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https://www.selleckchem.com/products/Rosuvastatin-calcium(Crestor).html As decisions in drug development increasingly rely on predictions from mechanistic systems models, assessing the predictive capability of such models is becoming more important. Several frameworks for the development of quantitative systems pharmacology (QSP) models have been proposed. In this paper, we add to this body of work with a framework that focuses on the appropriate use of qualitative and quantitative model evaluation methods. We provide details and references for those wishing to apply these methods, which include sensitivity and identifiability analyses, as well as concepts such as validation and uncertainty quantification. Many of these methods have been used successfully in other fields, but are not as common in QSP modeling. We illustrate how to apply these methods to evaluate QSP models, and propose methods to use in two case studies. We also share examples of misleading results when inappropriate analyses are used. What is the central question of this study? First, we validated easy-to-use oscillometric left ventricular ejection time (LVET) against echocardiographic LVET. Second, we investigated progression of left ventricular ejection time index (LVETI), pre-ejection period index (PEPI), total electromechanical systole index (QS2I) and PEP/LVET ratio during 60 days of head-down tilt (HDT). What is the main finding and its importance? The LVET and LVET showed good agreement in effect direction. Hence, LVET might be useful to evaluate cardiovascular responses during space flight. Moreover, the approach might be useful for individual follow-up of patients with altered ejection times. Furthermore, significant effects of 60days of HDT were captured by measurements of LVETI, PEPI, QS2I and PEP/LVET ratio. Systolic time intervals that are easy to detect might be used as parameters reflecting cardiovascular deconditioning. We compared left ventricular ejection time (LVET) measured via

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