Life Science

Computational tools and techniques for systems and data analysis are key to gaining better understanding of processes and products as well as to optimizing their performance. This holds true regardless of the applications being of technical or biological character since on a systems level they can be modeled and analyzed using general mathematical techniques.

Predictive Model Based Drug Discovery and Development

The economic risks involved in drug discovery can prevent drug candidates from progressing into clinical development. Modeling and simulation are important tools in a rational approach to drug discovery and development and can help prioritize and assess the potential of compounds, thereby…

Image Analysis Tools for Quantitative Yeast Cell Studies

Quantitative microscopy has in the last couple of years aroused substantial interest for life sciences applications. In eukaryotic cells, quantitative measurements of protein expression, protein localization and protein-protein interactions are key components for a proper understanding of cell functionality. FCC collaborates with…

Pharmacokinetics and Pharmacodynamics

Mathematical modeling and simulation of what the body does to a drug after administration, such as its absorption, distribution, metabolism, and excretion, also known as pharmacokinetics, and models of what the drug does to the body, i.e., how the drug concentration is…

Simulation of Atrial Electrical Activity

Mathematical modeling of biological systems that are of interest in the pharmaceutical industry is a rapidly growing area. The use of mathematical models brings the promise of reducing the high costs and long times associated with the development of new drugs and…

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