium as the additive in the third alloy. Transverse-rupture (TR), tensile, impact, and axial-fatigue bars were pressed from these mixtures to achieve a 7.0 g/cm 3 sintered density. Both the carbon contents and green density were altered slightly in the F-0008 and FC-0208 alloys to account for the expected effects of the sintering temperatures. Cross sections were removed from the broken TR and fatigue bars to examine the overall microstructure, evaluate the pore structure, and measure the interlamellar pearlite spacing. The result shows that the iron-silicon-vanadium-carbon alloy has more area occupied by smaller pores compared with the other four samples and an overall smaller pore-size distribution. Source

Rousseau C.W.,Product Development | Knoetze J.H.,Stellenbosch University
Journal of Propulsion and Power

Triggering of nonlinear combustion instability has often been attributed to velocity coupling. The prediction of this term is often ad hoc in nature, with no accepted experimental method to obtain the velocity-coupled response function. Tubular-grain solid rocket motors have been used successfully to obtain pressure-coupled response functions. The Rousseau and Knoetze analysis is extended to calculate the velocity-coupled response function using the Burnley-Culick velocity-coupling model. This model is used due to its easy incorporation into the analysis methodology. The solid rocket motor's linear stability is calculated for the expected modes at the point where nonlinear combustion instability occurs. Decomposing the composite acoustic wave, from pulse-tested tubular-grain motor data, into its fundamental modes makes it possible to obtain the velocity-coupling response function for several frequencies. The results from this analysis return reasonable values for the velocity-coupled response. These values can then be used to predict triggering. This analysis can be applied to liquid, ram, and hybrid rockets or any system that exhibits longitudinal mode acoustic instability. The ad hoc velocity-coupling model was used here, but the analysis methodology can be used to investigate other models as well. Copyright © 2012 by the American Institute of Aeronautics and Astronautics, Inc. Source

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