The Biotech Dodo @BiotechDodo

On June 30, 2026, the NEJM retracted the clinical trial that got a drug approved by the FDA, triggering a $3.7B acquisition by Amgen. The reason: the primary endpoint data was manipulated. Here's how it happened, how it came to light, and who paid the price. 🧵

Biopharma profits aren't guaranteed: they're finite cash flows exposed to patent cliffs, payer pressure, and uncertain pipelines. One number puts it in perspective: the combined market cap of the world's major biopharma companies at $4.3 trillion still trails NVIDIA alone.

If President Trump agrees to a 60-day ceasefire extension based on vague Iranian promises to “discuss” nuclear issues, it’s game over. That pushes the crisis into late July or early August, when major military operations become far less likely ahead of the midterms. Once the military leverage disappears, meaningful nuclear concessions disappear with it. Ballistic missile restrictions will be nonexistent. Iran will get billions in sanctions relief—while repeatedly using Hormuz as a tool of blackmail. Tehran will have won at the negotiating table what it lost on the battlefield.

The fear over AI is palpable. So, it's time for my optimistic take .... Why the AI doom-and-gloom story is missing the bigger picture A lot of people hear “AI” and immediately think one of two things: it’s just Google search on steroids, or it’s a magic machine coming for everyone’s job. Both miss the bigger picture. A job is not one single task; it’s a bundle of tasks supported by a massive, fragmented software stack. Email, spreadsheets, presentations, Slack, CRM platforms, and, in finance, a Bloomberg Terminal, FactSet, and market data feeds. For millions of jobs, the cost of software to provide basic tools for these tasks can run to $1,000 a month, and more for complicated roles. Much of the modern workday is consumed by the friction of this stack: moving data between systems, cleaning spreadsheets, searching for files, and summarizing meetings. AI is emerging as the new interface for enterprise software. Think about the iPhone. It collapsed cameras, GPS devices, and music players into one simple, powerful device. AI is doing something similar for workplace software, turning 10 clunky programs that don't talk to each other into a single conversational prompt. Just as we stopped buying standalone cameras and tape recorders once the smartphone came around, companies will happily pay for an AI layer. It will be far cheaper and eliminate the bloated costs of that fragmented software stack that requires you to perform endless, mundane tasks because these programs do not talk to each other. The immediate fear is that if AI lets three people do the work of five, companies will fire two people. But that ignores economic history. When the electronic spreadsheet was invented, the cost of calculations plummeted. But accounting jobs didn't vanish; demand for complex financial modeling exploded. Accounting clerks became financial analysts, a more in-demand role. Jevons Paradox suggests that making a resource more efficient actually increases total demand for it. By absorbing the drudgery, AI allows the employee to focus on judgment and strategy—making the human element more valuable, not less. In this framework, demand for high-output workers doesn't shrink; it explodes. Does this justify the mind-numbing capital expenditure currently pouring into AI infrastructure? If AI fulfills this promise of enterprise-wide productivity, the investment isn't just justified—it’s a bargain. That said, we are clearly near the peak of a hype cycle, just like the internet was in 1999. But remember: the dot-com crash did not mean the internet was a bust. It simply meant the hype outpaced the infrastructure. After the wreckage cleared, the optimistic predictions about connectivity and productivity were not only fulfilled—they were exceeded. The same path can lie ahead for AI. And instead of the fear that AI will replace workers, it's the joy of replacing soulless busywork, making jobs more fulfilling... and more profitable for employers.

The Economist @TheEconomist

2 months ago

The jobs apocalypse is not yet here. But if governments wait for conclusive evidence before creating a safety-net, it will be too late. Register for free to understand why econ.st/3PHF3N8

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@Uberrenditen Incredible work! Have you made this accessible to the public via TradingView?

Der 100-Jahre-Plan für den Aktienmarkt Wenn du dir die letzten 100 Jahre anschaust, siehst du ein klares Muster: Der Markt wiederholt immer wieder die gleichen Zyklen. Seit der Großen Depression 1930 gab es drei große Abwärtsphasen und drei Aufwärtsphasen . Wir stecken gerade mitten im dritten großen Bullenmarkt. Die schlechten Zeiten (Bärenmärkte) Diese Phasen dauerten meistens etwa 9 Jahre (die Weltwirtschaftskrise von 1930 war mit 12 Jahren eine Ausnahme). Ein typisches Zeichen war, dass der Markt zweimal oben und zweimal unten „anklopfte“, bevor es wieder aufwärts ging. Oft krachte der Kurs bis zu einer bestimmten langfristigen Linie (dem 300er-Schnitt im Monatschart) und startete von dort aus neu durch. Die guten Zeiten (Bullenmärkte) Die ersten beiden großen Aufwärtsphasen dauerten jeweils 24 und 25 Jahre. Das Spannende: Sobald der Markt einmal Fahrt aufgenommen hatte, fiel er fast nie unter eine bestimmte grüne Linie (den 100er-Schnitt). Die blaue Linie (50er-Schnitt) war dabei immer die beste Chance, um günstig nachzukaufen, wenn es mal zwischendurch ruckelte. Warum steigt der Markt so extrem? Hinter jedem Bullenmarkt steckt eine neue Technologie: Früher waren es industrielle Durchbrüche. Dann kam der Internet-Boom. Heute erleben wir den E-Commerce- und Social-Media-Boom. Klar, irgendwann platzen diese Blasen immer, weil die Leute übertreiben. Aber die Technik bleibt! Das Internet ist nicht verschwunden, nur weil die Kurse im Jahr 2000 abgestürzt sind – es wurde zum Fundament für alles, was wir heute nutzen. Der KI-Boom Wir sind jetzt im zweiten Teil des aktuellen Aufschwungs, und der wird von der Künstlichen Intelligenz getrieben. Wahrscheinlich wird diese Blase um das Jahr 2034 platzen. Das wird wehtun, aber danach wird KI das feste Rückgrat unserer gesamten Wirtschaft sein. Im Grunde sind die letzten 100 Jahre eine Kette von Erfindungen, die die Kurse immer höher treiben. Die Abstürze zwischendurch sind nur dazu da, die heiße Luft rauszulassen und Platz für neues Geld und die nächste Technologie zu machen. Was bedeutet das für dich heute? Wenn dieser Zyklus so läuft wie die letzten beiden, könnte der S&P 500 bis auf 17.000 Punkte steigen. Es wird zwischendurch immer wieder Korrekturen geben. Der Zoll-Crash Anfang 2025 war so ein Moment, hat aber die wichtige blaue Linie nicht ganz berührt. Schau auf den RSI-Anzeiger. Wenn der unter 30 fällt, ist das eine Chance des Jahrzehnts. Das ist in 100 Jahren erst sechsmal passiert – und jedes Mal war es der perfekte Zeitpunkt zum Kaufen. Liken, Folgen, Speichern, Kommentieren, Teilen. Danke für den Support 🫶😊🫶

Watching $RGNX data on May 14th. Below commentary by @Dr_Moneyball is helpful context for what bulls need to see.

Dr. MoneyBall @Dr_Moneyball

2 months ago

@BiotechAutist The bar isn't 10% expression. That is just the primary endpoint because that's the level that theoretically should provide benefit based on Becker muscular dystrophy phenotype. The bar is somewhere around 40-50% I would say. Elevydis expression was between 35-54% in later stage

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Really worth the listen!

Patrick OShaughnessy @patrick_oshag

2 months ago

My guest today is Paul Tudor Jones (@ptj_official), one of the greatest macro traders of all time. He correctly predicted the 1987 stock market crash and shorted the Japanese bubble in 1990. For over 40 years, his flagship fund has had a negative correlation to the S&P 500. 100%

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@RyanDetrick Really appreciate your contribution on this platform!

"No one has ever been a success betting against America since 1776 — and they're not going to be a success in the future doing it, either." – Warren Buffett

Doing some work on $XENE today and saw the p-value from their most recent P3……. (p=0.000000000006). Impressive pipeline. Great lead drug. Going after large indications. Plenty of cash. Top of the M&A biotech basket IMO.

@MartinShkreli Nice!! What indication(s) they going after? Actively raising $?

The current bull market is 3.5 years old and up 99.2%. As we've noted many times, once bull markets get past their third birthday they rarely end anytime soon. Over the past past 50 years, 5 made it past their 3rd birthday and those lasted eight years on average.

Stunning charts from GS — big extremes here:

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You can’t ignore the apathetic volume during the last few months but people are still entirely too bearish these days.

Ryan Detrick, CMT @RyanDetrick

3 months ago

Six for Six S&P 500 up six days in a row and up 6%? Above average returns across the board, with a median return of another nearly 11% 3-months later.

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Yes, they tried to scare you again. Last year it was tariffs, this year it was the war. Volatility happens, but we are still in a bull market that likely has years left. We've been saying that on repeat (even when it isn't popular) and are still in that camp today.

@AMeshkati From Evaluate Pharma….”Big Pharma Needs to Find at Least $90 Billion in Revenue to Overcome its Growth Gap Caused by Patent Expirations.” “Over 40% of all pharma revenue faces patent expiration in next 5 years.”

@AMeshkati This is driven by six M&As by pharma worth over $25 billion the last few weeks. Massive patent cliffs facing pharma this decade. It will be a strong performer for several years .

Called my $SLNO shot but oh so wrong on acquirer and valuation. $NIBX is getting a good value here. x.com/firstsquawk/st…

The Biotech Dodo @BiotechDodo

6 months ago

The price action with $SLNO has been very odd and admittedly to the bearish side but I’m going to shoot my shot…. Pfizer buys them for $5B in short order.

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It seems everyone is too bearish equities. Everything has to go “right” to the downside to get continuation. 2026 will likely be a mid teen type return for S&P500.

Macro Charts @MacroCharts

4 months ago

The cost of protection is near the most expensive levels in history. *Is it sustainable? / What happens next?

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