According to reports, the Massachusetts Institute of Technology (MIT) established the Drug Discovery and Synthesis Machine Learning Association (MLPDS) to try to change the drug development process. Currently, there are 8 industry partners, all leading in the pharmaceutical industry, including Amgen, BASF, Bayer. , Lilly, NovarTIs, Pfizer, Sunovion, and WuXi. Drug research and development is costly and time consuming, but machine learning is expected to analyze a large amount of chemical data, improve research and development efficiency, and help the development process and results. The MLPDS Association will combine the power of the MIT research team and industry with the primary goal of introducing machine learning into the drug development process. In April 2018, MIT held a summit, led by computer science professor Regina Barzilay and electronic engineering professor Erna Viterbi, to convene MIT researchers and technology, biotechnology and regulatory units to explore how to use digital technology and artificial intelligence. (AI) Overcoming the major challenges of biomedical and medical care. The MLPDS Association was initially funded by the Defense Advanced Research Projects Agency (DARPA) Make-It Program, which aims to synthesize drugs using machine learning and automated systems. It was followed by representatives of the pharmaceutical industry in May and September 2017. Businesses, regardless of industry or MIT, have a strong interest in cooperation. Klavs Jensen, a professor of materials science engineering, said that the co-workers are full of enthusiasm, and the potential of machine learning technology is unlimited. These will be the strong backing of scientists in the chemical and pharmaceutical industries. Machine learning helps to plan the chemical synthesis pathway and lead us to explore new chemical fields. To increase the diversity of chemistry, there will be a greater opportunity to identify compounds with special functions. In May 2018, the MLPDS Association once again gathered industry partners to provide them with a basic concept of machine learning through teaching and collaborative research programs. Barzilay teaches the basic supervised learning, one of the methods of machine learning, and also includes neural models and representationa learning. Barzilay said that it is just beginning to explore this new field, but the future potential is endless and it is expected to improve people's lives. This cooperation with the pharmaceutical industry is believed to be the key to smooth cooperation. He has always benefited a lot from the industry and found no. Less new questions worth thinking about. One of the goals of the association is to establish evaluation criteria and standard data sets to confirm the accuracy of machine learning methods. Most of the current research teams are based on internal data sets for evaluation, which hinders the comparison of different models and drags The slow scientific process, and even worse, the disclosure of information and the inability to present the complexity of pharmaceutical research. MIT conducts cross-disciplinary collaboration through new associations, including machine learning, chemical and chemical engineering. This is good for researchers and users of new technologies, helping to understand the current level of development and the potential for new technologies in machine learning. Jaakkola also said that combining modern machine learning techniques and chemistry knowledge is expected to open new avenues for drug discovery, improvement and synthesis. Connor Coley, a graduate student in chemical engineering, said that although drug synthesis planning software has been around for a long time, it has not been widely adopted. Synthetic planning is crucial for the initial drug development phase, and can quickly discover new synthetic strategies and reduce repeated research and development, synthesis, and testing. time. Co-ops are also optimistic about the potential of machine learning technology, Amgen's Shawn Walker said that machine learning is expected to accelerate drug development and more quickly deliver new drugs to patients. Novade's Biomedical Research Institute (NIBR) said that they are looking forward to joining the new association established by MIT, which is expected to accelerate the production of safer and more effective drugs. General Purpose Diode,General Purpose Rectifier Diode,General Purpose Schottky Diode,General Purpose Power Diode Shenzhen Kaixuanye Technology Co., Ltd. , https://www.iconlinekxys.com