CellSyde

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CellSyde

CellSyde

@CellSyde

Memes x Molecules x Markets

Inscrit le Haziran 2026
6 Abonnements1 Abonnés
BSS
BSS@barinder_sangha·
Why did $ABVX spend half its primer defining cancer background rates? Because they already have the data. Management rationally only frames these benchmarks because they know upcoming blended safety rates will land safely within them. Expectations anchored.
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CellSyde
CellSyde@CellSyde·
Well would you look at that, the smartest people in the room were right!
Adam May@A_May_MD

🚨$ABVX just quietly dropped new slides again! Aside from showing a much better/clearer discussion of data/expectations and a clear goal to handhold the market with the upcoming part 2 dataset, these slides give us another key insight: $ABVX is finding the same expected background nNMSC/NMSC rates as @deathtouch2k and I have discussed. nNMSC/100PY expected range: 0.3-0.7 ↪️Obe's rate so far: ~0.59 NMSC/100PY expected range: 0.7-1.4 ↪️Obe's rate so far: ~0.79 And those are just for the 50mg doses...the Obe rates get further diluted massively if you were to include the 25mg dose levels, suggesting that the overall population is likely on the low end of expected cancer incidence. (Note the the calculations can change slightly once we get exact numbers of PY of exposure). So, even just looking at the 50mg dosing patient years, and not including the Part 2 data that might further reinforce safety, $ABVX is getting the word out that their EXISTING cancer event rates are ALREADY well within EXPECTATIONS...the market is clearly waiting for the Part 2 data before coming to this conclusion...but I personally don't see why we need to wait. These data are very clear. I continue to see no evidence of a "cancer signal" here, and I find the double digit stock price to be an absolute STEAL. $ABVX would very likely (IMO) have at least temporarily cracked $200/share on their absolutely unprecedented maintenance update without this (bogus?) "cancer scare". Those of us in the weeds have been able to see that the "cancer scare" was noise from the beginning...the company of course will be slower in reaching the market to get that word out and make people understand it, but IMO that's where we are heading. I would predict that stock price will follow!

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CellSyde
CellSyde@CellSyde·
@TOWiU2 @Taintslapp12283 At least they haven’t got an anal abscess and bronchitis - ain’t nobody got time for that!
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CellSyde
CellSyde@CellSyde·
@AnotherKoreanX It’s ok they’ll probably wish NMSC on you, because they think it’s so deadly.
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Just Another Korean
Just Another Korean@AnotherKoreanX·
If you send me death threats via DM because you think I've been jinxing $ABVX, I will gladly stop... NOT
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CellSyde
CellSyde@CellSyde·
@ipollit77 @RNAiAnalyst Tell me you don’t know what basal cell carcinoma is, without telling me you don’t know what basal cell carcinoma is 🤡
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Ipollit
Ipollit@ipollit77·
@RNAiAnalyst Is this parody? What kind of ridiculous questions are these? Cancer is a serious issue in general. Maybe you should think about the MOA instead?
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Dirk Haussecker
Dirk Haussecker@RNAiAnalyst·
$abvx would you rather be diagnosed with basal cell carcinoma or moderate ulcerative colitis?
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CellSyde
CellSyde@CellSyde·
$ABVX bulls before and after maintenance
CellSyde tweet mediaCellSyde tweet media
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CellSyde
CellSyde@CellSyde·
@alex__pitti Just send them a link to Adam’s Yet Another Value Podcast episode, which addresses everything.
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SaaS hole $adbe
SaaS hole $adbe@alex__pitti·
@CellSyde no cancer clustering and no evidence of immunosuppressant in phase 2
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SaaS hole $adbe
SaaS hole $adbe@alex__pitti·
what does $abvx twitter think
SaaS hole $adbe tweet media
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dough
dough@semodough·
$ABVX Truist Healthcare Conference Call - 1:00 PM ET: Biotech KOL Call on Inflammatory Bowel Disease; Digesting ABVX’s Data - Greg Renza
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CellSyde
CellSyde@CellSyde·
@chaotropy @A_May_MD And why didn’t they complete? Because they were in agony compared to those on Obefazimod!
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Chaotropy
Chaotropy@chaotropy·
Following up on @A_May_MD's observation: The placebo arm in $ABVX's Phase 3 ABTECT Maintenance trial had a much lower completion rate, around 34%, compared to roughly 79% for obefazimod 25 mg and 82% for 50 mg. I estimated accumulated patient-years over the 44-week phase. Patients who discontinued early contribute their average exposure time, based on three modelled patterns of discontinuation timing: front-loaded, uniform, and back-loaded. The actual pattern is unknown, and it may differ between arms. Under these assumptions, the placebo arm shows substantially lower total patient-years than the active arms. So event counts per patient could be misleading without adjusting for the actual accumulated patient-years per arm. Nevertheless, the 25 mg and 50 mg arms are very close to each other, so this won't explain any difference in malignancies between these groups. These are modelled estimates only, since exact per-patient exposure times are not disclosed. Disclosure: long $ABVX.
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Adam May@A_May_MD

Yes, small sample size but he’s also making the fallacy of equating equal sample sizes (patient number) to equal AE capture. Sure, the number of patients in the placebo arm was roughly equal to the 50mg arm, but 66% of the placebo arm patients dropped out of the study before completion, versus only 18% of the 50mg arm!!! This means the PATIENT YEAR sample from the placebo arm is likely ~half that of the $ABVX 50mg arm’s patient year sample. So, the placebo arm should naturally be EXPECTED to have a lower rate of cancers, even with the same starting “sample size”, and even with A DRUG THAT DOES NOT HAVE CANCER.

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CellSyde
CellSyde@CellSyde·
Brilliant @YetAnotherValue episode with @A_May_MD - required listening if you’re going to claim Obefazimod causes cancer $ABVX
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CellSyde
CellSyde@CellSyde·
@basadomente @TOWiU2 It’s such an important point. People assume the placebo arm has the same number of patient years and make unfair comparisons.
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basame
basame@basadomente·
since we got a lot of slop posters on $ABVX, I was inspired by my own tweet to add my own to the mix. enjoy: Under reasonable assumptions, due solely to treatment time imbalance, a 5:1 drug:placebo NMSC ratio was the SINGLE MOST LIKELY OUTCOME in ABTECT maintenance. The setup. ABTECT re-randomized induction responders 1:1:1 to placebo (n=192), 25mg (n=193), and 50mg (n=195) for 44 weeks (~0.85 years). Placebo patients relapsed fast — only 34% completed vs ~80% on drug. To estimate exposure: completers contribute the full 44 weeks, dropouts ~half on average. That gives ~100 person-years for placebo vs ~295 for drug combined. Drug patients contributed ~75% of total exposure time (295 / 395). The model. 6 NMSC cases occurred. If all 6 were background events (age, prior skin cancer, prior immunosuppression — not drug-driven), how would they distribute across arms? Binomial(n=6, p=0.747). Each event independently "lands" in the drug arms with probability proportional to exposure time. Result: 5:1 was the most likely outcome. P(5 drug, 1 placebo) = 35.3% — the mode of the distribution. P(≥5 in drug arms) = 52.8%. A coin flip. [graph 1] The dose split. Within the drug arms, 5 cases split 1:4 between 25mg and 50mg. Exposure was nearly equal (~146 vs ~150 PY), so this is ~Binomial(5, 0.5). P(4+ in one arm) = 19.7% one-sided — like flipping a coin 5 times and getting 4 heads. Unusual but not remotely significant. Two-sided p = 0.375. [graph 2] Total NMSC count. We modeled expected background NMSC using claims-based incidence data (Rogers 2015, Muzic 2017), adjusted for UC risk and prior immunosuppression. Expected events for a trial of this size and duration: ~4.9. Observed: 6. P(≥6) = 37%. The total count is barely above expectation. All cancers. Same logic applies to all 8 cancer cases (7 drug, 1 placebo). Under Binomial(8, 0.747), the most likely outcome is 6:2 at 31.1%. The observed 7:1 is the second most likely at 26.3%. P(≥7) = 36%. Caveat. This is a simplified model meant to illustrate the effect of differential treatment time on event allocation. It uses published epi parameters and standard binomial statistics. It does not prove obefazimod is safe — you can't prove a negative from 6 events — but the observed pattern is exactly what you'd expect from the trial design alone.
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basame@basadomente

@grok conduct a Monte Carlo simulation to determine the likelihood that $ABVX would see a 7:1 imbalance in cancer cases between drug and pbo groups purely due to chance. Take into account background rates of cancer, as well as differences in time in treatment, age, pre-existing histories, and prior treatment histories between the two groups. Make no mistakes

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BioMedicalRx 🧬 🇺🇸 ✝️
Whether I do or not (no opinion), my post was simply a response that’s it’s BS that any counter opinion gets treated as personal affront. I also, like many on here have likely been burned when hype and groupthink enter the equation. No causation obviously but something to consider.
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Andre-ACGT
Andre-ACGT@Andre_AGTC·
$ABVX I was challenged by Adam. Here is my response $ABVX peak rev per Stifel is 3.3B >Obe is approvable due to good efficacy and oral convenience >Potential ADCOM and warning in the label similar to JAKs >Launch slower due to highly competitive field but to progress well
Adam May@A_May_MD

@Andre_AGTC You’re so bad at this it hurts (unless of course, as my new theory suggests, you’re a troll - in which case, you’re incredibly good at what you do).

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BioMedicalRx 🧬 🇺🇸 ✝️
How dare you give insight about $ABVX that does not fit the 💯 bull agenda! Great data thus far but in my experience doesn’t always end well when the cult vibe kicks in. When the same message needs to be stated daily and the army attacks any counter narrative it’s a 🚩. Neutral here but BS that you are taking heat simply since you aren’t “falling in line”. At a minimum, people should appreciate hearing an opinion that makes them investigate their conviction further vs being attacked.
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