ClearPath

Particular focus on bio, fintech, deeptech and broader vertical AI themes.

[ClearPath @ClearPath100]

$QURE Respectfully, the evidentiary critique overlooks AMT-130’s rigorous design.

Prespecified SAP (aligned via RMAT Type B) used propensity score-weighted/matched external controls from Enroll-HD (n=940 high-dose; covariates including age, CAG, baseline cUHDRS/TFC, motor/cognitive scores; also validated vs TRACK-HD/PREDICT-HD with/without striatal vol. proxies).

High-dose: ΔcUHDRS −0.38 vs −1.52 ext. ctrl at 36 months (75% slowing, p=0.003); TFC 60% slowing (p=0.033); CSF NfL −8.2% ΔBL (neuronal injury biomarker). Dose-dependent miHTT knockdown mechanism was also consistent.

Sham-controlled long-term randomization in fatal neurodegeneration poses HIGHLY ethical barriers (invasive burr holes, attrition).

PS methods minimize confounding; and importantly FDA’s initial alignment + Breakthrough/RMAT reflect RMAT statutory flexibility for unmet need as well as intermediate endpoint (cUHDRS) + supportive biomarker.

The standards must balance rigor with feasibility in a rare, progressive disease.

Truthfully, patient desperation is not the argument, but mechanistic and statistical signals are.

[Zach Brennan @ZacharyBrennan]

Scoop: acting FDA commissioner Kyle Diamantas told rare disease nonprofits yesterday that some major changes are coming in the post-Makary era: No more career staff overrules, and expect more adcomms https://t.co/VdA5kZAotF

[Pavel Prata @pavelprata]

Monthly VC/LP debrief.

What I actually saw in May 2026:

1/ SF is in full gold rush mode again, but history says the current winners won't stay on top forever. Every dominant technology eventually gets surpassed – newspapers, telecom, cable, Google in ads, IBM in computers. In AI the same pattern is already playing out: compute will hit walls, chips get dramatically more efficient, new energy sources emerge, and entirely new model architectures appear. The people feeling left behind today may just be early in a much longer cycle. (h/t @TurnerNovak)

2/ The largest $10B+ funds went from 140–150 collective early-stage deals per year in the SaaS era to 370–400 in the AI era. But the concentration is at the top of the market – top-decile rounds, known founders, proven operators. @kevinhartz calls it "option value": a small check today for the right to lead Series A tomorrow. The average seed round remains territory for EMs.

3/ We might be entering a Zombie VC era. ~85% of 2017–2018 vintage funds still haven't returned 1x DPI after 7–8 years. Median DPI sits at $0.34 on the dollar, while median IRR for the same cohort looks respectable at 11.6%. Paper returns hide the reality. The liquidity window opening over the next two years will be the moment of truth for most of these funds.

4/ @SpaceX IPO might be the single largest DPI event in VC history dropping into the lowest-distribution moment in venture capital history. @foundersfund alone, with an early $20M check in 2008, could return $60B+ (~3000x). When that capital hits LP accounts, it needs to be redeployed and that will circulate a new wave of fundraising for the same funds and fresh allocations from LPs who finally have liquidity to work with.

5/ The @cerebras IPO was the first real data point on crossover returns after two years of everyone writing off the model – both early-stage VCs and late-stage crossover funds made money on the same company, and LP conversations shifted from "do we have any exposure to the winners" to "how do we get into the next one." The same strategy that was declared dead in 2022-2023 got fully rehabilitated by a single exit. (h/t @MeghanKReynolds)

6/ Monte Carlo across 1,391 VC funds: concentrated portfolios (15 companies) and diversified ones (100 companies) produce the same average fund return – 2.44x. But compounded across multiple vintages, diversified wins: 2.25x vs. 1.78x. Concentrated funds carry more variance per fund, and variance drag compounds against you over time. The extreme outcomes (15x+) are almost exclusive to concentrated funds but the probability is tiny either way. (h/t Steve Kim)

7/ EM activity is showing the first real pulse in years. @cartainc logged 78 new US venture funds in the $10M–$100M range in Q1 2026 – a 34% jump from Q1 2025. Still well below the 2022 peak of 147, but the post-winter bottom might finally be in. The managers raising right now are doing it without a favorable macro, without easy LP recycling, and into a market where mega-funds are more active at seed than ever. (h/t @PeterJ_Walker)

8/ 76% of all EM-focused FoFs are American. The entire addressable market for a Fund I or Fund II isn't 132 FoFs – it's roughly 33. The other 100 exist, but Classic and Government-Led FoFs structurally can't anchor an early-stage vehicle: the check size doesn't justify the overhead, and a pension board can't be sold on a first-time manager without a track record. Geography and fund type filter out 75% of the market before the first meeting. (via @murphcapital)

9/ The 10-year fund is structurally mismatched with the assets mega-funds are holding. @SpaceX has been private for 18 years. @stripe for 15. For managers at that scale, @sequoia's move makes sense – open-ended, permanent capital, indefinite horizon. For small funds the logic runs the opposite way: the 10-year horizon enforced as a hard constraint, secondaries at Series C/D as the default exit, actual distributions on schedule. (h/t @credistick)

10/ There are only 3 positions that matter in a startup's cap table story: first investor, most helpful investor, biggest investor. Biggest is reserved for ~10 megafunds. First requires conviction most managers don't have – and LP preferences for concentrated portfolios often push against it structurally. So 90%+ of firms end up competing for "most helpful," which is why every pitch deck has a platform slide and every GP talks about their right to win oversubscribed rounds. (h/t @arian_ghashghai)

Every month I track new fund launches, LP events, market reports, and what's actually moving in VC/LP.

All of it in the @murphcapital newsletter: https://t.co/Wi8pAGQHLB

[DesertDweller_ROAR_4_A_CURE_4_HD @DesertDweller93]

All interested in @uniQure_NV $QURE AMT130, clear your schedule for this meeting today live streamed on YouTube. Looks like @Christina4HD and @KarlMiran will be on the agenda between 1:15-2:15 EST. They get 5 minutes to speak, and panel can ask follow up questions according to the agenda.

https://t.co/BYLWMbGLOD

[ClearPath @ClearPath100]

$QURE Useful perspective on valuation:

In 2019, before any patients had even been treated in the Phase I/II AMT-130 Huntington’s study, uniQure’s market cap reached roughly $3 bln. Today, after years of human clinical data, RMAT / Breakthrough / Fast Track designations, and a broader CNS / gene-silencing platform, the company still trades below $2 bln.

That disconnect is the crux of the bull case.

The market is heavily discounting FDA pathway risk after the agency pushed back on using Phase I/II data vs external controls as primary evidence. That is the gating issue.

But if AMT-130 ultimately secures a viable regulatory path, this is no longer just a single-asset Huntington’s trade. It becomes validation of uniQure’s AAV / miQURE platform in one of the hardest CNS indications in biotech.

That is why, as @peter_mantas has argued, $QURE remains one of the more asymmetric listed biotech setups: binary regulatory risk, but potentially platform-level upside if the FDA path clarifies.

[ClearPath @ClearPath100]

$QURE

[Peter Mantas @peter_mantas]

New link that wasn't on the FDA site yesterday: https://t.co/1prW3aUQqX

[Nassim Nicholas Taleb @nntaleb]

1/n
A physical book is a real object, anchored. If you read a particular edition, you remember not only the contents but the object itself: its cover, typography, smell, even where a passage sat on the page.
Books organize themselves in memory by place --the ancient method of loci.
Digital text does not exist.

[Za @ZaStocks]

Once the AI narrative shifts from “taking everyone’s jobs” to curing diseases, advancing education, improving productivity, etc. watch how quickly sentiment surrounding it changes.

Don’t be surprised when government funding eventually starts flooding in.

Remember, the U.S. government helped fund the railroad buildout and played a major role in the early internet buildout because both were viewed as critical infrastructure.

[U.S. FDA @US_FDA]

FDA is committed to advancing Real-World Evidence use in regulatory submissions across product centers & today updated its list of examples of how RWE has informed FDA's regulatory decisions since 2011. CDRH is now included, along with CDER, CBER & OCE. https://t.co/eeKosGIVJi

[ClearPath @ClearPath100]

You just put SKY in 7U playing in the dirt - that's my point, thanks for hitting it in.

Dad/coach pitch, sure. But he stepped in for three full seasons with the league keeping score, his NfL radar gun doesn't care who's pitching, and he hit the fast pitch better than the slow one, with same pitcher (high dose > low dose). You can't propensity-match an internal split.

Little brother hasn't had an at-bat. He's posting cage numbers - this is exactly what tominersen did before whiffing in the Show. FALCON-HD is live pitching, great.

[ClearPath @ClearPath100]

$QURE The under-discussed story in Skyhawk’s SKY-0515 12-month readout isn’t the data, it is the design.

84 days of real placebo, then everyone crosses to drug. A milder population (incl. Stage 1). Efficacy benchmarked to external natural history, not a concurrent control. That’s a fine Phase 1/2 setup, but it’s not a package that wins US accelerated approval.

The pivotal evidence that could change that lives in FALCON-HD, and its controlled arms are offshore, still enrolling, with topline a long way out.

Meanwhile $QURE’s AMT-130 already cleared the bar Skyhawk hasn’t reached: significant, durable, and FDA-engaged efficacy.

For US HD patients, the math is simple.

One program is at the regulator’s desk.

The other is a placebo washout and an ocean away.

Approving the proven option isn’t impatience. It is truly the only near-term path to a disease-modifying therapy in US.

[ClearPath @ClearPath100]

The analogy is backwards. Toddler-vs-tween implies both are in the cage and we are just projecting MLB.

AMT-130 has actually batted i.e. three years of clinical-endpoint data across motor, cognitive, and functional domains, plus a within-subject biomarker.

SKY-0515 has a swing in the cage, and that is blood mHTT lowering. Projecting impact from cage mechanics is the exact error the field made with tominersen, which lowered huntingtin beautifully and then made patients worse in Phase 3. "Ultimately a higher standard" is a claim about a trial that hasn't read out, and you can't bank prospective rigor, and a higher bar only helps if SKY clears it. A clean RCT that fails doesn't advance it; it ends it.

And note why SKY can run that clean RCT: pill-vs-placebo is trivial to blind; AMT-130's comparator would be sham brain surgery in a fatal disease. The evidentiary "advantage" is largely modality, not virtue - and the same chronic lifelong dosing that makes blinding easy is exactly what creates the open-ended safety risk. Design edge and safety liability are the same coin.

On the undisclosed matching: a real limit on the headline number, but "all the favorables are premised on it" overstates badly. The CSF NfL drop is a within-patient change from baseline - no control needed. The dose-response (high-dose favorable, low-dose variable, same trial, same surgery) is internal. Breadth across cUHDRS, TFC, SDMT, Stroop, and motor moving one direction isn't comparator artifact. It wounds the magnitude, not the package. "Possible signal, not proof" is a floor we cleared exchanges ago.

"Neither proven, AMT only slightly more mature" is the sleight of hand. Rational decisions weigh the quantity and quality of evidence, not a binary. Three years of clinical outcomes isn't "slightly" more than a 12-month biomarker interim, but actually a different category. Two unfinished bridges aren't equally close to the far bank.

And safety cuts the other way: if n≈40 over three years is too thin to characterize procedural and vector risk, then ~12 months of oral exposure is categorically less informative about decades of suppressing huntingtin and a DNA-repair protein daily.

I agreed on one thing, and that is that no honest surgeon should call this "proof" at consent. True, but that's clinical-communication ethics, true of every investigational drug, SKY included. Not the trump card it's played as.

Not equals, not proof, not symmetric.

AMT-130 holds the stronger evidentiary position now.

[Josh Schafer @_JoshSchafer]

Truist's Keith Lerner took a look at 30 major IPOs. The Year 1 max drawdown column stands out.

[Erik Bruckner @E_Bruxxx]

This is likely the best time ever to invest in hard tech and also the most difficult. Quality of founders is absurd. Caliber of engineering talent is highest I’ve seen. Legitimate world-class companies being built across defense, manufacturing, robotics, energy, space, and industrial systems. But damn, there is a lot of noise lol. Every deck is dual-use. Every company is reshoring. Every startup is industrial AI. Every founder is saving America. Most founders know exactly how to tell the story investors want to hear. Noise to signal ratio is out of control. Interesting times.

[Jeff Cranmer @jeff_cranmer]

Biopharma companies, investors and patient advocates have grounds for believing that @US_FDA decisions under Makary, Prasad that appeared final a few months ago may be reversed, says @steveusdin1 https://t.co/soTo7BFeU4

[ClearPath @ClearPath100]

@peter_mantas Vastly undervalued indeed.

Could be trading above its ATH ($82, back in June 2019) in six-twelve months.

[Peter Mantas @peter_mantas]

$QURE The most mispriced equity in bio

https://t.co/IsKoOQBrFo

[ClearPath @ClearPath100]

$QURE AMT-130 vs SKY-0515 aren’t evidentiary equals, and “arguable which is better” buries the key fact.

AMT-130’s data is topline, externally controlled, one-time brain surgery. All fair.

But most importantly, AMT-130 has 3-yr clinical endpoint data: 75% cUHDRS slowing, p=0.003, TFC p=0.033, CSF NfL below baseline, clean dose-response. External control is propensity-matched from Enroll-HD (n=940) + concordant with TRACK-HD/PREDICT-HD. “Not placebo-controlled” is FDA’s evidentiary-standard gripe, not proof the signal’s fake.

SKY-0515’s headline is biomarker - with around 62-69% blood mHTT lowering. This is a promising mechanism, but HTT lowering is NOT the same as clinical benefit in HD. Ask tominersen, which lowered HTT beautifully and got halted in Ph3 for doing worse. SKY-0515 is where tominersen once looked great. Not equivalence.

And “oral = safer” conflates acute one-time procedural risk with lifelong daily suppression of HTT and PMS1 (a DNA-repair protein).

Bottom line is that AMT-130 is the only HD asset with significant multi-year clinical-outcome data. SKY-0515 might get there at some point in the far future, but it isn’t nearly there yet.

[Daniel Jeffries @Dan_Jeffries1]

AI will become our interface to the world.

It will sit higher in the stack than the OS. It will collapse current SaaS layers, chat, communications, apps, app creation, into a single new kind of interface that doesn't exist yet.

It's got to be open. It's got to be a cypherpunk solution that makes privacy and security the number one priority.

If a closed source solution wins this layer, it's a disaster for the world. Especially if it's built by a single company with a single closed source model.

Why?

Because what we share with AI will be more intimate than anything we've ever shared with a machine.

It will be our friend, our sounding board, our advisor. It will know our business ideas before we've told anyone. Our medical issues. Our financial picture. We'll talk about the fight we had with our partner. About feeling lost or depressed. Our kids will talk to it about problems at school, about bullying, about heartbreak, things they won't tell us.

It will know us more intimately than we know ourselves.

Right now the world runs on a surveillance economy. We traded free stuff for apps that peer deeply into our lives.

If we replicate that model in the AI era, it's not just surveillance economy 2.0. It's surveillance economy squared. Social scoring. Legal conversations you thought were privileged showing up in court. Random people making $2 bucks an hour on the backend from God knows where reading the most intimate details of your life. Every insecurity, every fear, every half-formed thought you whispered to your AI buddy at 2 AM, sitting in a database somewhere, searchable.

This interface might eventually become an OS, like the OS in Her. But it will take a long time to reach down to that layer and it will require a fundamentally new kind of operating system design. You can't retrofit this onto Linux or Windows or Android or iOS. It's a new layer of the stack entirely.

And whoever controls that layer controls our lives.

We've got to make sure it's us. Not them.

[ClearPath @ClearPath100]

@MashReez Same for $QURE

[ClearPath @ClearPath100]

$QURE Timely backdrop to the HD therapy race:

FDA will according to Axios today issue draft guidance letting cell & gene therapy developers lean on prior scientific knowledge instead of rebuilding the evidence base each time, explicitly aimed at serious, life-threatening rare diseases.

Read alongside this year’s CMC flexibilities and expedited-program guidances, the post-Makary signal is clear: a regulator trying to move gene therapies faster, not slower.

That backdrop favors programs that have actually generated rigorous, FDA-engaged efficacy data. $QURE’s AMT-130 fits exactly: 36-mo significant cUHDRS slowing (p=0.003), CSF NfL below baseline.

A more flexible FDA isn’t a reason to lower the clinical bar.

It is a reason to act decisively on the candidate that has already cleared it.

For US HD patients with no approved disease-modifying option, the fastest real path runs through the program at the regulator’s desk today.