Technology Offers a “Snapshot” into the Future of Genetic Engineering
Screenshot of Snapshot software
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The first wave of genetic engineering technology initially could only be tapped by billion-dollar companies and large university labs. Now, a UK-based company is placing the power of its genetic engineering tech in the hands of thousands of professionals and researchers who can use it for a wide range of applications.
Snapshot is the first commercial model of the human cell that models genes and metabolic reactions to accurately simulate how cells function, according to Macauley Coggins, director of Scarborough Biotechnology. The model is designed as a low cost solution to help companies who implement genetic engineering for a wide range of applications such as developing breakthrough pharmaceuticals to helping train the next generation of genetic engineers.
Coggins said this is ground breaking technology for genetic engineering. Currently, if a company or research lab wants to explore cell functionality, they must spend money and time physically altering the cell function in vitro. With Snapshot, no laboratory equipment is required and thus is much cheaper, he added.
“Because this is an in-silico model of human metabolism, it is much cheaper to use given that the most common way to explore cellular metabolism is to genetically engineer them which requires expensive equipment and staff trained to use them,” said Coggins. “Our model has been designed to be as simple as possible to use and is all self-contained. Other models, on the other hand, may, for example, require several programs or packages to get the model running.”
He added that the technology has a number of uses to improve health and wellbeing.
“We believe Snapshot is going to make the world better in a lot of different ways, from aiding in improving bio-processes, such as optimising production of proteins for pharmaceuticals, to boosting life science research by offering precision modeling of how a cell functions,” said Coggins. “It’s also simple and intuitive to use that it could serve as a teaching aid for biology students. In fact we will be releasing educational documentation bundled in to snapshot which will teach about genetic engineering and its applications.”
According to Coggins, Snapshot is different because it can accurately predict the quantity of each metabolite involved in a reaction in grams. Current technology only offers a limited picture on a reaction and how it produces a metabolite.
Snapshot can give a company producing pharmaceuticals, for example, a much more accurate idea of not just what type of metabolite they are producing, but predict accurately how much they can produce. Furthermore snapshot can highlight specific genes associated with with reactions that produce target metabolites. This is a game changer as it will show companies what genes to target to produce as much as possible and therefore increase production of new cutting edge pharmaceuticals.
Snapshot’s current model includes under a 100 genes, but eventually the company wants to scale this up to over 1000 genes by early 2019.
Currently, the technology is only available as software, but company engineers are also working on a custom micro-controller board for even faster performance.
Snapshot is the first commercial model of the human cell that models genes and metabolic reactions to accurately simulate how cells function, according to Macauley Coggins, director of Scarborough Biotechnology. The model is designed as a low cost solution to help companies who implement genetic engineering for a wide range of applications such as developing breakthrough pharmaceuticals to helping train the next generation of genetic engineers.
Coggins said this is ground breaking technology for genetic engineering. Currently, if a company or research lab wants to explore cell functionality, they must spend money and time physically altering the cell function in vitro. With Snapshot, no laboratory equipment is required and thus is much cheaper, he added.
“Because this is an in-silico model of human metabolism, it is much cheaper to use given that the most common way to explore cellular metabolism is to genetically engineer them which requires expensive equipment and staff trained to use them,” said Coggins. “Our model has been designed to be as simple as possible to use and is all self-contained. Other models, on the other hand, may, for example, require several programs or packages to get the model running.”
He added that the technology has a number of uses to improve health and wellbeing.
“We believe Snapshot is going to make the world better in a lot of different ways, from aiding in improving bio-processes, such as optimising production of proteins for pharmaceuticals, to boosting life science research by offering precision modeling of how a cell functions,” said Coggins. “It’s also simple and intuitive to use that it could serve as a teaching aid for biology students. In fact we will be releasing educational documentation bundled in to snapshot which will teach about genetic engineering and its applications.”
According to Coggins, Snapshot is different because it can accurately predict the quantity of each metabolite involved in a reaction in grams. Current technology only offers a limited picture on a reaction and how it produces a metabolite.
Snapshot can give a company producing pharmaceuticals, for example, a much more accurate idea of not just what type of metabolite they are producing, but predict accurately how much they can produce. Furthermore snapshot can highlight specific genes associated with with reactions that produce target metabolites. This is a game changer as it will show companies what genes to target to produce as much as possible and therefore increase production of new cutting edge pharmaceuticals.
Snapshot’s current model includes under a 100 genes, but eventually the company wants to scale this up to over 1000 genes by early 2019.
Currently, the technology is only available as software, but company engineers are also working on a custom micro-controller board for even faster performance.
