Researchers at the University of Waterloo Canada have developed a new artificial intelligence system that can dramatically accelerate the rate of innovation in new drugs while reducing the need for expensive and time-consuming laboratory tests.
As part of a deep learning technology, the new system is called "perennial" and it can predict the communication process between biological sequences in seconds, which can reduce the complex problems that can occur during drug research.
PUK uses artificial intelligence technology to collect information through data analysis rather than relying on existing search mechanisms.
"POT systems can and do change the rules of the game with the ability to decode microprotein bonds in complex chemical environments," said Andrew Wong, an electronics systems engineering specialist. Accurate prediction based on available data. "
"The ability to access accurate information based on proven scientific results will lead to future research in pharmaceutical research," Wong said, noting that the PTO system has the potential to change how data is used in the future.
Researchers collect vast amounts of data from essential sequences, but it is not easy to extract meaningful and meaningful data from these data, but POT is an amino acid that decodes complex relationships within a biochemical equation and regulates protein response.
By deriving the results of the database through cloud computing technology, the P2K system can predict the possible interactions between preventive tumors and various cancer treatments.
PTK systems are still experimental prototypes, but Wong and his team have provided researchers with access to system versions on the Internet. "It would be helpful to leave this technology in the hands of a biomedical researcher.
Reach immediate results that can be used for future scientific discoveries. "