Biotech Fox

A guy with a passion for writing about biotech and pharmaceuticals

[Biotech Fox @Biotech_Fox]

@PeterKolchinsky @jrkelly @JacobPlieth @bradloncar 1/1 Watching the China biotech trade, I keep coming back to 2008. Not the leverage or the cascade, that part does not map. What maps is the originate to distribute incentive.
A mortgage originator who plans to sell the loan stops underwriting the borrower. An asset built to be out licensed stops being designed for the FDA and starts being designed for the deal. Weak control, favorable population, domestic regulator. Optimize for the readout that closes the term sheet.
The credibility wrapper does the rest. In 2008 it was a AAA stamp. Today it is a marquee pharma in license, a top tier syndicate, a plenary slot. Buyers see the wrapper and skip their own diligence, assuming someone upstream already did it.
The asset still has to perform in the population that got priced in. That is the part no wrapper survives.

[Biotech Fox @Biotech_Fox]

@bradloncar 100% and if we use technical analysis, it's textbook. Weekly closed below the trendline from the April 2025 low, lower high + lower low. 50% retrace of the run sits at ~119, 61.8% at ~106 = the 2024 range highs. A retest of the breakout is healthy, not a crisis.

[Biotech Fox @Biotech_Fox]

@AppleHelix This is an engineering result, not a discovery. No new target, no new mechanism, four known modules assembled well. Which is fine, most drugs are engineering. But engineering capability was never the thing in dispute, so it can't be the evidence.

[Biotech Fox @Biotech_Fox]

The IP argument was never about published papers. Nobody serious claims Chinese labs can't do excellent science, and this is CAS Institute of Zoology in Cell, not a scrappy university lab. The dispute is over trade secrets, departing employees and suspiciously parallel programs. A mouse paper doesn't touch it.

[Biotech Fox @Biotech_Fox]

Great piece as always, Julia. One gap I would push on: the plan is measured on starts and deal volume, but the next five years are when this wave reads out globally. If translation disappoints across multiple companies, do buyers keep paying for China-only data, or walk? And since most of today's assets are engineering on validated targets, the 25% first-in-class goal rests entirely on the basic science funding you flagged. Would love your view.

[Biotech Fox @Biotech_Fox]

@davidycli You didn’t have to say it. When the US gets medians and dysfunction and China gets a best-case “as quick as 4 weeks,” the framing does the work for you. Show comparable medians and distributions and then we can actually compare ecosystems

[Biotech Fox @Biotech_Fox]

@BiotechObserver @AppleHelix You’re arguing against a claim I never made. I never said Lp(a) was clinically validated. I said the genetics were strong, Phase 2 validated pharmacologic knockdown, and clinical outcome benefit remained unproven. Those are three different things.

[Biotech Fox @Biotech_Fox]

I’m starting to see a pretty consistent framing problem in your comparisons. The US gets judged on its worst bottlenecks, median timelines and institutional dysfunction, while China repeatedly gets presented through best-case execution, headline speed and selective examples. Then those asymmetric comparisons somehow become evidence that China is the emerging global leader.

Criticize the US all you want, our clinical-trial infrastructure absolutely deserves criticism. But apply the same analytical standard to China: median timelines, failed programs, trial quality, investigator/site variability, regulatory opacity, reproducibility, global acceptability of the data, capital efficiency and how many me-too programs ultimately create no value.

“China can activate a site in as little as four weeks” is not evidence that China has a superior clinical-development ecosystem any more than one terrible US academic center proves America cannot run trials.

If you want to argue China is structurally better, show comparable distributions across comparable trials. Otherwise this is selective benchmarking masquerading as analysis.

[Biotech Fox @Biotech_Fox]

You’re comparing US median timelines with China “as quick as 4 weeks,” which is basically a best-case anecdote. You cite a 2026 dataset that actually showed the US was faster at getting the first site activated, while conveniently skipping that part because it doesn’t fit the narrative. Australia also uses a fundamentally different regulatory model, so pretending these are clean apples-to-apples comparisons is misleading.

And then you jump from site-startup inefficiency to “clinical trial scarcity will be the biggest bottleneck in AI drug discovery in 36 months.” That’s not a conclusion supported by these data. It’s a prediction dressed up as evidence.

Yes, the US needs to fix contracting, site activation, local review and patient enrollment. Those delays matter enormously,patients wait longer, development costs rise, and promising medicines reach the market later. But we should fix that because it is a genuine problem, not manufacture a China-vs-US narrative using asymmetric statistics.

If China is really structurally superior here, show the median CTA-to-site-activation, site-to-FPI and 75%-site-activation timelines across comparable multicenter trials. Then we can have a serious discussion.

[Biotech Fox @Biotech_Fox]

@BiotechObserver @AppleHelix Saying Lp(a) was ‘never validated’ is too simplistic. It was strongly genetically validated and Phase 2 validated the ability to knock down Lp(a). What was never validated was the clinical-outcomes hypothesis: that lowering Lp(a) reduces MACE.

[Biotech Fox @Biotech_Fox]

@adamfeuerstein Could this be another miss driven by insufficient knockdown? At this point, for straightforward hepatic protein suppression, it’s getting harder to justify ASOs when siRNA can deliver deeper and more durable knockdown.

[Biotech Fox @Biotech_Fox]

The deaths in the Novartis and BMS trials appear to be linked to severe hyperinflammatory toxicity following CAR-T activation/expansion. That is potentially relevant to in vivo CAR-T, where the active CAR-T population is also generated and expands inside the patient, raising a similar question around how tightly peak CAR-T exposure and immune activation can actually be controlled.

[Biotech Fox @Biotech_Fox]

One underappreciated point from CARDIO-TTRansform, buried in Table S3 of the supplementary appendix: eplontersen achieved only 74.3% LS-mean TTR KD at Week 140; median 76.2%, IQR 65.2–85.7%. Hard to conclude that deep TTR silencing on top of a stabilizer doesn’t work when deep silencing wasn’t actually achieved.

[Biotech Fox @Biotech_Fox]

@Jack_O_Meara I suspect how much this has to do with China fast followers

[Biotech Fox @Biotech_Fox]

I’d absolutely pay to watch this debate. 🍿

One of the things I love about biotech is that, unlike many industries, the data ultimately decides who’s right. You can have the best story, the most capital, or the loudest narrative, but sooner or later the clinical results speak for themselves.

China has undeniably transformed the global biotech landscape, but I remain cautious because the evidence still has to earn that confidence. My biggest question isn’t the China-generated data it’s whether those results consistently translate in global development. Many of the highest-profile programs have generated impressive data in China, but comparatively less evidence has been generated in large, multinational studies or Western patient populations. The obesity/GLP-1 field illustrates this well: several China-originated candidates have shown promising results in China, but we’re still waiting to see whether those outcomes are consistently reproduced in broader global trials.

That may change and if it does, the data will speak for itself. That’s the beauty of biotech: in the end, the data not the narrative gets the final word.

[Jack O'Meara @Jack_O_Meara]

for all you biotech corpdev nerds out there

"In chess, the queen is the most powerful piece on the board. Most acquisitions in biopharma are pawn trades and knight exchanges. Some are rook captures. Arrowhead is the queen."

https://t.co/k3BASeH4Zl

[Biotech Fox @Biotech_Fox]

The risk was never “teaching China genetic engineering.” SpudCell being open academic science proves the frontier is already free. What the collaboration transfers is capital, validation, and US market access. That’s the concern, and always was. You’re rebutting a point no one made.

[Biotech Fox @Biotech_Fox]

The Nature Index signal is real, but I’d be careful calling this “academic leadership” without more context. This is based on fractional publication output in selected journals, not normalized impact, clinical translation, first/corresponding-author leadership, or breakthrough oncology contributions. A more useful cut would be original mechanistic/clinical oncology papers, field-normalized citations, translational impact, and actual therapeutic innovation.

[Biotech Fox @Biotech_Fox]

1/3 To be clear, am I happy this data is weak? Of course not. I would love nothing more than to see the same standard of innovation here that a Revolution Medicines is going after, novel biology, hard targets, real first-in-class risk. That helps patients, and patients are the only thing that matters at the end.
My problem is narrower. We are increasingly paying innovation prices for what is really operational and execution arbitrage. Run it cheaper, run it faster, run it against a soft control, license it into a Western wrapper. That is a fine business. It is not innovation, and it should not be priced like it.
Reward the molecule that took a real shot on goal. Do not reward the one that just optimized the trial.

[Biotech Fox @Biotech_Fox]

@PeterKolchinsky @jrkelly @JacobPlieth @bradloncar 1/1 Watching the China biotech trade, I keep coming back to 2008. Not the leverage or the cascade, that part does not map. What maps is the originate to distribute incentive.
A mortgage originator who plans to sell the loan stops underwriting the borrower. An asset built to be out licensed stops being designed for the FDA and starts being designed for the deal. Weak control, favorable population, domestic regulator. Optimize for the readout that closes the term sheet.
The credibility wrapper does the rest. In 2008 it was a AAA stamp. Today it is a marquee pharma in license, a top tier syndicate, a plenary slot. Buyers see the wrapper and skip their own diligence, assuming someone upstream already did it.
The asset still has to perform in the population that got priced in. That is the part no wrapper survives.

[Biotech Fox @Biotech_Fox]

1/2 ASCO 2026 gave two clean examples.
Ivonescimab took the plenary, first China originated drug there in 61 years, OS HR 0.66 in squamous NSCLC. Then read the protocol. China only, a younger and fitter population than a Western clinic sees, benchmarked against tislelizumab rather than pembro. Impressive, but not yet an answer to the question Western practice is asking. One of the lung discussants said as much from the floor.
Sac-TMT is the sharper tell. Kelun ran the China trial in PD-L1 1 percent and up against pembro monotherapy, a control that is genuinely weak across that whole range, and posted a huge PFS number. Merck took the same molecule global and quietly cut the trial to PD-L1 50 percent and up, the one slice where pembro mono is a defensible comparator. Same drug. Two designs. The company that answers to the FDA showed you where the real bar sits.
When the global readouts mature in the population that was actually priced, the gap shows up. That is the margin call. Not politics. Biology.