The pharmaceutical industry is a high-technology industry, and economically it is one of the best performing industries in Europe. There is an enormous need  for new and effective drugs to treat a wide variety of different diseases associated with the changing life styles (diabetes, hyertension, etc.), the aging of the population (Alzheimer, Parkinson, etc.) and the threat of new epidemics (HIV, SARS, etc.). At the same time, there is a significant challenge in the development of personalized and biologically more specific treatments. Yet, the European pharmaceutical industry exeriences significant dífficulties associated primarily with the rapidly rising costs of drug development.

A significant part of these costs is associated with the large number of tests that a drug must undergo to prove its efficacy and lack of adverse side effects. The development of detailed mechanism based models that can lead to a deeper understanding of the involved biological, pathological and pharmacological phenomena appear as the most promising way to cut the development costs and time. By means of a mathematical model one can extract the information available from a given test much more efficently, and one can accumulate knowledge from test to test. The main difficulty with this approach lies in the communication between theoretically oriented mathematicians, physicists and computer engineers on one side and the experimentally oriented life scientists on the other.

With its 26 academic, 10 industrial and 4 regulatory partners, the BioSim Network commands a wide range of biomedical expertise. At the same time, the network involves leading experts in pharmacokinetics, computer simulation, and complex systems theory. The purpose of the network is to develop in silico simulation models of cellular, physiological and pharmacological processes to provide a deeper understanding of the biological processes and help the pharmaceutical industry maintain its competitive power.

Among the projects that the BioSim Network will undertake in the next 18 months are studies of pancreatic hormone release and interactions among pancreatic cells, protein phosphorylation in human fat cells, flux control and metabolism in striated muscle cells, calcium-induces calcium release and activation of smooth muscle cells, autonomous oscillations in nerve cells and the use of deep brain stimulation to desynchronize cellular spiking behavior, nephron pressure and flow regulation, cardiac arrhythmia, mental disorders and sleep-wake cycles, the function of new anti-cancer molecules, drug absorption and metabolism, insulin-glucose regulation and the treatment of diabetes, chronotherapy of cancer, and the building of virtual populations of relevance to pharmacokinetic studies.

BioSim will also engage in a wide range of educational activities, including the training of PhD students, specialized courses for industry and regulatory experts, and communication with the public.