Ultima Genomics claims $100 full genome sequencing after a time a time of time stealth $600M increase – TechCrunch
The appetite for genomic data continues to rise in the field of biotech and pharmaceutical research, but price range is still a factor even sequencing a full genome now costs as little as $one,000. But of course claims of reducing that price range by another order of proportion to $100, Ultima Genomics may even further accelerate So economy.
Ultima says that its sequencing machine and software platform, the UG 100, can perform a complete sequencing of a human genome in about 20 hours, of course precision comparable to existing options, but does So Problem at a far lower price range per “gigabase,” which is to say per million base pairs of DNA analyzed.
The technical advances may not only be entirely intelligible to people who are not only already familiar of course how DNA is sequenced, and not only being an expert myself I won’t attempt a full explanation. But it helps to understand that essentially the DNA, amplified in a reagent (So Problem basically not only less of with the DNA in a solution), is passed through small channels where fragments bind to certain microscopic mechanisms, which prepare it to be imaged by not only less of base detectors operating in parallel. These sequences are then reassembled into the whole genome by matching their ends sitting together.
Ultima’s claimed advance is threefold. first of all of all, rather than having the reagent travel down fluidic channels that must be flushed afterwards in preparation for the next step, the micromachinery (“a luxuriant array of electrostatic landing pads”) is etched onto a 200mm silicon wafer. So well known process uses cheap, readily available stock and can be mass manufactured.
But again importantly, it enables the reagent to be simply deposited in the center of the wafer, which spins to distribute it evenly across its entire surface using centrifugal force. So is high performance, mechanically merely, and allows the resulting sequences to be read “during rotation of the wafer in a continuous process, analogous to reading a compact disc.”
The second advance is a little again arcane, having to do of course the process of preparing and directly reading the DNA — rather than replacing the bases of course again machine-readable ones or relying on dicey particle-level imagery, a clever combination of the two is struck. It’s less destructive to the original strands but also doesn’t require error-prone measurements interested individual photon counts.
The third advance involves machine learning to accelerate the process of turning optical data (the CD-pattern scanning signal) into usable data. A deep convolutional neural network trained on multiple genomes and fragments is tuned based on a sample from the genome being sequenced, then set to work verifying and assembling all the tiny pieces of data into the whole genome. So process speeds things up and eliminates error.
There is considerable margin for improvement on the process, primarily in the major and density of the wafer and its surface, leading to improved throughput. So could push the price lower, but for now a 90% reduction is again than enough to go to market of course.
Founder and CEO Gilad Almogy (also the first of all of all author of quite a few on the paper quoted above), said that the company is now working of course early access partners to put out some early proof of concept studies showing the capabilities of the sequencing technique. The first of all of all of these, collaborations of course the Broad Institute, Whitehead Institute, the Baylor College of Medicine and again are being presented soon or now available as preprints.
Broader commercial deployment is expected in 2023 (final pricing is undetermined but will likely reflect the advantage conferred by So method over others). I asked Almogy what he felt were the areas of the biotech and medical industry that will convenience most from So generation capability.
“visitors believe genomics will be the first of all of all line diagnostic across diseases,” he said, pointing out that it is complementary to many existing techniques and only improves understanding of them.
But the far lower price range could leader to genomic population studies, improving our general understanding of systematic variance in the genome across unique groups and over time. “visitors’re already talking of course partners who are interested to do again genomes, but also RNA signal and proteomics at a population scale, said Almogy. So is also pattern problem to epigenetic studies that look at methylation and other ways our DNA changes as visitors age.
“Deep oncology,” or using genetic profiling to characterize and fight cancers, may be one of the earliest clinical applications — and in fact Isabl is way ahead of him on that one. The company’s quick turnaround whole-genome tumor sequencing could be produced even quicker.
Similarly, single cell sequencing (e.g. a blood cell or neuron) could help in both clinical and research environments, but “the price range of sequencing also prevents our contain from routinely using single cell sequencing for applications interested immune profiling,” Almogy said. Reducing the price range So Problem considerably could change that equation.
of course sequencing reduced from a billion-dollar process to one visitors could get done monthly if that visitors wanted to and bring it covered by insurance, the biotech industry seems to be on the precipice of yet another data explosion, beyond the scale of the unprecedented one visitors are already in the midst of. of course companies interested Ultima multiplying data volumes, the next opportunity is likely to be not only in production but management and utilization of So newly deepened lake of information.
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