Global pharmaceutical company Astellas Pharma has signed collaborative research agreements with both the Nagasaki University and the Tokyo Institute of Technology, both located in Japan, regarding the dengue virus.
The agreement between Astellas and Nagasaki University will aim to discover new drugs for the treatment of neglected tropical diseases (NTDs) caused by dengue virus. The agreement between Astellas and Tokyo Institute of Technology will permit Astellas to utilize Tokyo Tech's TSUBAME2.0 supercomputer to efficiently discover candidates for the treatment of NTDs caused by dengue virus.
The Institute of Tropical Medicine at Nagasaki University (NEKKEN) and Astellas will cooperate on a drug-discovery research project. Astellas will provide multiple compounds with possible anti-dengue virus activities, and NEKKEN will evaluate these compounds in experimental model of infections with dengue virus for dengue fever/dengue hemorrhagic fever. The research will be advanced with advice from professor Kouichi Morita, M.D., Ph.D., at the department of virology in NEKKEN.
The collaborative research is largely divided into two phases. In the first phase (first screening), the anti-dengue virus activities and cytotoxic activities of compounds will be measured in vitro. In the second phase (second screening), compounds found to be with anti-dengue virus activities in the first screening will be tested for in vivo activity by evaluating drug efficiency in animals infected with the dengue virus.
In the Tokyo Tech collaboration, Astellas will work with a research group co-led by professor Yutaka Akiyama, Dr.Eng., at the department of computer science in the graduate school of information science and engineering, and associate professor Masakazu Sekijima, Ph.D., at the global scientific information and computing center.
Tokyo Tech’s petaflop class supercomputer TSUBAME2.0 will be used for data mining and for in-silico screening calculations of commercially available compounds. Astellas will be responsible for preparing input data for data mining, selecting and listing of hit compounds to be evaluated based on the in-silico screening calculations, thereby implementing efficient drug discovery in a short time period.