The completion of the first human genome sequencing more than a decade ago required nearly $3 billion. However, with the development of second-generation sequencing, this price has dropped from several billion dollars to about one thousand dollars. Since the National Health and Safety Commission issued the "Notice on the pilot work of prenatal diagnostic institutions for high-throughput gene sequencing prenatal screening and diagnostic clinical application" at the beginning of this year, the enthusiasm of the second-generation gene sequencing has been rapidly ignited at the industrial and capital levels. .
Bioinformatics analysis is the most explored potential and profitable link
At present, domestic genetic sequencing has formed a clear division of the industry chain: upstream is equipment and consumables suppliers, a small number of foreign investors such as Illumina rely on technology monopoly market; midstream is a third-party sequencing service provider, relying on equipment investment, operation management and terminal maintenance Development, barriers to entry are low; downstream is a bioinformatics analysis service provider with high technical and product scale requirements.
At present, domestic hospitals or research institutions spend a lot of money to buy a sequencer, 70% of which is in the sequencing step. At present, the most fierce competition in the country is the segment of the sequencing service provider. However, with the development of sequencing technology, the difficulty and cost of sequencing will continue to decrease, and data analysis will become the biggest bottleneck. Bioinformatics analysis service is recognized as the most revealing potential and profitability in the industry, but it is still in its infancy.
How to deal with the huge amount of data in NGS is the biggest challenge
NGS brings revolutionary advances in personalized medicine . At the 2015 China Medical Device Summit, Dr. Shi Chenyang, President of Kaijie, Asia Pacific, conducted an in-depth analysis of NGS data automation analysis.
The challenge for NGS is not sequencing itself, but how to get samples and how to handle patient samples? With the development of liquid biopsy technology, breakthroughs have been made in the uptake and processing of samples. So what are the huge challenges facing NGS today? It is not price, not technology, but the processing of huge amounts of data. How to obtain clinical guidance from huge data is the meaning of NGS, and it is also the biggest challenge of NGS.
Dr. Shi cited the US Quest company as an example to point out the necessity of automated analysis of NGS data. Quest is the largest third-party testing company in the United States, with twenty or thirty pathologists explaining the sequencing data and doing pathology reports. Quest believes that according to the growth of sequencing workload, they need nearly 3,000 pathologists to analyze the data, which indicates that the clinical evaluation workload of gene sequencing results increases exponentially, so automated data analysis is an inevitable trend.
Automated data analysis becomes the next hottest business opportunity for NGS
What is obtained from the sequencer is information about genetic changes, but this is not the most valuable for clinicians. Turning the information on the sequencer into a clinical guide is the most valuable to the clinician.
With the development of sequencing technology, automated data analysis has become inevitable. How to automate the analysis of NGS results? The clinical classification and reporting logic of the sequencing results is mainly composed of three steps: detection variation-variation annotation-variation classification. However, all three steps require automated analysis.
Taking clinical variation classification as an example, the current clinical variation classification (associated with disease) can be divided into: no association, no association, no doubt, no association. Variant classification requires more data correlation than sequencing. For example, it needs to be linked to the disease database, treatment database, and patient family history database. The need for multi-domain data correlation makes the classification of classification inseparable from automation. However, many companies in China have mentioned sequencing. The first reaction is to do a sequencer, ignoring the field of automated data analysis. At present, the field of domestic automated data analysis is still in a blank stage.
There are currently different software packages or products available in the US in this area. For China, although these products are imported, it is still a question whether the Western database is suitable for China. From a Chinese perspective, we can use the same technical means to incorporate Chinese patient data into the database to benefit Chinese patients. Therefore, automated data analysis will be the next hottest business opportunity for NGS in China.
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