[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
. 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
. 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 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
, 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
.)
Synthesis prices have slowed for entirely different reasons. Again, I have covered this ground in many other
, 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
.
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
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
, 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.