Meet the New deCODE, Same as the Old deCODE?
When deCODE genetics declared bankruptcy last fall it made a big splash. Geneticists pondered the future of the Icelandic biotechnology company’s one-of-a-kind genetic database and research platform, while investors and creditors wondered if they were going to be left out in the cold.
The initial bankruptcy buzz gave way over the past several months to a steady but relatively unremarkable stream of filings in the United States Bankruptcy Court for the District of Delaware (the case is No. 09-14063). Last week, however, brought a noteworthy docket entry, with the bankruptcy court approving the sale of most of deCODE genetics Inc.’s assets to Saga Investments LLC (pdf) – an investment company whose owners include Polaris Venture Partners, ARCH Venture Partners and genomic sequencing giant (and DTC genomics dabbler) Illumina.
A Holiday Fire-Sale? The sale, as approved by the bankruptcy court, sends substantially all of deCODE genetics Inc.’s assets – including its valuable genetic research engine that is driven in part by its access to its large Icelandic population database – to Saga Investments. As we described back in November, the bankruptcy sale process required a Stalking Horse bidder (Saga Investments) and a sale and auction process that, at least in theory, allowed other interested parties a chance to step in and make a bid for deCODE’s assets. No other bidders came forward, and the sale to Saga Investments was approved in just under two months.
GLR Update: In The Battle for Sequencing Supremacy, is 128 > $10,000?
The biggest industry developments last week were being announced at J.P. Morgan’s 28th Annual Healthcare Conference in San Francisco. The Genomics Law Report covered Illumina’s announcement of its new next-generation genomic sequencing machine (Another Stop on the Road to the $1,000 Genome), the HiSeq 2000, which promises to sequence an entire genome in one week for $10,000. Illumina’s $10,000 price point represents a new commercial sequencing benchmark, but it is unlikely to deter the company’s competitors. Those include sequencing-as-a-service provider Complete Genomics, which followed up Illumina’s announcement with one of its own, declaring that it plans to sequence up to one million human genomes worldwide over the next five years.
I’ve discussed previously the importance of analyzing just what you get when you purchase a whole-genome sequence. Illumina’s $10,000 genome does not include the cost of the machine or the necessary data analysis, whereas Complete Genomics offers human genome sequences starting at $20,000 while providing its own hardware and data analysis. However, as Matthew Herper of Forbes pointed out last week, the real number to pay attention to in Illumina’s announcement may have been 128—the number of new Illumina machines that BGI committed to buy—and not $10,000. As this recent survey of research labs by In Sequence suggests, current or so-called “second-generation” sequencing platforms, including the one utilized by the HiSeq 2000, continue to make inroads into sequencing centers worldwide, posing an obstacle to Complete Genomics and other newcomers attempting to crack the genomic sequencing space that might not be overcome on price alone.
Another Stop on the Road to the $1,000 Genome
The latest stop on the road to the $1,000 genome? San Francisco, CA, where J.P. Morgan’s 28th Annual Healthcare Conference is in full swing. There is an abundance of real-time Twitter coverage from the conference, but certain announcements warrant a more detailed discussion.
The announcement generating the biggest buzz today came from Illumina, Inc., whose CEO Jay Flatley unveiled a new genome sequencing machine, the HiSeq 2000. According to Matthew Herper of Forbes.com, Illumina’s new machine “will decode a person’s DNA in one week using $10,000 worth of materials – five times cheaper than any other competing gadget on the market.” Herper adds that the machines will begin shipping in February with a cost of $690,000 (compared to $500,000 for Illumina’s current model). Illumina’s own product page for the HiSeq 2000 provides more technical details, including coverage (~30x) and read length (2×100 bp). There have also been unconfirmed rumors that the machine will come equipped with an iPhone user interface, a concept that Flatley first pitched at last summer’s Consumer Genetics Show.
If it performs as advertised, the HiSeq 2000 is likely to be a huge hit with large genome sequencing centers, as evidenced by the announcement that the BGI (formerly the Beijing Genomics Institute) has agreed to purchase a whopping 128 of the new sequencing systems. But what, if anything, does the Illumina announcement mean for individuals consumers interested in receiving a complete genomic sequence?
deCODE Declares. Now What?
If you’re a regular reader of the Genomics Law Report – or the Wall Street Journal for that matter – by now you have probably heard the news: deCODE genetics, Inc. has filed for Chapter 11 Bankruptcy protection.
Given deCODE’s recent financial struggles, this latest development is hardly a surprise. Indeed, two months ago, we anticipated this very event when we asked a hypothetical question: “What Happens if a DTC Genomics Company Goes Belly Up?” That’s precisely the question that deCODE’s customers and creditors are asking today.
In our original article, which was initially published in three parts on September 14, 15 and 16 at Genetic Future, we looked at the interplay between the privacy policies of DTC genomics companies and the relevant bankruptcy law statutes, and offered some educated guesses as to how courts and companies would handle the sale of a bankrupt company’s sale of its customers’ genetic information.
The coming weeks will see that analysis tested in Delaware bankruptcy court. In the meantime, there is a lot to unpack in this morning’s deCODE announcement.
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Completing the Personal Genomics Toolkit
The big news buzzing through the world of genomics this afternoon is the publication of a paper in the journal Science announcing the production of three whole-genome sequences at an average materials cost of $4,400. The work was performed by the third-generation sequencing company Complete Genomics Incorporated, along with researchers from George Church’s lab at Harvard Medical School.
The Race for the $1,000 Genome
Erika Check Hayden of Nature’s blog The Great Beyond has an excellent summary of the Complete announcement in which she also attempts to head off some of the inevitable media hype:
Complete’s $4,400 price tag doesn’t include costs for the company’s infrastructure, such as its Silicon Valley data farm and the army of analysts and technicians required to make sense of the data; the company lists more than 60 employees in this paper’s author list. The company is actually selling genomes at $20,000 apiece in minimum orders of five; costs go down as the order size increases. That puts it slightly behind the schedule it set at its launch; the $5,000 genomes won’t be available until next year.
The announcement from Complete Genomics is hardly unexpected. At its launch last fall the company promised that it would deliver $5,000 genomes (and 1,000 of them, not just 3) by the end of 2009.
From a personal genomics standpoint, there is no question that Complete is a viable contender in the race to deliver affordable, individual whole-genome sequences. Spurred by competition from the likes of IBM, Illumina, Pacific Biosciences, Oxford Nanopore and others, the $1,000 genome continues to draw closer. It is no longer a question of if but when that magic number will be attained.
But while the $1,000 genome competition makes for an exciting horserace, the real focus of today’s announcement should be not on how much a genome sequence costs, but on what you can (or cannot) do with that sequence.
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Make Room for Big Blue: IBM the Latest (and Largest) Entrant in the Race for the $1,000 Genome
The quest for the $1,000 genome—viewed by many as the point at which whole-genome sequencing will become cost-effective and widely available—is a fierce competition populated by a cast of start-ups and specialized genomics companies.
The most well-known entrants in the next-generation sequencing market are companies such as Oxford Nanopore, Pacific Biosciences and Complete Genomics; names that are hardly familiar to the average patient or consumer. And the wilder the sequencing claims—e.g., a full genome “for less than $100 in under an hour“—the more obscure, at least for the moment, the company: Halcyon Molecular, BioNanomatrix and NABsys among others.
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Leveraging the Crowd to Understand Your Genome
Earlier this week Peter Aldhous of NewScientist magazine recounted an unusual experience with DTC genomics provider Decode Genetics. In reviewing his genetic data on the deCODEme website, Aldhous uncovered what appeared to be significant and bizarre errors in his mitochondrial DNA. Aldhous turned to Blaine Bettinger, The Genetic Genealogist, for help in diagnosing the problem with his mitochondrial DNA. Bettinger’s response: “This is a strange question, but are you sure this is Homo sapiens?”
Aldous, Bettinger and Decode investigated the problem and ultimately determined that the “errors” in the mitochondrial DNA were actually being introduced by a bug in the deCODEme software interface that allows users to browse their data. (Aldhous carefully points out that the software glitch was a rare one and that it did not seem to affect deCODEme’s disease-risk summaries or analysis.)
More than a simple software error, Aldhous’s experience highlights the complexity inherent in consumer genomes. Translating an individual’s saliva sample into a description of genetically influenced traits and risks is a multi-stage process with potential for error at every step in the chain. Or, as Daniel MacArthur of Genetic Future cleverly puts it, “There’s many a slip ‘twixt spit and SNP.”
Will Funding Break Through the Bioinformatics Bottleneck?
Earlier this month, the NIH announced the renewal of a grant program that awards up to $275,000 over two years to academic institutes, small businesses, non-profits and other groups, to support research aimed at developing new ways of managing, manipulating and interpreting genomic and other biological data. But the utility and necessity of such grants is not entirely clear.
To be sure, the biomedical community has recognized a potential for a “bioinformatics bottleneck” as the cost of genome sequencing plummets and the sheer quantity of raw data rises, potentially without a corresponding increase in the capacity to interpret that data. And the NIH’s focus on funding innovative, “high risk/high impact” research projects is certainly welcome. But it is far from clear that a handful of two-year, $275,000 grants will produce the right type of innovation, on the right time-scale, to put a dent in the problem. And perhaps more to the point, it is worth taking a closer look at whether any amount of public funding would address some of the other issues at the root of the impending shortfall in biomedical informatics and computational biology research and development.
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Whole-Genome Sequencing and Gene Patents Coexist (For Now)
In a recent post, John Conley analyzed the ACLU’s lawsuit challenging Myriad Genetics’ patents on the BRCA-1 and BRCA-2 “breast and ovarian cancer susceptibility” genes. Several readers responded with the same general inquiry: if an individual undergoes a whole-genome sequence analysis, will the individual (or the company providing the sequence) be required to pay royalties to Myriad because the BRCA-1 and -2 loci will have been sequenced?
Although focused on the BRCA genes, the question is broadly applicable to the entire genome sequencing industry: when sequencing all or a portion (e.g., the exome) of an individual’s genome, are individual gene patents infringed upon by either the company providing the sequence or the individual purchasing or requesting it? The answer is not entirely clear, but, at least in the case of Myriad and the BRCA genes, it appears to be no. Or at least, not yet.
Let’s begin with what is not patented, which includes a majority of genes and the vast majority of the human genome. Genes—those stretches of DNA that encode for proteins—make up approximately 2% of the human genome. The estimate of the exact number of genes ranges from between roughly 20,000 to 30,000 and, of those, a 2005 study in the journal Science found that only 20% of human gene DNA sequences are patented (subscription). Although those numbers are certainly subject to change, the reality is that, today, it is likely that less than 1% of the entire human genome has been patented.
Of course, that very small number belies the fact that the genes which have been patented consist of some of the most important identified genes associated with the prediction or determination of human health and disease. The high-profile BRCA genes are an excellent example and thus make for a good case study.
The Genome In Silico and the Future of Whole-Genome Sequencing
In my previous post summarizing last weekend’s conference on Genetics and Ethics in the 21st Century I briefly mentioned Professor John Robertson’s discussion of the “genome in silico.” Using Illumina’s recently announced $48,000 whole-genome sequencing service as an example, Robertson wondered whether the future of whole-genome sequencing lies in converting the genome to silicon storage (in silico) or whether on-demand sequencing of short genetic segments (or even whole genomes) will continue to be done as and when patients present with specific clinical conditions (in vivo). To put it another way, will the patient of the future present his doctor with the equivalent of Illumina’s concept iPhone app or Knome’s USB drive, or will she come prepared to undergo a more traditional blood draw or tissue biopsy.
Following Illumina’s announcement at the Consumer Genetics Show, Daniel MacArthur at Genetic Future speculated that Illumina, in focusing “on the sequence generation side…[was] restricting itself to the least attractive segment of the personal genomics market.” And I agreed, arguing that the bioinformatics portion of the genome sequencing market — interpreting and functionalizing raw sequence data — appeared to be both larger and less well-developed, thus presenting a more promising commercial opportunity.
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