Computer Simulation In Drug Development Helps Reducing Animal Tests
Scientists at the Technische Universität Dresden/Germany are significantly involved in a European research project entitled “BioSim“ which aims at utilising biosimulation as a new tool in drug development. The use of computer simulations will provide more objective data which helps to develop drug compounds more effectively and to reduce investment in drug development drastically. Above all the number of animal tests as well as clinical studies with volunteers will decrease substantially.
“We intend to translate the existing knowledge of drug metabolism and the operating modes of several organs into mathematical models. These serve to perform complex computer simulations of the involved biochemical processes”, says assistant professor Dr Martin Bertau, biochemist at the Department of Chemistry and Food Chemistry at the Technische Universität Dresden.
The highly ambitious scientific “Network of excellence“ – also called “BioSim” – has been funded with 10.7 million euros by the European Union for a five year period since December 2004 and brings together internationally leading European research groups in the fields of life sciences, medicine and mathematics. The activities are coordinated by Professor Erik Mosekilde, Institute of Physics at the Danish University of Technology in Kgs. Lyngby. On the part of the pharmaceutical industry Apogepha Arzneimittel GmbH is involved in Dresden. The network is completed by European regulatory agencies as well as the European Federation of Pharmaceutical Sciences.
In addition to a model of drug metabolism the European activities comprise approaches to the biosimulation of diabetes, cardiac arrhythmia, neurologic/psychiatric disorders and tumor diseases.
At the TU Dresden, a working group of nine scientists headed by assistant professor Dr Martin Bertau of the Institute of Biochemistry as well as researchers from the Institute of High-Performance Computing participate in “BioSim“. Recently, their novel approach in predicting drug metabolism has been successfully demonstrated, using the model drug compound chloramphenicol.
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