[Given the mix-up in the publication date of 2015, I have now deleted the original post. I have appended the comments from the original post to the bottom of this post.]
It's time once again to see how quickly the world of biological technologies is changing. The story is mixed, in part because it is getting harder to find useful data, and in part because it is getting harder to generate appropriate metrics.
Sequencing and synthesis productivity
I'll start with the productivity plot, as this one isn't new. For a discussion of the substantial performance increase in sequencing compared to Moore's Law, as well as the difficulty of finding this data, please see this post. If nothing else, keep two features of the plot in mind: 1) the consistency of the pace of Moore's Law and 2) the inconsistency and pace of sequencing productivity. Illumina appears to be the primary driver, and beneficiary, of improvements in productivity at the moment, especially if you are looking at share prices. It looks like the recently announced NextSeq and Hiseq instruments will provide substantially higher productivities (hand waving, I would say the next datum will come in another order of magnitude higher), but I think I need a bit more data before officially putting another point on the plot. Based on Eric Check Hayden's coverage at Nature, it seems that the new instruments should also provide substantial price improvements, which I get into below.
As for synthesis productivity, there have been no new commercially available instruments released for many years. sDNA providers are clearly pushing productivity gains in house, but no one outside those companies has access to productivity data.
DNA sequencing and synthesis prices
The most important thing to notice about the plots below is that prices have stopped falling precipitously. If you hear or read anyone asserting that costs are falling exponentially, you can politely refer them to the data (modulo the putative performance of the new Illumina instruments). We might again see exponential price decreases, but that will depend on a combination of technical innovation, demand, and competition, and I refer the reader to previous posts on the subject. Note that prices not falling isn't necessarily bad and doesn't mean the industry is somehow stagnant. Instead, it means that revenues in these sectors are probably not falling, which will certainly be welcomed by the companies involved. As I described a couple of weeks ago, and in a Congressional briefing in November, revenues in biotech continue to climb steeply.
The second important thing to notice about these plots is that I have changed the name of the metric from "cost" to "price". Previously, I had decided that this distinction amounted to no real difference for my purposes. Now, however, the world has changed, and cost and price are very different concepts for anyone thinking about the future of DNA. Previously, there was at times an order of magnitude change in cost from year to year, and keeping track of the difference between cost and price didn't matter. In a period when change is much slower, that difference becomes much more important. Moreover, as the industry becomes larger, more established, and generally more important for the economy, we should all take more care in distinguishing between concepts like cost to whom and price for whom.
In the plot that follows, the price is for finished, not raw, sequencing.
And here is a plot only of oligo and gene-length DNA:
What does all this mean? Illumina's instruments are now responsible for such a high percentage of sequencing output that the company is effectively setting prices for the entire industry. Illumina is being pushed by competition to increase performance, but this does not necessarily translate into lower prices. It doesn't behoove Illumina to drop prices at this point, and we won't see any substantial decrease until a serious competitor shows up and starts threatening Illumina's market share. The absence of real competition is the primary reason sequencing prices have flattened out over the last couple of data points.
I pulled the final datum on the sequencing curve from the NIH; the title on the NIH curve is "cost", but as it includes indirect academic costs I am going to fudge and call it "price". I notice that the NIH is now publishing two sequencing cost curves, and I'll bet that the important differences between them are too subtle for most viewers. One curve shows cost per megabase of raw sequence - that is, data straight off the instruments - and the other curve shows cost per finished human genome (assuming ~30X coverage of 3x10^9 bases). The cost per base of that finished sequencing is a couple orders of magnitude higher than the cost of the raw data. On the Hiseq X data sheet, Illumina has boldly put a point on the cost per human genome curve at $1000. But I have left it off the above plot for the time being; the performance and cost claimed by Illumina are just for human genomes rather than for arbitrary de novo sequencing. Mick Watson dug into this, and his sources inside Illumina claim that this limitation is in the software, rather than the hardware or the wetware, in which case a relatively simple upgrade could dramatically expand the utility of the instrument. Or perhaps the "de novo sequencing level" automatically unlocks after you spend $20 million in reagents. (Mick also has some strong opinions about the role of competition in pushing the development of these instruments, which I got into a few months ago.)
Synthesis prices have slowed for entirely different reasons. Again, I have covered this ground in many other posts, so I won't belabor it here.
Note that the oligo prices above are for column-based synthesis, and that oligos synthesized on arrays are much less expensive. However, array synthesis comes with the usual caveat that the quality is generally lower, unless you are getting your DNA from Agilent, which probably means you are getting your dsDNA from Gen9.
Note also that the distinction between the price of oligos and the price of double-stranded sDNA is becoming less useful. Whether you are ordering from Life/Thermo or from your local academic facility, the cost of producing oligos is now, in most cases, independent of their length. That's because the cost of capital (including rent, insurance, labor, etc) is now more significant than the cost of goods. Consequently, the price reflects the cost of capital rather than the cost of goods. Moreover, the cost of the columns, reagents, and shipping tubes is certainly more than the cost of the atoms in the sDNA you are ostensibly paying for. Once you get into longer oligos (substantially larger than 50-mers) this relationship breaks down and the sDNA is more expensive. But, at this point in time, most people aren't going to use longer oligos to assemble genes unless they have a tricky job that doesn't work using short oligos.
Looking forward, I suspect oligos aren't going to get much cheaper unless someone sorts out how to either 1) replace the requisite human labor and thereby reduce the cost of capital, or 2) finally replace the phosphoramidite chemistry that the industry relies upon. I know people have been talking about new synthesis chemistries for many years, but I have not seen anything close to market.
Even the cost of double-stranded sDNA depends less strongly on length than it used to. For example, IDT's gBlocks come at prices that are constant across quite substantial ranges in length. Moreover, part of the decrease in price for these products is embedded in the fact that you are buying smaller chunks of DNA that you then must assemble and integrate into your organism of choice. The longer gBlocks come in as low as ~$0.15/base, but you have to spend time and labor in house in order to do anything with them. Finally, so far as I know, we are still waiting for Gen9 and Cambrian Genomics to ship DNA at the prices they have suggested are possible.
How much should we care about the price of sDNA?
I recently had a chat with someone who has purchased and assembled an absolutely enormous amount of sDNA over the last decade. He suggested that if prices fell by another order of magnitude, he could switch completely to outsourced assembly. This is an interesting claim, and potentially an interesting "tipping point". However, what this person really needs is not just sDNA, but sDNA integrated in a particular way into a particular genome operating in a particular host. And, of course, the integration and testing of the new genome in the host organism is where most of the cost is. Given the wide variety of emerging applications, and the growing array of hosts/chassis, it isn't clear that any given technology or firm will be able to provide arbitrary synthetic sequences incorporated into arbitrary hosts.
Consequently, as I have described before, I suspect that we aren't going to see a huge uptake in orders for sDNA until cheaper genes and circuits are coupled to reductions in cost for the rest of the build, test, and measurement cycle. Despite all the talk recently about organism fabs and outsourced testing, I suggest that what will really make a difference is providing every lab and innovator with adequate tools and infrastructure to do their own complete test and measurement. We should look to progress in pushing all facets of engineering capacity for biological systems, not just on reducing the cost of reading old instructions and writing new ones.
Comments from original post follow.
"the performance and cost claimed by Illumina are just for human genomes rather than for arbitrary de novo sequencing." --Rob
(genome.gov/images/content/cost_per_genome.jpg ) But most of the curve has been based on human genome sequencing until now. Why exclude human, rather than having a separate curve for "de novo"? Human genomes constitute a huge and compelling market. -- George
"oligos synthesized on arrays are much less expensive. However, array synthesis comes with the usual caveat that the quality is generally lower, unless you are getting your DNA from Agilent" -- Rob
So why exclude Agilent from the curve? -- George
"we aren't going to see a huge uptake in orders for sDNA until cheaper genes and circuits are coupled to reductions in cost for the rest of the build, test, and measurement cycle." --Rob
Is this the sort of enabling technology needed?: arep.med.harvard.edu/pdf/Goodman_Sci_13.pdf
My response to George:
Thanks for your comments. I am not sure what you might mean by "most of the curve has been based on human genome sequencing". From my first efforts in 2000 (published initially in 2003), I have tried to use data that is more general. It is true that human genomes constitute a large market, but they aren't the only market. By definition, if you are interested in sequencing or building any other organism, then instruments that specialize in sequencing humans are of limited relevance. It may also be true that the development of new sequencing technologies and instruments has been driven by human sequencing, but that is beside the point. It may even be true that the new Illumina systems can be just as easily used to sequencing mammoths, but that isn't happening yet. I have been doing my best to track the cost, and now the price, of de novo sequencing.
As I mention in the post, it is time that everyone, including me, started being more careful about the difference between cost and price. This brings me to oligos.
Agilent oligos are a special case. So far as I know, only Gen9 is using Agilent oligos as raw material to build genes. As you know, Cambrian Genomics is using arrays produced using technology developed at Combimatrix, and in any event isn't yet on the market. It is my understanding that, aside from Gen9, Agilent's arrays are primarily used for analysis rather than for building anything. Therefore, the market *price* of Agilent oligos is irrelevant to anyone except Gen9.
If the *cost* of Agilent oligos to Gen9 were reflected in the *price* of the genes sold by Gen9, or if those oligos were more broadly used, then I would be more interested in including them on the price curve. So far as I am aware, the price for the average customer at Gen9 is in the neighborhood of $.15-.18 per base. I've heard Drew Endy speak of a "friends and family" (all academics?) price of ~$.09 from Gen9, but that does not appear to be available to all customers, so I will leave it off the plot for now.
All this comes down to the obvious fact that, as the industry matures and becomes supported more by business-to-business sales rather than being subsidized by government grants and artificially cheap academic labor, the actual cost and actual price start to matter a great deal. Deextinction, in particular, might be an example where an academic/non-profit project might benefit from low cost (primarily cost of goods and cost of labor) that would be unachievable on the broader market where the price would set by 1) keeping the doors of a business open, 2) return on capital, and 3) competition, not necessarily in that order. The academic cost of developing, demonstrating, and even using technologies is almost always very different from the eventual market price of those technologies.
The bottom line is that, from day one, I have been trying to understand the impact of biological technologies on the economy. This impact is most directly felt, and tracked, via the price that most customers pay for goods and services. I am always looking to improve the metrics I use, and if you have suggestions about how to do this better I am all ears.
Finally, yes, the papers you cite (above and on the Deexctinction mailing list) describe the sort of thing the could help reduce engineering costs. Ultimately technologies like those will reduce the market price of products resulting from that engineering process. I look forward to seeing more, and also to seeing this technology utilized in the market.
Thanks again for your thoughtful questions.