Adam May

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Adam May

Adam May

@A_May_MD

I invest in biotechs. I often tweet about companies I have positions in. Nothing I say should be considered investment advice.

Katılım Aralık 2017
97 Takip Edilen26.3K Takipçiler
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Adam May
Adam May@A_May_MD·
I won't share in depth pitches like $NKTR often (2/year?). Only with really compelling setups. I've got another one now. The market says PoS is VERY low and that upside could be 10x+. Like with $NKTR, I think the data say success is far more likely than the market thinks. The name is $ABVX (Abivax).
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Adam May
Adam May@A_May_MD·
@deathtouch2k @TripleGateCaptl I’ll be able to make an entire career out of this when Seedy19 (obefazimod 50mg tablet) supplants Entyvio as IBD king 😜 😅
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BoredCorso
BoredCorso@TripleGateCaptl·
$ABVX — strong framework, but it's using mgmt's background which seems to be inflated. The 0.3–0.7 (non-NMSC) / 0.7–1.4 (NMSC) ranges depend on thiopurine-treated cohorts: the 1.36 NMSC ceiling is literally Abbas year-5 thiopurine, plus a Kaneko "5× prostate" that I couldn't find in the paper. Thiopurine-naïve UC is ~0.3–0.5 / ~0.4–0.9 → events-to-signal drops well below 10–14. On NMSC: the ABX464-104 protocol (NCT04023396) discloses the N-Glu metabolite is phototoxic at clinically relevant exposure — a real drug-specific BCC/SCC mechanism. So skin cancers aren't purely background, even if manageable. Sources: Abbas 2014 → pubmed.ncbi.nlm.nih.gov/25244964/Kaneko 2024 → pubmed.ncbi.nlm.nih.gov/38592255/Proto… (NCT04023396) → cdn.clinicaltrials.gov/large-docs/96/…
deathTouch@deathtouch2k

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.

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Adam May
Adam May@A_May_MD·
@ezmoneymonty @deathtouch2k @TLS_Invests I think they can commercialize it. I don’t think they have to. VRNA was getting comically, ridiculously low credit. They had little choice. But they did show that in the modern era a tiny biotech can go it alone in a huge mass market indication.
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Monty Capuletti
Monty Capuletti@ezmoneymonty·
@A_May_MD @deathtouch2k @TLS_Invests You think this is a VRNA situation where they have to commercialize it first? It’s always a base case but here you’d have to change the management team. And you can’t evaluate “strategic alternatives” anymore (those were the days).
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deathTouch
deathTouch@deathtouch2k·
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.
deathTouch tweet mediadeathTouch tweet media
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Adam May
Adam May@A_May_MD·
@deathtouch2k @TripleGateCaptl You joke but I could currently cure every single case of NMSC ever associated with every Obefazimod clinical trial ever run in under an hour. Put me on the label, I’ll treat all the Obe patients for free!
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Adam May
Adam May@A_May_MD·
@RoryNgu18662505 @RNAiAnalyst It 1000000000% was a Hy’s Law case. Is there like a conference or course series they sign you drones up for where you learn these ridiculous one-liners? It. Was. A. Hy’s. Law. Case. Period. Please consider escaping the cult if this is what people have led you to believe.
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ClinicalTrialInvestor
ClinicalTrialInvestor@RoryNgu18662505·
@A_May_MD @RNAiAnalyst It wasn’t a Hy’s law case as the patient had a pre existing condition. Even the FDA lifted their hold and allowed enrollment to continue. Their data has been peer reviewed by experts in the industry including the NEJM. It’s time to move on and allow $NTLA to help people.
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Adam May
Adam May@A_May_MD·
So uhh, that new $NTLA publication that just dropped discloses that 15% of Lonvo-Z patients had liver enzyme elevations...Mostly within the first 6 weeks...the same pattern that we were seeing with the smaller sample size in ATTR before the Hy's Law case... AFAIK they did NOT disclose these liver AEs before🤔
GIF
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Adam May
Adam May@A_May_MD·
This is why I’m less worried about the open market price here. IMO this will be a multiple bidder scenario, meaning the final valuation will ultimately be based primarily on a premium to the value of the 2nd highest bidder, with little impact from something like the 50DMA. This one is simple enough that expect pharma(s) to get it right.
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deathTouch
deathTouch@deathtouch2k·
@A_May_MD @TLS_Invests Either the market gets it right, or one person senior enough within pharma BD gets it right. Either/or works.
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Rudy
Rudy@RudyResearch·
Holy fuck
deathTouch@deathtouch2k

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.

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Adam May
Adam May@A_May_MD·
The market mispriced $ABVX by >1,000% going into the induction readout with existing data almost mathematically proving it was going to hit. It’s only mispriced by 50-80% this time! The market consistently gets this “do the work on your own” stuff wrong until a press release and company presentation crams the truth down its throat. I’ve seen this movie before!
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Tyson S.
Tyson S.@TLS_Invests·
@deathtouch2k My bird brain understands based on a few tweets by some people on X, why is the market having so much trouble with it? It's not that deep, feels like they are way overcomplicating it because it's a new MoA.
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Adam May
Adam May@A_May_MD·
I’m not aware of any drug that confers NMSC risk via sub clinical photoxocoty…none. Not that I know everything, but as a dermatologist I do have a decent grip on these things. NMSC risk tends to come from BLATANT photo toxicity, or immunosuppression, very clearly neither happening here. Even still, is 4 vs 1 really a meaningful signal? Especially in the context of the cases that had *prior* NMSC already, and or exposure to drugs with known NMSC risk? Regardless, it’s something that doesn’t merit too much disproportionate attention/debate. The FDA as a near unanimous rule does not hand out black boxes for NMSC. Black box or no is really the question that matters for ABVX as a stock. Entyvio as the king of IBD has non-NMSC warnings on label… So while my read on the data is that there’s very likely no NMSC signal here, I’m not sure the NMSC part of this is really worth debating too intensely. Not a black box threat even if you think it’s real, and thats all that really matters to the stock right now.
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BoredCorso
BoredCorso@TripleGateCaptl·
Appreciate the pushback - and you're right on the placebo arm. Our back-calc from the disclosed headache IRs, the PY gap is ~1.5x (≈142 vs ≈92 PY), not 2x. PY-adjusted that's 50mg 2.82 vs PBO 1.09 /100P -narrower than 4-vs-1, but not balanced. But the comparison we'd actually point to isn't vs placebo — it's 25mg vs 50mg. Both near-identical PY (≈135 vs ≈142), same screening protocol: 1 case vs 4 (0.74 vs 2.82 /100PY). The dropout confound doesn't have an impact here. On phototox, it's obviously not causing acute rash, but could be promoting keratinocyte NMSC. Why/how those showed up after months, I don't know.
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Adam May
Adam May@A_May_MD·
The study was appropriately randomized. It was powered to detect meaningful differences in COMMON events (50% remission versus 10%). It was NOT powered to detect differences in very RARE events (1% nNMSC vs 0%). This is a very simple concept and your inability to comprehend it while repeatedly raving about how the “randomization failed” betrays the fact that you have absolutely no idea what you’re talking about.
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financebully
financebully@financebully·
@deathtouch2k the fda makes its decisions primarily based on concurrent, randomized registrational data. look into the regulatory precedence for chronically dosed i&i therapies—post-hoc modeling to hand-wave away data that a sponsor doesn't like doesn't usually sway them.
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Adam May
Adam May@A_May_MD·
@biotechboogaloo @adamfeuerstein Hated it at $90 18 months ago and the people who were disingenuously pumping it at those levels. No problem with it now, but many of its cultists still hate me 🤷🏻‍♂️
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Adam Feuerstein ✡️
Adam Feuerstein ✡️@adamfeuerstein·
$ABVX $NKTR $VKTX $NTLA
Bill Ackman@BillAckman

An update on Pershing Square USA, Ltd. $PSUS:   Since its IPO on April 29th, PSUS has deployed nearly 85% of its capital in 12 companies including Amazon, Microsoft, UBER, Meta, Brookfield, Restaurant Brands, Fannie Mae and Freddie Mac at prices we believe to be extremely attractive.   The PSUS portfolio, along with the other Pershing Square funds, also includes four new companies, which we will disclose at the time of our second quarter report.   As a result of our investment activity over the last six weeks, we believe the PSUS portfolio is now invested in a number of the highest quality durable growth companies in the world, which are trading near their all-time lowest valuations.   Furthermore, as of this moment, PSUS is trading at a ~20% discount to the net asset value (NAV) of its underlying holdings so a buyer of the stock at today’s price is acquiring the current portfolio at a double discount. We believe the PSUS discount to NAV has emerged due to short-term technical factors related to the IPO that should moderate over time.   Pershing Square management and affiliates are all-in, having acquired more than ten million shares or $500+ million of PSUS in the IPO and in the market thereafter. 
In summary, we believe PSUS and its portfolio holdings represent an extremely attractive bargain at today’s share price and we have put our money where our mouth is.

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Adam May
Adam May@A_May_MD·
@TripleGateCaptl your premise that the drug arms even show a meaningful imbalance in NMSC to begin with is faulty. If you look at 50mg alone you see 4 vs 1 cases. But although the starting sample sizes were ~equal, severely disproportionate early dropouts in the placebo arm (66% early dropout vs only 18% on the drug arm) likely makes the PY capture on the 50mg ~2x higher. That would make 4 vs 2 cases perfectly balance on a PY basis…meaning a SINGLE extra event on the placebo would have balanced the signal perfectly, exposure adjusted. This is not even *remotely* a signal. Comparing 4 to 1 is not valid in this case due to dropout imbalance. Then, if you add in the 25mg arm, which only had 1 case despite also having likely close to double the PY exposure capture…you’ve essentially closed the gap. There is no NMSC signal to explain to begin with, but we can be confident there is no clinically relevant photo toxicity signal here either. I can tell you from experience, drugs that are clinically phototoxic are NOT SUBTLE, and we would have known about a significant “rash signal” from obefazimod *years* ago…the (5-7 year long) P2 was mostly in Poland/Eastern Europe after all - not a lot of leeway for phototoxic drugs in those folks! I’m not sure what you refer to as “clinically relevant” doses for that preclinical phototox study, but keep in mind that although the P3 studied 25 and 50mg doses *much* higher doses of 100mg, 150mg, and 200mg of obefazimod were used in prior studies. If 25/50mg were phototoxic, we would know. That signal would not be subtle. So we can take solace in that, but again, once you take note of the PY exposure differences in these arms, you realize there is no NMSC signal needing explained in the first place (especially factoring in the very long P2 study with no such signals).
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deathTouch
deathTouch@deathtouch2k·
Thank you for the thoughtful response. You’re right they saw phototox at high preclin levels, but our understanding is it was mainly rash, only seen in one model and not others, and at doses higher than what is tested in humans. Actually, we think the reason why NMSC incidence jumped between Ph 2 and Ph 3 was a function of implementing protocol that went well above and beyond past trial screening criteria and is now much more sensitive to detecting incidental cases. There was an imbalance between PBO/25mg and 50 mg, adjusted for patient years, but we think it’s more likely than not to converge closer over time. SOC is that UC patients already get screened for skin cancer by a derm yearly given elevated risk so nothing really changes in practice regardless of if there’s an elevated rate long term or not. We would expect a warning at most, not a BB. To iterate on this, using non-thiopurine is an excellent test-case. Let’s take your stated non-thiopurine ranges as given (no source provided): 0.3-0.5/100 PY non-NMSC and 0.4-0.9/100 PY NMSC. Using the floor of the midpoint of each range as the background IR rate (0.4/100 PY non-NMSC; 0.6/100 PY NMSC) and assuming your stated non-thiopurine values also have documented 7000 PY behind them, this same framework says we need to see a total of 12 non-NMSC events and 15 NMSC events before the statistics are supportive of the claim that the true obefazimod IRs are respectively elevated vs your non-thiopurine only backgrounds with greater than 50% probability. These non-thiopurine IR midpoints tell you to expect 1.6 non-NMSC and 2.7 NMSC in 450 PY Part 2 data, respectively; meaning you would need to see an additional 8 to 9 non-NMSC over and above the background 1 or 2 before the true obefazimod non-NMSC IR has a greater than a coin-flip chance of being elevated above your non-thiopurine non-NMSC background. Likewise, you need to see 8 to 9 additional NMSC over and above your expected 2 or 3 non-thiopurine background NMSC events before the true obefazimod NMSC IR has a greater than a coin-flip chance of being elevated above your non-thiopurine NMSC background. Dropping the weight of your non-thiopurine priors from 7000 PY to 3500 PY, the same framework says we need a total of 10 non-NMSC events and 13 NMSC events before we could conclude that the true obefazimod IRs are respectively elevated vs your non-thiopurine only backgrounds with greater than 50% probability; that is, you would need to see an additional 6 to 7 non-NMSC over and above the background 1 or 2 before the true obefazimod non-NMSC IR has a greater than a coin-flip chance of being elevated above this weaker non-thiopurine non-NMSC background; likewise, you need to see 6 to 7 additional NMSC over and above your expected 2 or 3 non-thiopurine background NMSC events before the true obefazimod NMSC IR has a greater than a coin-flip chance of being elevated above this weaker non-thiopurine NMSC background.
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Adam May
Adam May@A_May_MD·
@Archimedes20311 Were you under the impression that it is possible for that stock to go *down* ever?
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Archimedes
Archimedes@Archimedes20311·
Why is $SYRE up? $SNY $TEVA data far more robust
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Adam May
Adam May@A_May_MD·
Appreciate your concern. You don’t think we should be tracking high rates of liver enzyme elevations in HAE given that this platform has had multiple high grade liver events including a Hy’s law case and a fatality in the only indication where they actually have a respectable sized safety dataset?
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Dirk Haussecker
Dirk Haussecker@RNAiAnalyst·
@A_May_MD Seriously, Adam, you are wasting your time and risking serious $ on a future of medicine that $ntla is leading.
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Adam May
Adam May@A_May_MD·
@TripleGateCaptl Yep, just like the ATTR program did at this sample size before they got the drug into more people and started getting grade 4s + a fatality
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R̶e̶t̶a̶r̶d̶ Biotech Gambler
It's hard trusting banks and investment firms when they come out with these type of price targets lol... It takes some absurd level of stupidity to put out PT like these 👇👇 $NTLA
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