Simcyp Launches Virtual ‘Lab Rat’ for Drug Development
News Oct 21, 2008
Simcyp Limited, the leader in modelling and simulation of drug-drug interactions in virtual human populations, announced the launch of Simcyp Rat 2008, a ‘virtual animal’ for in silico prediction of drug kinetics.
Rats have been traditionally used in pharmaceutical development to examine how a compound is absorbed, distributed, metabolised and excreted by the body. Simcyp Rat can model these processes, providing crucial insights into how medicines will behave in real life.
Professor Amin Rostami-Hodjegan, Director of Research and Development at Simcyp Limited commented: “We have a great understanding of rat physiology which has allowed us to create algorithms and models which represent a virtual rat. Research scientists can now use their drug development data in simulations to predict how their medicine will behave in virtual animals. The system can even mimic real life experimental scenarios including whether rats are fed at the time of dosing and the amount of fluid that is administered with an oral dose.”
Dr Steve Toon, Executive Director at Simcyp, commented: “There is growing support within the pharmaceutical industry for alternative approaches to reduce, refine and replace animal testing while still maintaining high standards of research. Modelling and simulation is another tool which is now available to researchers who are trying to achieve these goals.”
The Simcyp Rat Simulator contains databases of commonly used drugs which allow the properties of new medicines to be compared with medicines that are already available. The Simulator is available to members of the Simcyp Consortium which includes nine of the top ten pharmaceutical companies worldwide.
Chinese researchers have developed interfacially polymerized porous polymer particles for low- abundance glycopeptide separation. These polymer particles - with hydrophilic-hydrophobic heterostructured nanopores - can separate low-abundance glycopeptides from complex biological samples with high-abundance background molecules efficiently.