Aug 4, 2017 4:51am
Curoverse and Veritas co-founder George Church (Courtesy of Veritas)
Veritas Genetics has bought Curoverse to dial up its genome data interpretation capabilities. The takeover combines two George Church, Ph.D., cofounded startups to create a company equipped to sequence and make sense of genomes at scale. Curoverse is the developer of an open-source platform used originally by the Personal Genome Project and, more recently, by sequencing shops including the Wellcome Trust Sanger Institute. Organizations deploy the platform, Arvados, on premise or in the cloud to store data and put them through multi-part pipelines. Some firms pay Curoverse to set up and run the system, enabling it to pull in sales while giving the platform away for free. Boston, MA-based Curoverse will continue to support its customers as an independent subsidiary of Veritas. But with Veritas flush from its $30 million series B and seeking a platform to support its projected data-crunching requirements, Curoverse is now positioned to scale up and expand the capabilities of its platform. “At Veritas, we are building a platform to sequence, and more importantly, interpret hundreds of thousands, and eventually millions, of human genomes per year. This will only be possible by deploying AI and machine learning at scale, which requires data that is produced, stored and managed in a standardized way. Curoverse excels at this capability,” Veritas CEO Mirza Cifric said in a statement. Veritas is currently a long way short of sequencing and interpreting millions of genomes a year. As it stands, Veritas sequences hundreds of genomes a month, Xconomy reports. But if it can lower the cost of its consumer-targeted $999 whole genome sequencing service and, perhaps more importantly, persuade people there is value in knowing their DNA, the number could increase. The Curoverse buyout is intended to equip Veritas for this future by enabling it to build a platform that can handle millions of genomes. If things play out as Veritas hopes, people will come to it for sequencing services and then return repeatedly with interpretation requests to answer questions that come up later. Having computers handle the interpretation work will increase the profitability of the service as it scales. Veritas is paying an undisclosed sum to acquire Curoverse. Read more on
genome sequencing , genomic analysis , genomic data , genomics , artificial intelligence , machine learning , Veritas Genomics , George Church
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Veritas buys Curoverse to boost genomic data capabilities

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Genes carry the information that make you you. So it's fitting that, when sequenced and stored in a computer, your genome takes up gobs of memory—up to 150 gigabytes. Multiply that across all the people who have gotten sequenced, and you're looking at some serious storage issues. If that's not enough, mining those genomes for useful insight means comparing them all to each other, to medical histories, and to the millions of scientific papers about genetics . Sorting all that out is a perfect task for artificial intelligence . And plenty of AI startups have bent their efforts in that direction. On August 3, sequencing company Veritas Genomics bought one of the most influential: seven-year old Curoverse. Veritas thinks AI will help interpret the genetic risk of certain diseases and scour the ever-growing databases of genomic, medical, and scientific research. In a step forward, the company also hopes to use things like natural language processing and deep learning to help customers query their genetic data on demand. It's not totally surprising that Veritas bought up Curoverse. Both companies spun out of George Church's prolific Harvard lab . Several years ago, Church started something called the Personal Genomics Project, with the goal of sequencing 100,000 human genomes—and linking each one to participants' health information. Veritas' founders helped lead the sequencing part—starting as a prenatal testing service and launching a $1,000 full genome product in 2015—while Curoverse worked on academic strategies to store and sort through all the data. But more broadly, genomics and AI practically call out for one another. As a raw data format, a single person's genome takes up about 150 gigabytes. How!?! OK so, yes, storing a single base pair only takes up around two bits. Multiply that by roughly 3 billion—the total number of base pairs in your 23 chromosomes—and you wind up with around 750 megabytes. But genetic sequencing isn't perfect. Mirza Cifric, Veritas Genetics’ cofounder and CEO, says his company sequences each gene at least 30 times in order to get a statistically significant read of what that person's gene actually is. "And you gotta keep all that data, so you can refer back to it over time," says Cifric. That's just storage. "Everything after that is going to specific areas and asking questions: There’s a variant at this location, a substitution of this base, a deletion here, or multiple copies of this same gene here, here, and here," says Cifric. Now, interpret all that. Oh, and do it across a thousand, hundred thousand, or million genomes. Querying all those genetic variations is how scientists get leads to find new drugs, or figure out how existing drugs work differently on different people. But cross-referencing all those genomes is just the beginning. Curoverse, which was focusing on projects to store and sort genomic data, also has its work cut out for it in searching through the 6 million—and counting—jargon-filled academic papers detailing gene behavior, including visual information found in charts, graphs, and illustrations. That's pretty ambitious. Natural language processing is one of the stickiest problems in AI . "Look, I am a computer scientist, I love AI and machine learning, and no amount of coding makes sense to solve this," says Atul Butte , the director of UCSF's Institute of Computational Health Sciences. At his former job at Stanford University, Butte actually tried to do the same thing—use AI to dig through genetics research. He says in the end, it was way cheaper to hire people to read the papers and input the findings into his database manually. Related Stories

Veritas Genomics Scoops Up an AI Company to Sort Out Its *DNA*

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Genes carry the information that make you you. So it’s fitting that, when sequenced and stored in a computer, your genome takes up gobs of memory—up to 150 gigabytes. Multiply that across all the people who have gotten sequenced, and you’re looking at some serious storage issues. If that’s not enough, mining those genomes for useful insight means comparing them all to each other, to medical histories, and to the millions of scientific papers about genetics. Sorting all that out is a perfect task for artificial intelligence. And plenty of AI startups have bent their efforts in that direction. On August 3, sequencing company Veritas Genomics bought one of the most influential: seven-year old Curoverse. Veritas thinks AI will help interpret the genetic risk of certain diseases and scour the ever-growing databases of genomic, medical, and scientific research. In a step forward, the company also hopes to use things like natural language processing and deep learning to help customers query their genetic data on demand. It’s not totally surprising that Veritas bought up Curoverse. Both companies spun out of George Church’s prolific Harvard lab. Several years ago, Church started something called the Personal Genomics Project, with the goal of sequencing 100,000 human genomes—and linking each one to participants’ health information. Veritas’ founders helped lead the sequencing part—starting as a prenatal testing service and launching a $1,000 full genome product in 2015—while Curoverse worked on academic strategies to store and sort through all the data. But more broadly, genomics and AI practically call out for one another. As a raw data format, a single person’s genome takes up about 150 gigabytes. How!?! OK so, yes, storing a single base pair only takes up around two bits. Multiply that by roughly 3 billion—the total number of base pairs in your 23 chromosomes—and you wind up with around 750 megabytes. But genetic sequencing isn’t perfect. Mirza Cifric, Veritas Genetics’ cofounder and CEO, says his company sequences each gene at least 30 times in order to get a statistically significant read of what that person’s gene actually is. “And you gotta keep all that data, so you can refer back to it over time,” says Cifric. That’s just storage. “Everything after that is going to specific areas and asking questions: There’s a variant at this location, a substitution of this base, a deletion here, or multiple copies of this same gene here, here, and here,” says Cifric. Now, interpret all that. Oh, and do it across a thousand, hundred thousand, or million genomes. Querying all those genetic variations is how scientists get leads to find new drugs, or figure out how existing drugs work differently on different people. But cross-referencing all those genomes is just the beginning. Curoverse, which was focusing on projects to store and sort genomic data, also has its work cut out for it in searching through the 6 million—and counting—jargon-filled academic papers detailing gene behavior, including visual information found in charts, graphs, and illustrations. That’s pretty ambitious. Natural language processing is one of the stickiest problems in AI. “Look, I am a computer scientist, I love AI and machine learning, and no amount of coding makes sense to solve this,” says Atul Butte, the director of UCSF’s Institute of Computational Health Sciences. At his former job at Stanford University, Butte actually tried to do the same thing—use AI to dig through genetics research. He says in the end, it was way cheaper to hire people to read the papers and input the findings into his database manually. But hey, never say never, right? However they accomplish it, Veritas wants to move past what companies like 23andMe and Color offer: genetic risk based on single-variant diseases. Some of America’s biggest dangers come from diseases like diabetes and heart disease, which are activated by interactions between multiple genes—in addition to environmental factors like diet and exercise. With AI, Cifric believes Veritas will be able to not only dig up these various genetic contributors, but also assign each a statistical score showing how much it contributes to the overall risk. Again, Butte hates to be a spoilsport, but … there’s all sorts of problems with doing predictive diagnostics with genetic data. He points to a 2013 study that used polygenic testing to predict heart disease using the Framingham Heart Study data—about as good as you can get, when it comes to health data and heart disease. “They authors showed that yes, given polygenic risk score, and blood levels, and lipid levels, and family history, you can predict within 10 years if someone will develop heart disease,” says Butte. “But doctors could do the same thing without using the genome!”
He says the problems come down to just how messy it is trying to square up all the different research on each gene alongside the environmental risks, and all the other compounding factors that come up when you try to peer into the future. “It’s been the holy grail for a long time, structured genome reporting,” says Butte. Even attempts to get researchers to write and report data in a standard, machine-readable way, have fallen flat. “You get into questions that never go away. One researcher defines autism different from another one, or high blood pressure, or any number of things,” he says. Butte isn’t a total naysayer. He says partnerships like the one between Veritas and Curoverse are becoming more common—like the data processing deal between genetic sequencing giant Illumina and IBM Watson—because there’s a clear need for new computing methods in this area. “You want to get to a point where you are developing stuff that improves clinical care,” he says. Or how about directly to the owners of the genomes? Cifric hopes the merger will improve the consumer experience of using genetic data, even seamlessly integrating it into daily life. For instance, linking your genome and health records to your digital assistant. Alexa, should I eat this last piece of pizza? Maybe you should skip it, depending on your baseline genetic risk for cholesterol and latest blood test results. Diet isn’t the only area where genomics could help improve your day to day life. Some people are more or less sensitive to over the counter drugs. A quick query might tell you whether you should take a little less Tylenol than is recommended. Cifric thinks this acquisition could position Veritas as a global powerhouse of genomic data. “Apple recently announced that they had shipped 41 million iPhones in a quarter, right? I think in not too distant future, we’ll be doing 41 million genomes in a quarter,” he says. That might seem ambitious, given that the cost to consumers is nearly $1,000. But that cost is bound to come down. And artificial intelligence will make paying for the genome a matter of common sense.

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Veritas Genetics Acquires Curoverse for Undisclosed Sum
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Genome company Veritas Genetics announced that it has acquired biomedical computing startup Curoverse . Financial terms of the deal were not disclosed. Curoverse is building an open-source platform that supports real-time queries of globally distributed biomedical data, efficiently runs machine learning algorithms, and is secure, fault tolerant and scalable. It empowers clinicians and scientists by providing them with unique data and computing infrastructure, allowing them to focus on what they do best: making breakthrough discoveries and delivering real-world care. The company had previously raised $1.5 million in seed funding. “At Veritas, we are building a platform to sequence and, more importantly, interpret hundreds of thousands, and eventually millions, of human genomes per year. This will only be possible by deploying AI and machine learning at scale. Curoverse excels at this capability. Working closely together will not only benefit Veritas but the industry as a whole,” explained Mirza Cifric, co-founder and CEO of Veritas, in an official statement. RELATED ARTICLES

Veritas Genetics Acquires Curoverse for Undisclosed Sum

August 07, 2017
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Veritas Genetics,a leader in whole-genome sequencing, has acquired computing and bio-informatics firm Curoverse for an undisclosed amount. Curoverse provides infrastructure for life sciences companies to manage large datasets, including an open source platform called Arvados. The acquisition isn't totally unexpected, since the two companies have a strong existing relationship. Not only were both companies cofounded by Harvard professor Dr. George Church, but Veritas and Curoverse have worked together on Harvard's Personal Genome Project. "There are very few companies in the world that have the expertise and experience of more than a decade in aggregating genomic data and enabling machine learning," Church said in a statement. "I am pleased to see these two teams work even closer together. They not only share a common technological goal but also a commitment to making this invaluable information actionable and accessible." Veritas offers whole genome sequencing for $999 and delivers results to customers' smartphones. The goal of the acquisition is to use Curoverse's big data expertise to enable Veritas to more easily use artificial intelligence and machine learning to extract insight from that genomic data. "At Veritas, we are building a platform to sequence, and more importantly, interpret hundreds of thousands, and eventually millions, of human genomes per year," Veritas CEO Mirza Cifric said in a statement. "This will only be possible by deploying AI and machine learning at scale, which requires data that is produced, stored and managed in a standardized way. Curoverse excels at this capability. Working closely together will not only benefit Veritas, but the industry as a whole." Through initiatives like Arvados and the Common Workflow Language project, Curoverse has been involved in efforts to standardize the way genomic data is produced and aggregated. Veritas intends to continue supporting the goal of open standards for genomic data. Tags:

Veritas Genetics acquires Curoverse to enable AI push

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Curoverse is a venture-backed company developing computational storage infrastructure for precision medicine driven by genomic and biomedical big data. Curoverse is a major contributor to the Arvados free and open-source software project.

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