Charles Campbell Roberts Profile picture
Sep 15, 2020 4 tweets 2 min read Read on X
Weekly Newsletter (📰):

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) Image
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:

(3/4)

These types of assays already have gotten quite good within cancer types that we find often in localized (early) stages (e.g. thyroid, melanoma). When we start detecting other cancers earlier, we think that prognostic performance could be generalizable, reducing over-treatment.

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More from @CCRobertsARK

Jan 5, 2023
>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.

How does the model work?
Read 19 tweets
Jun 16, 2022
The following paper is one of the most interesting and thoughtful I've read in quite some time.

The authors offer a new framework for understanding if genetic mutations are harmless (benign) or dangerous (pathogenic).

Spoiler: AlphaFold 2 is involved.

nature.com/articles/s4146…
First, I'd like to cite the authors; .@capra_lab, .@rodendm, and .@computbiolgeek. I'm sure they'll correct me if I butcher anything.

I originally stumbled on the paper after reading a thread about it by .@RyanDhindsa, which I've linked below:

Some Background:

The basis of medical genetics is understanding how #DNA mutations (variants) give rise to disease.

Recall that inherited DNA sequence variants can sometimes alter proteins by changing the identity of an amino acid.

This is called a 'missense mutation'. Image
Read 23 tweets
Jan 18, 2022
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.

biorxiv.org/content/10.110…
Read 10 tweets
Dec 16, 2021
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.

Open Acces Link:

pnas.org/content/118/50…
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.

What's methylation?
PDF of HK Model Paper:
pnas.org/content/pnas/1…

I'll summarize my main takeaways from the current paper and end with some of my open questions/concerns.
Read 30 tweets
Dec 3, 2021
@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.
Read 5 tweets
Sep 16, 2021
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.

Please see our general disclosure: ark-invest.com/terms/#twitter
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:
Read 28 tweets

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