National Focus on Precision Medicine In March of this year, China established the Expert Group on Precision Medical Strategy. The National Health Planning Commission and the Ministry of Science and Technology held several meetings to demonstrate the initiation of the Precision Medical Plan. For a time, institutions and associations related to precision medicine all over the country have sprung up, such as the Precision Medical Research Center, which was established by the top three hospitals such as Peking Union Medical College Hospital and West China Hospital of Sichuan University. Forums and projects related to precision medicine are also in full swing, such as the 4th Bio4P International Summit Precision Medical and Smart Health Forum held in Hangzhou, and the total genome sequencing of a total of 1 million people conducted by Huaxi Hospital. It is reported that the Chinese Academy of Sciences The Beijing Genomics Institute and several large institutions are already launching a similar million-person genome-wide sequencing program. On July 29th, in a column of CCTV's "Chao Wen Tian Xia", the news channel made an easy-to-understand introduction to precision medicine for the theme of "focus on precision medicine". Simply put, precision medicine is the use of modern medical methods to develop personalized prevention and treatment options for patients. The program fully responded to the concept of detonating the scientific community and the medical circle in the first half of 2015. However, the story is not over yet. The media reports are filled with various medical concepts and technologies: molecular diagnostics, genetic testing, targeted drugs, and personalized medicine. . . However, these are all “medicalâ€, and where is “precision†going? Where should the “precision†big data and cloud computing be reflected? The core of precision medicine is precision, not medical treatment. Medical itself has its own laws and methods of development. The precise implementation here requires the realization of medical big data , and the premise of realizing medical big data requires the help of cloud computing. However, we must be clear that cloud computing can't solve medical problems, only to find out the problem quickly and accurately. Cloud solutions can neither solve medical problems nor discover big data problems behind medical treatment. The problem that can be found lies in bioinformatics. Whether bioinformatics requires cloud computing to solve clinical problems requires a big question mark. Cloud solutions can help bioinformatics provide solutions, but not a necessity. For example, when we need to solve the problem of eating and drinking, we spend too much time studying the green or red bowl of rice, and using deep or shallow dishes to hold the vegetables. These are the useless things that can't solve the pain points. Nowadays, the current situation of cloud computing in China is like this. On the one hand, cloud computing has not yet achieved sufficient integration and sufficient coverage in various industries. On the other hand, it has not yet achieved sufficient informationization in the traditional medical field. Informatization is not equal to big data Ketan Paranjape, global general manager of life sciences at Intel Corporation, once mentioned in an interview that large and complex genetic data in the collection, transmission, storage, analysis, etc., brought the requirements for computing, Storage requirements, network requirements, including high performance computing. From the perspective of big data collection, the country needs investment here. In the development of China's genetic industry, the most well-deserved investment in this area is the Huada Gene. One of the most intriguing things is that data collection should be a basic scientific research invested by the state, but in China it has become a project for enterprises to undertake. There is no doubt that this pattern cannot be copied and imitated by the company's burning of money to complete the data collection step. In the words of Mr. Li Yingrui, chief scientist of Huada Gene: "Hua Da Gene is doing basic scientific research on the one hand, and transforming the research results of basic science into real products that the public can use on the other hand. We mainly integrate various kinds of products. Platform and technical means to provide the corresponding clinical services to the public. In other words, Huada gene from the upstream to the downstream, from the B end to the C end, from the production and research closed loop, all can be done. Since Huada Gene can complete data collection through general eating, we have to ask a question: What is the nature of big data? The formation of big data must not be done by monopoly giants. The 4V characteristics of big data are Volume, Velocity, Variety, and Value. The data here has a generated process that produces a process that can be acquired. Many Internet giants achieve big data collection by controlling the entry of data, such as Google and Baidu. In the industry, the competition for data portals by various companies has not stopped. Entrances can migrate as technology evolves and people's lifestyles change, from Weibo to WeChat, from the web to the mobile. The control of the entrance can usually be implemented by a control device or by a platform. For example, Apple's mobile phone and Xiaomi mobile phone are the access to control data through the device. The WeChat platform realizes the entrance control of data traffic through the control platform. Devices and platforms in the genetics industry can ultimately achieve two ways of entry-level: devices and platforms. Equipment is required to collect data, and platforms are needed to analyze data. The devices here only have intelligent devices that can be Internet-enabled, so that they can be used to control the entrance of the control device through the era of big data. For example, Illumina's sequencer, if it is just an instrument that produces genetic data, Illumina cannot be a future gene industry giant. Only by having each device access Illumina's online tracking system, Illumina's system can track the sample information of each machine. Once the device is connected to the Internet, all sample and data information can be automatically synchronized to the device-controlled data center. collection. Each device can not only transmit status monitoring data, sample information, but also the usage and geographic location of each device. The collection of these data is the entry of data through the device. Another data entry point is the data analysis platform, where the control of the portal is achieved by processing and analyzing the data. Whether the equipment manufacturers can do this one, the answer is yes, but the cost is very high. One of the key reasons is the personalization and fragmentation of genetic data analysis. The answer to this reason is the platform, where the platform is not a cloud platform. Many people can't tell the difference between the gene big data platform and the gene big data cloud platform. In fact, analogous examples are the Alibaba platform and the Alibaba cloud platform. The cloud platform is only a technical carrier to implement the platform. The real core is not the cloud computing itself, but the implementation of the platform's operation and mode. Therefore, many people understand Qiyunuode is the gene big data cloud platform, and forget that the accurate definition here is the gene big data platform, and the cloud platform is only a technical module to realize online. If the core of Didi taxi is the cloud platform hosting the DDT taxi platform, obviously this is a very wrong understanding. Only by understanding this point, let us look at the help of cloud computing for precision medicine, only to achieve accurate computing carriers. From the point of view of cloud computing for data collection, the greater contribution here is to solve the fragmentation of data. Integrate fragmented resources through the online platform of the Internet to achieve big data collection. From this trend, the development of cloud computing is a process of decentralization. Ultimately, the data collection methods controlled by giants such as Huada Gene will be weakened by the promotion of cloud computing. The gene big data platform with cloud computing as the core will develop rapidly. This is the first phase of achieving precision medicine, and the cloud of data. Cloud computing helps the second phase of precision medicine to achieve data security management. No company can guarantee the security of data. The law of the business world is always the user is king. The user's awareness of data security and personal privacy is human nature, and the user's sensitivity to data security depends on the cost and threshold of maintenance. The safety of genetic data exists from the beginning of data generation, and the specific point in which it receives the attention of users depends on the maturity of the genetic industry. Cloud computing is relatively mature in data security problem solutions. It is specific whether genetic data is applicable. I believe this is a technical issue rather than a moral issue. But one thing is certain: the security maintenance of genetic data must be hosted on a platform with strong third-party attributes, not a data production supplier like Huada. It is difficult to understand that it is difficult for the user to accept the referee and the athlete are the same person, unless the industry is very niche and closed. Incubator Products,Air Circulation System,Lighting Incubator Machine For Lab,Incubator Temperature Controlle Guangdong Widinlsa International Co.Ltd , https://www.widinlsas.com