Long-read #NGS obeys Wright's Law.

For every cumulative doubling in sequence data generated across its install base, @PacBio has been able to lower (consumables) costs by roughly 30%, as shown below.

What could this imply about the future of long-read #sequencing?
First, let's acknowledge a Catch-22. Does PacBio need to (a) derive knowledge from platform utilization to lower sequencing costs or (b) lower costs first in order to unlock greater platform utilization?

At present, we believe it's more of the latter. Why?
PacBio's HiFi chemistry and Sequel II optics are relatively nascent (2019). This suggests a lot of near-term headroom left for optimization in these areas.

It's crucial that all long-read users, not just the top 1%, have access to this innovation.

PacBio has a demonstrated history of 'field-upgrading' systems, meaning that labs don't need to shell out $1 million of CapEx to access best-in-class OpEx. Instead, they can pay a 5-10% premium to remain at the forefront of throughput, accuracy, and cost.

In our view, this strategy is not only customer-friendly, but also means more capital is spent on generating HiFi data (not buying systems), which should drive consumables costs down even faster in a virtuous cycle.
Granted, consumables are just one part of the total cost-equation. With the Sequel IIe, PacBio collapsed compute time for HiFi by 70% and storage costs by 90%, again suggesting that the next-leg of cost-declines may be chemistry/optics.

With all of this out of the way, let's flip back to the chart (below) to imagine what demand may look like if, indeed, PacBio is able to scale HiFi like we think they can.

Let's start easy. What happens if PacBio's install base converges to the current Sequel IIe?
Presently, it costs ~$3,600 to generate a (Q50*) human genome on Sequel IIe. Using Wright's Law, this implies an immediately-addressable market of ~90K genomes.

What could this mean for consumables revenue?

*Q50 = 99.999% accuracy (AKA Phred Score)
If we take the definite integral from today's base (16,000 genomes) to 90,000, we get roughly $360 million in consumables sales. But, let's not stop there. What happens if costs fall to $1,000 for a HiFi genome? Then what?

(This forecast runs on units, not time.)
Using the same approach, a $1,000 HiFi genome yields a market for ~1.6 million genomes, or $2.6 billion in consumables sales, as per Wright's Law. Now, where might those genomes be coming from?

(Again, this is a forecast/estimate.)
In our view, long-read sequencing is vastly superior to short-read across a large and growing number of clinical applications. We believe large swaths of the clinical market will migrate to long-reads, provided that costs continue to fall.
The beachhead clinical market(s) include: pediatric oncology and rare disease, differential diagnoses of neurological disorders, hereditary disease testing, and carrier screening. We think all of these could immediately benefit from the switch.
HiFi also could improve cancer tissue profiling, provided samples are fresh-frozen and not formalin-fixed. This may require Sequel systems to move close to the point-of-care. Or, someone could come up w/ a clever chemical hack). It's something to think about.
Moreover, many large-scale research applications, such as population sequencing, we think could majorly benefit from the added clarity, again provided that costs continue to fall. Together, these applications (and many others) amount to millions upon millions of genomes.
Final Note:

This is a work in progress and we may change final numbers around before publishing something more comprehensive. Critique/feedback welcome.

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More from @sbarnettARK

20 Oct
Besides #immunotherapy, how can #CRISPR be used to treat cancer?

Researchers at @CNIOStopCancer just published an exciting proof-of-concept showing how CRISPR can delete cancer-causing gene fusions, selectively killing cancer cells.

I'll elaborate.

First, let's discuss what gene fusions are. As shown below, fusions result when two genes crash into each other and fuse together.

The resulting protein product is a hybrid. It has some features of Protein A and some of Protein B.

This usually is very bad.
We know that cancer-causing (#oncogenic) fusions have been found in nearly all cancer types. They're more common in pediatric cancers, but still are present in as many as 15-20% of adult cancers.

If present, fusions often are the main drivers of tumor growth.
Read 12 tweets
24 Sep
Interesting, Exact Sciences ($EXAS) is halted and spiking up ~15%, likely because of what's going on at the Cowen liquid biopsy conference. I will provide updates.
This is the first time, to my knowledge, Exact has seriously discussed multi-cancer liquid biopsy instead of just colorectal cancer screening via Cologuard. They presented preliminary data evaluating a blood-based multi-cancer test.
The cohort was relatively small, but showed sensitivity of ~85% (true-positive rate) and specificity of ~95% (true-negative rate). This is definitely the highest sensitivity I've seen from a test like this, but also the weakest specificity. Granted, this is early data.
Read 4 tweets
24 Sep
Rapid whole genome (🧬) sequencing (rWGS) is one of the most exciting (and benevolent) collisions of #AI and #genomics I can think of.

rWGS can diagnose a critically ill child in minutes where previously it took years.

A few years ago, Illumina ($ILMN) and Rady Children's Hospital (@RadyGenomics) collaborated to offer sequencing services for diagnosing critically-ill infants and toddlers.

Roughly 70% of rare diseases are genetic and they can take five years to diagnose.
As sequencing costs dropped and #AI got faster, this collaboration became Project Baby Bear: a pilot study for rWGS's diagnostic yield, clinical utility, and health economics in practice.

Several innovative companies joined Rady's in creating a rapid diagnostic pipeline.
Read 14 tweets
22 Sep
Hi, @7MaxxChatsko --

I agree with a lot of what you've laid out above. However, I think I should clarify some parts of my thread and offer counterpoints to a few of yours. I'm always game to trade notes.

I disagree that the DNA sequencing market is worth $10 billion. Today, it’s less than that. Should Illumina (a) drive unit prices lower (w/ super resolution, see below) & (b) help customers up the platform upgrade cycle to realize bleeding-edge OpE...

…that the market could be worth much more. I’ll cede that this position isn’t ideal because, as you point out, the vastest TAM is within clinical genomics. Still, investors could be ‘headed for the exits’ because their time horizons may not be long enough.
Read 18 tweets
21 Sep
Illumina ($ILMN) Acquires GRAIL: Pros, Cons, & Questions

Earlier today, Illumina announced its intent to acquire cancer-screening company GRAIL for $8 billion, marking its most direct foray into clinical #genetics.

Here's what we think:

🔗: businesswire.com/news/home/2020…
I'll begin with some positives (✅).

GRAIL's test (Galleri) is being evaluated in some of the largest clinical studies within genomics. Three of these studies are ongoing:

PATHFINDER (n=6,200; Ends Jan 2022)
STRIVE (n=99,481; Ends May 2025)
SUMMIT (n=50,000; Ends Aug 2030)
I'm basing timelines off of the study completion dates (see below). I'm doing this because I believe the secondary outcome measures are more relevant to commercialization and/or reimbursement, as is the case w/ STRIVE, for example.

Read 37 tweets
21 Sep
It’s now official: Illumina is acquiring GRAIL for $7.1 billion in a cash + stock transaction. I’ll be discussing my take as well as the potential pros and cons in a thread later today.

(🔗): google.com/amp/s/www.wsj.…
EDIT: $8B* transaction
After listening to the conference call, I think there's an even greater need for a thread. There were many details/questions that I feel went unaddressed. I plan to post a thread later today. Happy to see questions accumulate below so I can address or respond ad hoc.
Read 4 tweets

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