hounclfan22

Let's do a prediction. @btcbabey can tell me if I'm lucky this time? 1. No $abvx deal by the end of June. 2. Data reveals more safety signals. 3. Deal finalized end of year, 130-150 range.

@deathtouch2k $abvx malignancy “Bayes” post = prior laundering. 7k PY UC bg at 0.5/100PY = 35 pseudo-events before seeing drug data. 2 obs non-NMSC/150PY can’t move it. Then “signal” requires >50% odds above UC 95th pct. Late tripwire. Obs pt ests ~2.7x bg. unresolved, not de-risked.

Based on our conversations with the buy side and sell side, one thing is clear: the market is still struggling to define the actual safety bar for $ABVX. Specifically: how many non-NMSC events would ABTECT Maintenance Part 2 need to show before FDA reviewers or sophisticated pharma BD teams should become concerned that obefazimod may have a true carcinogenic signal, rather than background malignancy events in a refractory UC population? We provide our analysis and conclusions below. Said simply: under our assumptions, $ABVX would need to show a malignancy burden far beyond one or two incremental cancer cases before the bear case becomes statistically and biologically coherent. When a drug trial reports a handful of cancer cases, the natural question is: is this a real signal, or just bad luck? A drug study with 150 patients over one year will almost certainly see some cancers — because UC patients get cancer at a background rate even without any drug. In fact, even otherwise healthy people get cancer at a background rate without any drug. The real question is whether the number of cancers seen on the drug is more than we would expect by chance from that background rate alone. Enter statistics: the formal language of separating signal from bad luck. In this case: what is the event burden and pattern that is high enough, coherent enough, and biologically plausible enough to overcome a low causal prior to obefazimod being carcinogenic? This is exactly the kind of question Bayesian inference is useful for answering. Our Bayesian inference model asks a simple question: Given an estimated background non-NMSC incidence rate of ~0.5/100 PY, how many additional non-NMSC events would need to appear in the next ~450 PY of 50 mg exposure before the pooled 50 mg maintenance dataset begins to look meaningfully above UC background? At ~0.5/100 PY, the expected background incidence over ~450 PY is roughly 2–3 non-NMSC events. Our model suggests the upcoming 50 mg Part 2 update would need to show something closer to 10 additional events above background — roughly 14 total non-NMSC events in the pooled ~600 PY 50 mg maintenance dataset — before the posterior begins to suggest a >50% probability that the true obefazimod non-NMSC rate exceeds the upper bound of UC background. We favor a Bayesian inference framework in these cases because it contemplates the data through a lens similar to that of what we believe an FDA reviewer and pharma regulatory teams would look through: exposure-adjusted rates, confidence intervals around those rates, event heterogeneity, organ clustering, baseline UC cancer risk, prior therapy risk, timing of exposure, investigator attribution, and whether the pattern resembles a broader immunosuppressive AE phenotype. Most importantly, with this approach we do not need to assume obefazimod causes cancer. In fact, the causal prior should be low because there is no obvious a priori hypothesis for obefazimod causing cancer, including clean preclinical work, no clustering to a specific cancer type, no broader adverse event pattern associated with impaired immune surveillance, and investigator assessment that the disclosed prostate and breast cancer cases were unlikely related. Thus, the analysis is not whether “observed cancers divided by patient-years is greater than zero.”; that is coarser than the data allows. The question is whether the observed event pattern is adequate to overcome a low causal prior. We estimated background malignancy IRs across an aggregate 7000+ PY based on a synthesis of Colombel et al. (2017), Rubin et al. (2026), D’Haens et al. (2023), Swissmedic (2024), Sands et al. 2026, Abreu et al. (2022), and Sandborn et al. (2019), and arrived at an estimated non-NMSC IR of 0.5, which is the midpoint of the range provided by management in the Part 2 primer deck published earlier today (ir.abivax.com/static-files/7…). We use 0.5/100 PY as the non-NMSC IR as the background prior of our model. Our analysis allows us to use 7000 PY as the weight of that prior probability. Then, we ask how many non-NMSC events need to be observed in the ~450 PY from Part 2 for the aggregate obefazimod non-NMSC IR to indicate that the true obefazimod non-NMSC rate exceeds the UC patient background upper bound with at least 50% probability. We set the PY reported in ABTECT Maintenance Part 1 according to management feedback. An estimated background non-NMSC IR prior of 0.5/100 PY is at the midpoint of the range provided by $ABVX management and implies an expected 2-3 non-NMSC events per 450 PY. Our model suggests that the ABTECT Maintenance Part 2 update for the 50 mg dose would need to show 10 additional events over and above those background events in 450 PY (i.e., total of 14 non-NMSC events) before the pooled 600 PY maintenance dataset (Part 1 + Part 2) for the 50 mg dose to indicate a greater than 50% probability that the true obefazimod non-NMSC rate is greater than the upper bound of UC background rate, when the observed non-NMSC IR begins to possibly be considered elevated above background expectations. Even when we cut the prior probability weight in half to 3500 PY, the conclusions remain unchanged: ABTECT Maintenance Part 2 update for the 50 mg dose would need to show 7 additional non-NMSC events over and above the number of events expected given the background IR before the pooled 600 PY maintenance dataset (Part 1 + Part 2) for the 50 mg dose to indicate a greater than 50% probability that the true obefazimod non-NMSC rate is greater than the upper bound of UC background rate. Said differently, the key risk is not that another cancer event occurs; the UC and IBD literature documents an expected incident rate for non-NMSC at their background rate (0.3-0.7/100 PY). The key question is whether the next ~450 PY expected from the Part 2 50 mg arm is consistent with the drug-driven malignancy hypothesis: repeated non-NMSC events, organ clustering, biological patterning, exposure-duration logic, or a broader immune-surveillance signal. That is what our model tests. If the next cut instead shows low-count, disparate, background-plausible events, the current obefazimod-driven malignancy argument becomes increasingly difficult to sustain. But what about Rinvoq? They didn’t see a big imbalance? This is not a Rinvoq/Xeljanz-style RA safety signal, where a nearly 4,500-patient outcomes study produced a statistically significant malignancy and immunosuppressive AE cluster in line with an a priori safety hypothesis prior. So far, these few malignancy observations are easily explainable by the background rate of UC cancer in this population especially, and mechanistically, there is also no obvious reason to believe obefazimod should be carcinogenic. If anything, Qin et al. (miRNA-124 in Immune System and Immune Disorders - PMC) discuss miR-124 biology in anti-proliferative and anti-fibrotic contexts, though we would not underwrite an anti-cancer effect here. Against the magnitude of efficacy demonstrated by obefazimod to date: ~50% clinical remission versus ~10% placebo, plus large effects on endoscopic remission, HEMI, steroid-free remission, and sustained remission that is life-altering; these non-NMSC events do not appear to alter the risk-benefit equation. We do not think these disclosed data support a black box. A black box for what appears likely to be background artifact would risk causing net harm to patients by creating unnecessary friction around delivery of a novel and highly efficacious therapy. A brief comment on NMSCs: Based on our diligence, including conversations with former FDA review leadership responsible for evaluating new IBD drug approvals, NMSCs are most commonly basal cell carcinoma and cutaneous squamous cell carcinoma. Importantly, these cancers are: 1) very common; 2) very slow growing; 3) very visible; and as a result, 4) very treatable and curable. These cancers are rarely metastatic, and very rarely fatal. There is published evidence that IBD patients appear to be at elevated rates of NMSCs, hypothesized to result from either higher baseline persistent inflammatory processes and/or thiopurine use. In fact, clinical guidelines published in April 2025 following an expert panel from the American Gastroenterological Association Clinical Practice Update provided specific guidance that all adult patients with IBD should follow skin cancer primary prevention practices by avoiding excessive UV exposure, that patients on immunomodulators, anti-TNF biologic agents, or small molecules should undergo yearly total-body skin exam, and that patients with any history of thiopurine use should continue yearly total-body skin exam even after thiopurine cessation. In the cohort study, the incidence of NMSC was higher among patients with IBD compared to controls (IRR 1.64, 95% CI 1.51–1.78). Recent thiopurine use was associated with NMSC (adjusted OR 3.56, 95% CI 2.81–4.50), and persistent thiopurine use was associated with NMSC (adjusted OR 4.27, 95% CI 3.08–5.92). While, prior to our analysis, we were not concerned that the FDA or pharma would view elevated NMSC rates as a major issue, we were concerned that investors might continue to misclassify them as a serious systemic malignancy signal. However, based on recent conversations with other buysiders, we sense the market is beginning to understand that NMSCs are not a meaningful issue here: they are generally detectable, manageable, and already incorporated into the standard-of-care dermatologic monitoring framework physicians use for UC patients. For completeness, we repeat our Bayesian inference analysis as described above but for NMSC. Taking the NMSC background IR of 1/100 PY provided by management today, we expect 4.5 cases in a 450 PY dataset. Our model suggests that the ABTECT Maintenance Part 2 update for the 50 mg dose would need to show 12 to 13 additional events over and above those background events in 450 PY (i.e., total of 21 NMSC events) before the pooled 600 PY maintenance dataset (Part 1 + Part 2) for the 50 mg dose to indicate a greater than 50% probability that the true obefazimod NMSC rate is greater than the upper bound of UC background rate, when the observed NMSC IR begins to possibly be considered elevated above background expectations. In summary: The right conclusion is not that no cancer events occurred, or that no events will occur in the future. They will occur, not only because cancer risk is elevated in UC, but because cancer can occur in anyone, at any time, including otherwise healthy patients. We think the right conclusion is that the events that did occur look explainable by baseline patient risk, common cancer epidemiology, UC biology, and routine screening detection, rather than acting as evidence of an obefazimod-specific oncogenic signal. We think FDA reviewers and pharma regulatory teams are more likely to reach this conclusion than to view the disclosed cases as a coherent obefazimod-specific malignancy signal, making increasingly clear what we believe is a best-in-disease efficacy/risk profile in the lucrative maintenance setting for UC and substantially de-risking the company’s opportunity in Crohn’s. Disclosure: I/we may be long ABVX and may buy, sell, hedge, or otherwise change exposure at any time without notice. Not investment advice or a recommendation. Analysis reflects current views and assumptions based on public disclosures, published literature, and non-confidential conversations, and may change as new data become available. No compensation from ABVX or any third party.

$nvo ZEUS: zilti reduce hsCRP and miss MACE. 1044 events, 95% power for 20% RRR. CANTOS = ~15%. At HR 0.85, ZEUS power falls to ~75%; at HR 0.88, ~coin flip. SOC(SGLT2i/GLP1) thinned the modifiable hazard.

$bcrx at ~4–4.5x EV/sales not fully valued, but misunderstood setup: “decel” is partly acctg/geo noise. HAE not WTA; segment into prophylaxis, BT rescue, RoA convenience, and gene-editing risk tolerance $kalv may be more bearish $ntla

Three heuristics of biotechs: 1. base rate is short biased 2. soft signals matter 3. know the marginal buyers after a catalyst

Hmm

Re: $sepn ~35: SEP-786 already showed human PTH1R PD, but failed UGT1A1-mediated unconj hyperbili. 479 = new chemotype. FIH more abt MAD PK/PD, sCa/PTH dynamics, accum kinetics, bili liability, and calcemic TI are clean. largely priced in

@lcbnuoH Platform play

$RVMD hmm?

@lcbnuoH Welcome back.

those who followed me without reading my tweets will be bagged.

@ElMonoGran42994 @ljy2001green You're talking to a bot.

@ljy2001green That’s usually low profit….and not very smart if you have an edge in a sector. But if you don’t have that edge…best to stay in large caps, yes

$xbi I have to say blocking all posts related to ABVX is unsurprisingly refreshing 😂😂😂. Also confirms narrow focus of BioX …..so quiet

Some of the toxicity has gotten a little too far. Everyone makes mistakes, and we should be able to disagree while remaining civil and constructive. I'm not sure what Stephen's motives are, but let's critique him on substance, not personal background or faith.

@JoseRestonVA Isn't $RNA $NVS DM1 readout overhang for $DYN? HARBOR might hit first with strong vHOT + broader function. Guess you're worried about del-desiran's 2 SAEs + 1 that led to discont? aviditybiosciences.com/sites/default/…

Also started a position in $DYN

@btcbabey Perfect. We'll see how it plays out then.

@JerryLee2248 Yes I will call you lucky because I think youre retarted

Let's do a prediction. @btcbabey can tell me if I'm lucky this time? 1. No $abvx deal by the end of June. 2. Data reveals more safety signals. 3. Deal finalized end of year, 130-150 range.

I dislike this man, but even a broken clock is right twice a day.

@justkissmyRezpe @A_May_MD You're selling calls?

I finished listening to @A_May_MD podcast. I am double down $abvx tmmr

@MartinShkreli This isn't a product issue, it's an arrogance issue. Anthropic researchers, just as much as they hate sdevs, trivialize biological research.

the weird thing is you know they tested this. they have a million top product people. this was the intentional result? how!??!

@RiskInhibitor Any safety concern in ARDS? In LPS acute lung injury model, pulmonary iNKT activation exacerbated ALI. IFNγ/TNFα rose in lung, Gr-1+ monocytes/neutrophils were implicated, and cytokine blockade improved survival. Murine model academic.oup.com/intimm/article…

i know this cant be priced properly because no one ive talked to even know what an iNKT cell is. free alpha #2 riskinhibitor.substack.com/p/inkt-wtf-is-…

@RiskInhibitor Excellent writeup.

never writing anything this long ever again btw

@biofeed before big A, certainly.

Then again if expensive deals are the thing Cogt next

Wake me up when XENE is gone

Anyone else like $mirm?