AMRI leads European cancer research project

Albany Molecular Research, Inc.(AMRI) has launched the CancerGrid Project, a three-year multidisciplinary research programme funded by the European Commission in which 10 life sciences companies and academic centres will work together to discover and develop novel anticancer agents.

'This innovative project utilises grid-based computing technology for the automated design of chemical libraries, with the goal of discovering potential cancer treatments,' said Michael Guaciaro, president and managing director of AMRI's European operations, located in Budapest, Hungary.

Grid computing uses multiple computational resources in a parallel manner, allowing researchers to tap into a powerful network of interconnected workstations that can process large amounts of data and reduce computational time.

In addition to AMRI's site in Budapest, Hungary, the consortium includes both companies and academic centres with established reputations in anticancer research and project management: Inte:Ligand (Austria), Tallinn University of Technology (Estonia), University of Helsinki (Finland), GKI Economic Research Co., Computer and Automation Research Institute (Hungary), DAC Srl and University of Bari (Italy), University Pompeu Fabra (Spain) and Hebrew University of Jerusalem (Israel).

'We are excited to coordinate such a distinguished consortium of cancer research experts,' added Guaciaro, who noted that the project represents the first large scale application of this technology in drug discovery.

'Our goal is to develop methods for creating chemical libraries containing molecules active against the newly emerging cancer targets,' said Gyorgy Dorman, head of science and technology at AMRI in Budapest, Hungary.

'The use of grid-aided technology should substantially increase both the likelihood of finding novel anticancer lead compounds, as well as increase the translation of basic knowledge into the application stage,' he added.

This project is also expected to produce and validate a technology for in silico design of chemical libraries and models that predict toxicity and target specificity, which are theoretically applicable to any drug discovery project.