There is a huge pain point in the traditional drug research and development field. First, the research and development cycle is long, the development time of new drugs is about 10 years on average; second, the cost is high, and the research and development cost of each new drug is about 1.5 billion US dollars; third, the success rate is low, and only about one of the about 5,000 synthetic compounds can enter clinical II. Period experiment.
The combination of artificial intelligence and drug mining can greatly improve research and development efficiency and reduce enterprise costs. At present, there are several technology-leading start-ups in North America. They use deep learning to cooperate with traditional pharmaceutical companies and medical research institutions such as Merck to infect cardiovascular drugs, anti-tumor drugs, orphan drugs and economically underdeveloped areas. New breakthroughs have been made in many areas such as the treatment of diseases such as Ebola, and it has attracted the favor of excellent incubators such as Y Combinator, Khosla Ventures and Data Collective.
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