Nano Bead + AI: Let Liquid Biopsy Go Closer
Not long ago, Southern University of Science and Technology - United States Silicon Valley Apostle joint project settled in Shenzhen, the co-founder of the three doctors from Stanford University and Duke University, Ge Dongliang, Zhang Bo, Guo Ye, and by the American Academy of Sciences Dr. Charles Canter As a consultant. This "luxury technical team" wants to make liquid live examinations closer and closer to China.
Dr. Ge Dongliang introduced that the DNA of some solid tumor cells can be released into the peripheral blood. The main pathways are tumor cell apoptosis and exosomes. Diagnosis of cancer DNA by peripheral plasma or other body fluids is a liquid biopsy technique that can be used as a routine physical examination item. Liquid biopsy technology for early screening of various types of cancers, early detection, and small-scale, controlled and highly effective surgical procedures. The World Economic Forum and Scientific American have listed liquid biopsy technology as 2017 Ten global emerging technologies.
Existing technologies face two major challenges
Tumor DNA can be an effective tool for early diagnosis of tumors, but it must be accurately and sensitively detected. Ge Dongliang introduced that in this field, international scientific research and industry have encountered a key challenge: Existing liquid biopsy technology cannot provide the accuracy needed for early diagnosis when detecting tumor DNA that is present in peripheral plasma.
Because of the unavoidable error of high-throughput sequencing, the current technology is difficult to overcome. Even if the current error rate is technically reduced hundreds or even thousands of times, we can't tell the difference between these accumulated errors and real tumor mutations when used in the early diagnosis of tumors with very high multiplier sequencing. , thus failing to achieve effective early diagnosis.
The primary challenge in the application of liquid biopsy technology is that the concentration and concentration of free nucleic acids in the body fluids of patients is very low, typically only a few nanograms to one or two hundred nanograms per 10 milliliters of blood. Current nucleic acid extraction technologies are One hundred microgram grade, for a small amount of small pieces of nucleic acid material for liquid biopsy, the extraction efficiency is not enough. Since the content and concentration of the free nucleic acid itself are very low, and the free nucleic acid content from the diseased tissue is lower, when the extraction efficiency is insufficient, the quality of the detection cannot be guaranteed. Therefore, there is a need in the world for a comprehensive early screening research and platform for efficiently obtaining free nucleic acid and amplifying cancer information.
International Original Approach to Addressing Key Issues
"Our nano-beads and artificial intelligence patents are specifically designed to solve these two key issues." Ge Dongliang introduced that nano-magnetic beads are a three-layer structure with a very small diameter and a core-envelope-specific modification. It can be completely and efficiently combined with a very small amount of small-scale nucleic acid substances in body fluids, and can be perfectly and effectively released and released in the reverse direction. It can achieve an enrichment of more than 95% for a very small fraction of nucleic acid substances, and thus can capture tumors with a small content. DNA solves the current worldwide problem of low capture efficiency of free nucleic acid.
The identification of mutations in different tumor genes depends on artificial intelligence. Ge Dongliang told reporters that they have established a large database of 35,000 cancer patients' genome information, covering more than 25 types of cancer, and designed a special computer algorithm. Its purpose is to face a large number of complex databases. Heterogeneous collection of genomic phenomena, through the machine self-learning, training computer efficient, high-speed, accurate identification of tumor mutations, distinguishing between suspected mutations, abandon invalid mutations. Such machine self-learning and evolutionary logic, methods and machine intelligent thinking systems can be applied to more unknown detection spaces, thereby completely solving the challenge of genetic heterogeneity of disease detection. Currently in the international field, this method is original.
The joint project has now entered the stage of industrialization. Ge Dongliang said that this cutting-edge “black technology†is not a laboratory paper but a project that can be industrialized. Once this highly promising new technology is put into widespread use, it will greatly improve the national economy and people's livelihood, and will drive the industry scale of the US$100 billion level for the country. (Liu Chuanshu)
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