@NatHarooni@snicobio I’m watching Jeopardy—will come back later tonight. Short answer—no, not competitive to PacBio. Likely friends down the road.
@NatHarooni@snicobio Alright, so in theory the QSI platform can enable DNA (or RNA) sequencing on chip. However, I think of it more like a call option and less of a near-term goal. Proteomics is the killer app enabled by the QSI platform. But, as OP alluded to, multi-omics (inc. proteins) on one ...
@NatHarooni@snicobio ... instrument could be an attractive value prop. from a capital outlay point of view, especially for $50K which is achievable for many labs w/o needing to seek a major grant (so speedy sales cycles). Now, back to the main point about sequencing. If you read the patents ...
@NatHarooni@AlbertVilella In my opinion — HiFi reads are the most accurate/complete, but currently are more expensive and lower throughput. Nanopore reads are cheap, fast, and high-throughput, but have a weaker error profile. Both of these descriptors are changing and may not be the case in a few years.
@NatHarooni@AlbertVilella As far as QSI is concerned, it’s a little too early for me to calculate operating costs per run. I’ll update when I know more.
@NatHarooni@AlbertVilella Regardless of how you consider the remaining engineering obstacles, necessary R&D spend, or computational issues—I feel that long-read sequencing (as a class of tech), will outperform short reads on virtually every relevant metric by 2024-2025
@nhawk45@AlbertVilella Hey, @nhawk45 -- Sure, I think I can take some of these. Let's start from the beginning to help explain why certain features of QSI's approach/IP are needed and interesting.
First: Why are proteins the hardest molecules to sequence of the 'big three'? (DNA/RNA/Proteins) ...
@nhawk45@AlbertVilella Here are some of my notes on reasons I could think of, but I'll take a moment to elaborate on some of them.
The proteome is estimated to have the largest 'unit diversity' for lack of a better term. DNA = 20K genes, RNA = 10^5 isoforms, proteins = 10^6 proteofroms ...
@nhawk45@AlbertVilella Proteomic diversity is driven by post-translational modifications (PTM), which is a set of chemical alterations to peptides not dissimilar to how DNA can have #epigenetic modifications like methylation. Combine this w/ the fact that peptides have a 20-letter alphabet ...
Anyone have any opinions on how self-insured employers consider innovative healthcare offerings to pass on to their employees?
As I understand it, by shouldering the financial risk, self-insured employers can curate a list of more relevant benefits ... (1/10)
... thereby avoiding paying out lofty insurance premiums for services that its employees don't use or want. There seems to be a long list of intangible benefits having to do with talent acquisition and retention, but I'd like to understand the cost equations more fully. (2/10)
In the context of multi-cancer screening, I'm skeptical that it could be cost-saving for small or medium-sized employers (<500 employees). Assuming a representative sample of the population, there are simply too few cancers and too many false positives w/ expensive ... (3/10)
@TerraPharma1@hiddensmallcaps Here are some of my thoughts on the Personalis <> Natera tie-up. This is mostly a tech-focused breakdown, so not a recommendation to buy, sell, or hold any security: (bit.do/eyRo8)
First, a bit of background on the details and opinions scattered throughout . . .
@TerraPharma1@hiddensmallcaps Historically, Personalis has focused entirely on serving the biopharma market. These customers aren't as price-sensitive and they have an insatiable appetite for novel discoveries. In our view, Personalis' NeXT platform is a great biopharma product-market fit. Why? . . .
As cash-rich molecular diagnostics companies scale volume and expand menu breadth, there could be an "acqui-hire" shockwave.
These growing companies likely will continue vertically integrating in front (sample prep) and behind (informatics) to gain . . . (1/4)
. . . operating efficiencies on the move up. Or, there could be a weak link in the existing R&D pipeline that needs mending all-of-a-sudden. For example, that extracting bite-size #epigenetic signal from blood would be central to earlier #cancer detection . . . (2/4)
. . . maybe wasn't as obvious five years ago. There seems to be a ton of awesome IP/university spinouts that've gone on to become private companies and/or patents. Along with this, a fleet of brilliant scientists/impassioned people who . . . (3/4)
Interesting that Exact acquired Ashion (private) ostensibly to bring tumor-normal profiling onto the platform. This comes after they got exclusive rights to the TARDIS platform for MRD testing. Both Ashion and TARDIS come out of @TGen, so likely a smoother integration.
Seems to be another form of error-corrected sequencing, which is useful for liquid biopsy applications where tumor fraction (amount of cancer in body) is very low, so this reads through to mutation-based early ...
... detection assays (CancerSEEK) as well as for MRD, where tumor burden is low, but more emphasis on dynamics of the tumor (treatment resistance, clonal evolution, etc) in addition to just quantification of the tumor (ctDNA % up or down).
Companies wishing to sell IVDs must seek pre-market approval (PMA) from the FDA, which can take roughly 200 days. As I understand it, IVD's must be run on FDA-cleared diagnostic equipment, such as the NextSeq 550Dx, which is FDA-cleared and CE-marked (for Europe).
The first day of the conference hasn't disappointed, especially if you're a fan of talking cubes. What is this mysterious object and what sorcery is inside?
See disclosures at the end.
The Tempus One, meant to be carried in a doctor's coat or sat at the bedside, is a physical manifestation of @TempusLabs' genomic and phenotypic data-lake. Oncologists can ask One all sorts of questions regarding their patients, though I'm unsure if it'll (...)
(...) just reflex you to a computer after a sufficiently difficult question. I'm sure we'll learn more soon. Has this sort of form-factor been tried before?
I'm just hoping it has adjustable humor/honesty settings like TARS from Interstellar.
Tomorrow kicks off the JP Morgan Healthcare Conference, one of the most information-dense and exciting weeks for biotechnology. #JPM2021
Though I’ll miss annual lab tours, I’m excited not to have my shoes destroyed amidst all the shoulder-to-shoulder crowds.
Unlike last year, I’m going to try to give a daily news recap once the US trading session closes (inspired by @aurmanARK). My hope is to aggregate input from folks who can offer alternative takes.
We’ve got our #mARKetUpdate webcast on Tuesday, where I’ll be talking more about my recent blog on earlier #cancer detection as well as plans for including community feedback in the forthcoming white paper.
First, let's deconstruct the paper's title: "De Novo Assembly of 64 Haplotype-Resolved Human Genomes of Diverse Ancestry and Integrated Analysis of Structural Variation".
De novo (Latin: "Of New") assembly involves sequencing a genome without the help of a reference.
Assembling a #genome de novo is like solving a jigsaw puzzle without using the picture on the front of the box. You could start with the corners, assemble the edges, and try to fill in the rest using color- or shape-matching methods.
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.
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.
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.
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.
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.
Despite common misconception, we’ve never sequenced 100% of the human #genome.
Since the completion of the Human Genome Project in '03, scientists have struggled to fill in numerous small gaps scattered throughout our 23 chromosome pairs. (1/7)
These gaps, sometimes called dark genes, constitute holes in our understanding of #genetics, evolution, and human disease. Dark genes contain long, highly repetitive stretches of DNA that cause short-read sequencers to make errors.
Many of these errors begin during sample preparation, making it difficult or impossible to overcome with software tools. Last week, researchers published a complete copy of chromosome 8—the first non-sex chromosome to be fully sequenced.
Liquid biopsies for earlier detection are coming, and fast. Over the next few years, we think these screens will bend the cancer detection curve - allowing many types of tumors to be caught earlier than ever thought possible.
But, there's a catch. (1/4)
Not all tumors are lethal, or will cause symptoms. Surgery/treatment on these ultra-slow-growing (indolent) tumors constitutes over-treatment: one argument against screening.
We think molecular prognostics - tests to predict the fate/lethality of tumors can help. (2/4)
This will not fix over-treatment completely, but we think it's very likely to help as well as get better and cheaper with time/data.
In the 📰, I reference a study I talked about in a previous thread on prognostics in esophageal cancer:
It's unwise for multi-cancer, earlier detection companies to deploy large-scale screening programs without upfront, hereditary cancer testing.
The most important input variable for large-scale screening is the incidence rate of cancer in the population.
By incidence rate, I'm referring to the number of persons in a group that is diagnosed with cancer. Intuitively, screening 100,000 people aged 65+ will result in better outcomes and economics than screening 100,000 teenagers. Why?
Cancer incidence increases with age.
However, age isn't the only variable affecting cancer risk.
Hereditary cancer testing, which is based on your individual predisposition to cancer(s) as determined by mutations you inherited (e.g. TP53, BRCA1/2, etc.), is a HUGE determinant of cancer risk.