“We have been able to achieve the main processes of precision medicine within 24 hours, including data collection, analysis, finding the cause, giving personalized targeted drugs, etc. However, the current cost is still too high for ordinary users. â€
In the face of reporters' questions, Li Yadong, general manager of Intel Corporation's Medical and Life Sciences Group Asia Pacific, is frank.
In the field of precision medicine, “24-hour precision medicine†is more like a data steward. But for Intel, this "housekeeper" is not good. How to control product cost? How to speed up the interpretation? Who is the buyer of the product? One question is in front of the Intel related team.
Yang Xu, Global Vice President and President of Intel China
Recently, at the 3rd Intel Life Science Information Technology Forum, Yang Xu, Global Vice President and President of Intel China, gave a time node on the progress of “24-hour precision medical treatmentâ€, namely: “Completed within 24 hours in 2020 The cost of a person's full-gene analysis is reduced to $500."
The origin of the calculation is still the bottleneck of the genetic industry
Why is a data company going to be in the field of precision medicine?
Yang Xu said that precision medicine is a data-driven science and a frontier in the integration of life sciences, medical technology and computing technology. As a data company, Intel can provide technical support for precision medicine in big data, cloud computing, artificial intelligence, and network storage.
Currently, in the field of genetic testing, computing is still the bottleneck. According to Kay Eron, general manager of Intel Medical and Life Sciences Group, there are four major data challenges in the field of precision medicine, which is what Intel is trying to solve.
Data size. The amount of data involved in the genome is terabytes. It is a challenge for many data scientists to achieve smooth and timely transmission and sharing of these data among different users.
Resolution speed. In general, genome-wide analysis takes a few weeks, which is too long for many clinical services, so it is necessary to speed up the analysis of the genome in clinical or outpatient settings.
The security of information sharing. Genetic information is related to people's most fundamental privacy and personal data, so be sure to ensure its security.
The scalability of the data. The explosive growth rate of genomic data has exceeded the speed of Moore's Law. Therefore, the back-end technology of the product needs to ensure that there is sufficient scalability to support the explosive growth rate beyond Moore's Law.
At present, data processing is one of the bottlenecks encountered by Huada Gene. "Our national gene bank now processes 10PB of data per year (higher storage unit, equal to 250 bytes). It is very difficult to handle such a large amount of data, but build a huge computer room, time and energy. Not enough.†Wang Hongqi, vice president of Huada Gene, said that this difficulty is difficult to store on the one hand and difficult to interpret on the other. It is based on this consideration that Huada Gene and Intel have become partners.
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