AI pharmaceutical circuit is heating up, but the three major difficulties still need to be solved.

Pharmaceutical Network Market Analysis: It is well known that the problems of long research and development cycle, low success rate and high research and development costs have been plaguing pharmaceutical companiesAccording to public information, the average time it takes for a new drug to go on the market takes about 14 years and $2.6 billion (an increase of 145 percent over 2003)Huge research and development costs for new drugs are making it increasingly unaffordable for pharmaceutical companiesAs a result, AI technology, which is expected to be effective enough to reduce research and development costs, has begun to receive widespread attention in the pharmaceutical industry in recent yearsThe AI-plus pharmaceutical circuit is heating up, but the three major difficulties still need to be solved in recent years, we can clearly see that there are a number of powerful pharmaceutical companies began to try cross-border AI, in the "AI enabling pharmaceutical industry development" to make their own effortsFor example, AstraZeneca in 2017 with various partners to establish the China Health Internet of Things Innovation Center, relying on artificial intelligence, Internet of Things, big data, 5G and other high-tech, to create a comprehensive treatment management solutionsAt the 2020 World AI Conference Cloud Summit, AstraZeneca also unveiled the top 10 "AI-Medical" scenarios and recruited partners to focus on disease management and empower the industry with eco-innovationNovartis is in the "AI enabling new drug research and development" in the direction of exploring more pharmaceutical companies, the relevant actions have reached 30, of which up to 20 internal research and developmentIn addition, in March 2019, Novartis Signed a new strategic partnership memorandum with Tencent to better benefit chronically ill patients by integrating innovative drugs, artificial intelligence and social platformsGilead announced a strategic partnership with insitro in April 2019 to develop treatment options for non-alcoholic fatty hepatitis patientsThe two companies signed a three-year, $1 billion cooperation agreementThrough the agreement, Gilead will use insitro's artificial intelligence platform to create disease models for non-alcoholic fatty hepatitis, develop treatment options, and identify targets that can help clinical progression and disease subsidyFrom the above point of view, artificial intelligence empowers the field of medical health has become a trend, and in the field of medicine is showing more and more powerful roleHowever, it is worth noting that, on the whole, the current status quo of AI-plus pharmaceutical research and development is not very optimistic, but also faces many challengesFirst, the real output of AI-plus drug research and development is very small, and most companies need to face a situation where the results of insufficient or inadequate output lead to financial distressIt is reported that in April 2019, IBM decided to stop developing and selling the drug development tool, The Watson Artificial Intelligence Suite, because of poor financial resultsAs a leader in artificial intelligence in the field of medical health, it also has to face the state of poor financial performance In addition, the current AI application of more concentrated target screening direction, has been through literature analysis and other screening than approved drugs more targets, but the target and drug-making evidence is a difficult problem, how to establish a confirmed model, and what to use to confirm, confirm the prediction of drug medicinal ability, are need to think In addition, Companies in AI-plus drug research and development face policy, talent, technology and other challenges The introduction of new technology, so that the original drug research and development model changes, regulatory talent, policy guidelines, etc need to be updated simultaneously, and there is no targeted or promotional policy guidelines In general, there is currently very little real output in the development of AI-plus drugs, and no new AI-developed drug has been approved for market Therefore, in the majority of enterprises need to face the lack of output results or poor results in the financial situation of the current situation, enterprises need to position the role of the industrial chain reasonably, choose the appropriate innovative business model However, although the current status quo of AI-plus pharmaceutical research and development is not very optimistic, but there are still many challenges, but it can be expected that the combination of AI-plus drug research and development is bound to be the future development trend of the pharmaceutical industry, in the future it will be a subversive change in the field of medicine