I'm really digging the form factor, off the bat. (2nd) the turnaround time (TAT) is <15 minutes, which will be terrific for accurate data collection while the patient is in the clinic, great for timely tracing.
Point-of-care administration within the work/schoolday also probably good for bringing school populations back online in bigger groups, still involves a nasal swab which when I did it helped me learn about new parts of my nose
Tech is lateral flow (LFIA), which I think is similar to what's in a pregnancy test, a summary of LFIA below
Also, the description says the assay type lacks in sensitivity, which I've described below. Basically, it's less-than-perfect at predicting true positives, so if you were sick, then this tight is slightly less great at being right
Source below (Me)
So cool that the readout is linked to a digital app (#IoT), that can link in to the school/clinic's records, which suggests the data will be easily sharable and analyzable because of the record's (or EMR's) Structure
The cartridge readouts have existing infrastructure to be automatically read by a machine and transferred into digital record, though the article suggests that those machines may be supply-constrained given the anticipated product rate of the company and the demand
Here's a meta-analysis of the performance characteristics of various lateral flow assays (LFIAs) used specifically on COVID-19
After reading this (and I'm still parsing the info), it may be that LFIA tech is currently ill-suited to handle what I mentioned above in my previous comments.
Definitely warrants a deeper dive into the performance characteristics of the proposed test!
Interesting that the article doesn't address specificity in this paragraph, then. But, explicitly states the 97% for sensitivity. Below is what specificity is:
Here's the previous article on this that dealt which the same issue: wsj.com/articles/abbot…
I'm unsure what became of this timeline off the top of my head, but here's a pointer.
Binox isn't up on the government (FDA) EUA page, but here is a link to it anyway (this is for Access Bio, Not Abbott, but also uses LFIA and viral protein target):
If this test is equivalent on the basis of combined antibody specificity of 98.9 % (n=180/182) and (CI:96.1%-99.7%), then in a simulated population of 15,000 (the average public college school size), then...
The true positives and quarantine, the true negatives be retested on intervals, the false positives will enjoy Netflix, and the false negatives are worrisome (potentially).
If they keep going to school, we'll restart this math (and no one else changes disease state), then ...
...and it'll be a cyclical loop that I don't want to punch into Excel at the moment, however, things look like they're going in the right direction.
If tests cost $50 for inventory, but reimbursed (so $0) for those that are symptomatic or have shown a positive contract trace..
Then the cost by an entity is $750,000 upfront, if 50% of people were suggested symptomatic or in contact (or fibbing), and half was reimbursed, then investment is $375,000 to do a volley of tests for a school of that magnitude), w/ perfect claims
So at $5 instead of $50 per test, cuts per student expenditure to ~5% of semester budget to provide daily (school day) testing with results back before you go back home/to dorm/etc
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>90% of Americans over 45 have seen a Cologuard ad this week.
Fewer know of the test's parent company, Exact Sciences (EXAS), whose tests also guide care for the majority of early-stage breast cancer patients in the US.
Today, we released a 5-year model + article on Exact.
Our (base case) 2027 price target is $140 ($49 today). To get there, here's what we believe has to happen:
1. Exact's core business (Cologuard + Oncotype DX) grows on avg. >15% per year thru 2027, reaching $4B.
2. Exact achieves EBITDA positivity in the '23/'24 timeframe.
What we believe must happen (Cont.):
3. Exact uses its earnings to reinvest in its burgeoning pipeline, service its outstanding debt, and maintain its capital equipment.
4. Exact's pipeline, in aggregate, hits >$1B revenue by the end of 2027.
Now that @Quantum_Si has given us a peek under the hood of its protein #sequencing platform (Platinum), we can begin comparing actual results to theory.
A few months ago, I shared this paper that gave a theoretical framework for protein sequencing: pubs.acs.org/doi/10.1021/ac…
The author simulated how different factors, such as the # of readable amino acids (AAs) and the read length, would affect a protein sequencer's ability to unambiguously detect the 20,000 canonical human proteins in our bodies.
That chart is attached below.
I've marked in green where QSI currently stacks up. Based on its recent pre-print (linked below), Platinum can directly read seven (7) amino acids (F, Y, W, L, I, V, and R) with peptide reads that seem to max out around 20 AAs.
A recent publication by Dennis Lo et al applied long-read sequencing (LRS) in the prenatal screening (#NIPT) setting. It's a rather unorthodox technology/application pairing, and it's got me scratching my head a bit.
For context, earlier this year, Lo et al published a convolutional neural network ("the HK model") that enabled PacBio LRS devices to read methylation (5mC) across the entire genome with very high fidelity. This is important later.
@MJLBio@Sanctuary_Bio@Biohazard3737 Sure! I realize I was being a little vague with those statements. Generally, I think you're correct in your interpretation of the importance of P2 (great $/GB, but at a smaller scale) as well as duplex sequencing.
Something that is important to recognize, though ...
@MJLBio@Sanctuary_Bio@Biohazard3737 ... is how product deployment works differently between PacBio and Nanopore, which is partly an artefact of culture and of time in the public markets, in the public markets. I'm not advocating for one over the other with my next statements.
@MJLBio@Sanctuary_Bio@Biohazard3737 PacBio has been a public company for a long time. While the management has changed much since the failed Illumina merger, the familiarity with how to operate as a public company has not.
PacBio is more secretive and only unveils fully built-out commercial products.
I'd like to share my initial reaction to today's Berkeley Lights report. But first, I need to do some housekeeping. I can't comment on stock movements, share financial projections, or debate fair value.
Generally, I respect anyone who's put this much work into a topic. I won't pretend to have a clean rebuttal to every point. In my experience, beyond the hyperbole and hasty generalizations, there is some truth in these types of reports.
I want to soberly appraise those truths.
Also, I'd invite the subject-matter experts waiting in the wings to build off of this thread, add detail, or share their experiences. Ultimately, we're all after the same thing.
I will start with a few concessions and end with a few counterpoints to today's report: