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Pharmaceutical companies try to develop new drugs that have a high success rate of reaching the market. However, current disease models lack a strong correlation to clinical reality, because of the underestimation of the complexity and variability of clinical disease processes. This leads to high attrition rates late in drug development and soaring costs. Improvement of disease models is an important issue to reduce the high attrition rates in drug development. Using cell‐based disease models, which should take into account the molecular diversity of the human cytome, will improve the predictive value of drug discovery. © 2006 International Society for Analytical Cytology

The complexity of the spot patterns of two-dimensional electrophoresis gels made it necessary to use image processing techniques to analyze the gels. An important issue in the analysis is the detection and quantification of the protein spots. In this paper we describe a new technique to segment and model the different spots. For the segmentation of a gel into its different spot regions we apply a watershed technique, which is robust and efficient. For the quantification of the spots, a new spot model is constructed, based on diffusion principles. Besides the advantage of having a physical interpretation, the model is demonstrated to be superior to the commonly used Gaussian models.

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The focus of this article is to provide an overview of the current technologies for the pharmaceutical and biotech industry. Disease processes express themselves in the functional and structural disturbance of cellular systems. Cells and their metabolites constitute the building blocks of tissues and entire organisms. Studying the spatial and temporal phenotype of disease processes in tissues at the cellular level reveals a multitude of information about the progress and status of a disease. Detailed exploration of tissues by slide‐based cytometry is an important source of information about disease processes. Technological and analytical advances allow us to shed a new light on tissues and to come to a better understanding of the complexity of disease processes. Dealing with complex multidimensional datasets from tissue samples requires an advanced approach to image processing and data management. The increase in computing power and the continuing research into imaging algorithms allow us to improve the exploration of the data content of tissues. © 2006 International Society for Analytical Cytology