Big data becomes "catalyst" for drug innovation

The 2015 China (Beijing) International Technology Transfer Conference is the most fashionable vocabulary at present Because of its ability to quickly obtain valuable information from various types of data, big data technology is widely used in more and more industries, which has a subversive impact on many industries including the pharmaceutical industry New drug R & D needs big data to support Dr Ding Hongxia, executive director of Yaodu Jingwei information technology (Beijing) Co., Ltd., said that with the continuous popularization of network and information technology, the amount of data generated by human beings is growing exponentially, and the birth of cloud computing has directly sent us into the era of big data Before in the field of medicine, because of the technical bottleneck of data collection and analysis and the lack of people's understanding of the significance of these data, the value of big data has not been really mined In recent years, with the accelerated accumulation of medical data, big data in the field of medicine ushered in a critical moment from quantitative change to qualitative change, which is having a revolutionary and significant impact on life science, clinical medicine, drug research and development, pharmaceutical marketing and other fields Ding Hongxia said that innovative drug research and development has always been a problem faced by all pharmaceutical enterprises As the biological process and drug model of drugs become more and more complex, drug research and development has been in a situation of large investment and low success rate, as well as product line stagnation The average time of a new drug R & D is 15 years, and the average cost is more than 800 million US dollars The R & D industry chain includes the search and digestion of massive R & D data, resource cooperation involving various disciplines such as chemistry, biology, toxicology, pharmaceutics, patent science, communication with regulatory and approval departments, capital investment and withdrawal, selection of industrial parks and many other links 。 However, at present, the overall drug research and development is still in a state of "fighting on their own, fighting alone" Although the whole industry invests a lot of human and material resources year by year, the repetitive work makes the R & D information and R & D resource allocation inefficient, which sometimes even causes fatal damage to a drug R & D project "The application of big data is an important technical support to solve the problems of long drug R & D cycle, high cost and many uncertain factors." Ding Hongxia believes that by using big data, researchers can mine from genomics, proteomics and metabonomics, cooperate with clinical trial data and real world clinical data, and help us identify potential new molecules that are likely to be successfully developed as drugs through predictive modeling, so as to find more effective targets, markers and active substances Quality is verified, and the screening work is more effective in the follow-up animal experiments and clinical phase I ~ III clinical trial data, so as to shorten the whole time of drug development   Not only that, in many other links of pharmaceutical industry chain that can generate data statistics, the use of big data can also play its role: help drug regulatory and approval departments to understand the current situation of drug research and development, approval status, drug use and other information in China and the world, so as to better play their own functions in the work; help market capital to better choose items Objective to invest and withdraw in time; to help biotechnology companies to choose financing more wisely and carry out industrialization; to help industrial parks to select the most promising projects to land, and to provide more promising support "To provide big data support and establish a platform for effective allocation of R & D resources in all aspects of the whole pharmaceutical R & D sector will have an immeasurable impact on the entire pharmaceutical industry." Ding Hongxia stressed "In 2013, the U.S Food and Drug Administration (FDA) approved 26 new molecular entities (NMES), while in 2014, 41 NMES were approved, increasing year by year From 2011 to 2014, the application for listing of new drugs in China also increased steadily " Dr Li Jing, founder of Yaodu Jingwei information technology (Beijing) Co., Ltd., introduced the overall situation of new drug research and development in the world and in China, and stressed that "new drug research and development is a complex system engineering, including pre clinical target identification, drug activity screening, non clinical animal model research, clinical research, etc., and the accumulation of data is indispensable for each link Use At present, the requirements of drug research and development for data services are more and more urgent " Li Jing said that to make drug innovation, literature research must be carried out, and materials such as chemistry, biology, toxicity and clinical research of related drugs need to be studied to master relevant information For example, there are 25-30 new diabetes drugs on the market every year, and the literature of each new drug is about 20000 pages To develop a new diabetes drug, we need to read all the relevant information of the new drugs on the market, but this is about one million pages "It's true that you can become an expert after reading such a large amount of literature, but you won't have time to make innovations This is the biggest contradiction between limited life and R & D " Li Jing believes that for drug researchers, turning huge data such as 20000-30000 pages of literature into 10 pages can not only quickly understand the history, but also quickly respond to future research and development work For drug reviewers, the review opinions put forward will be more "reliable" if they know the relevant information of listed drugs in time through data "Big data provides something that keeps competitors around the world on the same track." Li Jing said that the mission of Yaodu is to build a "comprehensive, one-stop drug R & D information service platform" by using big data technology, to provide refined R & D data for personalized drug R & D, and to allocate optimal R & D resources Yang Dazhou of Zhongkang pharmaceutical information (Group) Co., Ltd shows how to use big data to introduce foreign high-quality drugs into China from the perspective of imported drug registration For imported drugs, the traditional way is the recommendation of foreign acquaintances or intermediaries, but the recommendation of intermediaries will narrow the selection range, and may only screen the varieties of a certain country or individual manufacturers, which will greatly reduce the matching rate, requiring enterprises to provide a more focused selection range It takes time and effort for the R & D department or marketing department of the company to research massive drug information from Google, websites of major companies, etc By using Zhongkang's data resources, we can screen the market growth power of the products according to the sales database, confirm the preliminary information according to the comprehensive drug information database, retrieve the domestic registration acceptance database to understand the product application risk, retrieve the global clinical trial database to evaluate the academic status of the products, retrieve the global listed drug database to select the appropriate targets, so as to help enterprises Select high-quality international cooperation projects Hu Dalong, general manager of Thomson Reuters Life Sciences in China, introduced that big data has the characteristics of "4V" of volume, velocity, variety and value In the era of big data, all institutions are "forced" to make better use of the data available to them In the face of the ownership of a large number of data, the real challenge is the ability to integrate, analyze and interpret data "The pharmaceutical industry's solution to information intelligence is integration." Hu Dalong said that there are many key information in drug research and development, including: drug compounds, synthesis path, chemical reaction, protein, gene sequence, basic information of biological drugs and chemical drugs, global patent information, financial information, competitive intelligence, market research, multi field and multi-disciplinary research and development literature, etc., and through information integration technology (information management and visualization technology), It can make these information produce high value-added applications, such as target determination and certification, lead compound confirmation and optimization, drug research and development path selection, efficient clinical research, intellectual property protection, tracking competitors' activities, strategic planning, etc On the basis of integration, there are four types of data analysis and interpretation: normative analysis, descriptive analysis, predictive analysis and diagnostic analysis According to Hu, data is everywhere Disease data, including disease basic medicine and market data, epidemiological research data, diagnosis methods and information, treatment methods and methods, treatment drug research and development, product pipeline and other data; target mechanism data, including the latest mechanism of action, development of target, distribution of popular hot spots, target mechanism certification, related drug pipeline progress, drug research and development phase Data on biomarkers; data on compounds, including basic research, pharmacology, pharmacokinetics, toxicology, structure-activity relationship of compounds, full synthesis path, literature and patents, animal experimental models and other data; data on generic drugs, including pharmacology and clinical data of original drugs, chemical synthesis, amplification process and other technologies, formula technology development, research on new dosage forms Data, as well as market competitive product analysis, generic drug competition analysis, patent expiration date analysis data, etc The application of big data integration and analysis in the pharmaceutical industry is to select strategic decision-making in the field of treatment, carry out risk assessment of target mechanism development, project investigation of hot varieties and project selection of generic drugs, and control the risk of cooperative transactions and formulate strategies "Due to the intervention of big data technology, the industrial pattern of drug R & D will change Effectively identifying the opportunities and risks will be the key to the success of drug R & D enterprises." Said Hu Dalong