pfisherman

FDA regulates the marketing of drugs and medical devices. This is a case of Hims and Hers (and other compounding pharmacies) marketing drugs without having been granted approval.

There is an abbreviated application for new drug approval (ANDA) pathway meant for generics, but it does not seem like H&H has gone this route. It does require you to open your supply chain up to inspections and to provide evidence that your generic version basically works the same as the brand name.

In my opinion there two things going on here that I strongly feel are true.

1. Something is systemically wrong in the US when we are cutting off people’s access to meds, like GLP-1s, which have profound health benefits.

2. Hims and Hers are also in the wrong. The rules and laws are there for a good reason. It is not just for us to arbitrarily pick and choose when to enforce them.

Oh boy, are you going to be in for a rude awakening. Might I ask what is your exposure? Because this does not line up with what I am witnessing day to day at all.

This type of commentary reminds me of the people during the dot com boom who were adamant that e-commerce was all film flam and would never take off.

Consider that it is possible that both (1) we are in an investment bubble and (2) we are underestimating the long term impact of LLMs and perhaps mispredicting where they will land.

That is such a bummer. At the time, it was annoying and I groused and grumbled about it; but in hindsight my reviewers pointed me toward some good articles, and I am better for having read them.

Hotels are not platforms. No network effects at play. The idea of ban is to push teen DAUs below the critical mass necessary for self sustaining retention and growth.

Sure teens will still figure out a way to access when they really want to, but they won’t be be the same level of peer pressure.

I feel like this is the strongest argument in favor of the bans. I am not sure it will be effective or is the most effective way to go about it. I am curious to see the data that comes out of Australia in a few years.

I don’t know what this comment is, but it is totally missing and underselling Chinese capability in biotech. They are not coming to push TCM. They are coming to dominate high end drug discovery and development. Perhaps they are looking to dominate both the high end and the low end bro science segments of the health market…

They are currently eating our biotech lunch. Between cuts to NIH, chaos at FDA and CDC, and China’s intensive investment and buildout of their biomedical infrastructure the US is going to be getting lapped soon. Ask a biotech VC about it.

But who knows, maybe if we keep the tariffs for another 10 years we can host the chemical manufacturing facilities that produce the drugs their biotechs sell to us after ours are no longer competitive.

Counterpoint: Charlie Brown

A big part of what makes Charlie Brown so endearing is his undying earnestness and optimism in the face of near constant bad luck and disappointment.

He is exactly the lovable loser archetype that this piece says Americans do not dig. Yet the Peanuts comics and cartoons and an American pop cultural institution.

Some biomedical research will definitely run up against guardrails. I have had LLMs refuse queries because they thought I was trying to make a bioweapon or something.

For example, modify this transfection protocol to work in primary human Y cells. Could it be someone making a bioweapon? Maybe. Could it be a professional researcher working to cure a disease? Probably.

One thing I have not seen come up in these discussions is how these bans interact with the network effects. They might actually be one of the most effective tools we have to fight back against and punish platform businesses.

I assume that something like a partially effective ban could have a devastating impact on social media because it may push active users in the teen / adolescent demographic below the critical mass necessary for self sustaining growth and retention.

Has anyone done any studies on where that tipping point / critical mass is? How effective do these bans have to be to achieve their intended outcome?

Thanks for the technical explanation! This is pretty fascinating.

So it works kind of like a soft delete — dereference instead of scrubbing the bits.

Is this behavior generally explicitly defined in PDF editors (i.e. an intended feature)? Is it defined in some standard or set of best practices? Or is it a hack (or half baked feature) someone implemented years ago that has just kind of stuck around and propagated?

Can someone spell out how this is possible? Do pdfs store a complete document version history? Do they store diffs in the metadata? Does this happen each time the document is edited?

Adding to this, the molecular mechanisms of psychiatric disorders such as depression, bipolar disorder, and schizophrenia are not well understood. People prefer their brains and skulls intact so taking brain samples for study is not possible.

Diagnosis and grading is fuzzy - a cluster behavioral symptoms observed and reported by patients, family members, and clinicians.

Based on some of the genetic evidence, which can also be fraught, it is likely that something like depression is in fact a grouping of a bunch of separate underlying disorders / causes that all result in the same (easily) observable symptoms. Hence why some treatments work on a subset of patients, but are ineffective in others.

I has a Nokia N95. The phone itself was great. The problem was the dearth of apps. Nobody developed anything for windows mobile OS. Maybe Ballmer was not so crazy when he was running around on stage screaming “Developers, developers, developers”.

That is because there has been an absolute massacre in biotech in the bay area. Between tariffs (higher COGS), chaos at the FDA, cuts to NIH funding for basic and translational research, and competition from China biotech ventures are getting squeezed from both ends.

My sense is that AI is the one area where boards cannot justify cutting back on investment. If there were no AI boom the rest of the economy would still be getting hammered.

There is still a lot of tech investment, deal making, and hiring going on. It has just left the USA.

My pet theory is that we are experiencing stagflation, but only people >70 years old have ever really experienced it before, so most people are just scratching their heads wondering how it’s possible that stocks keep going up (inflation) while jobs are disappearing (stagnation). I am most definitely not an economist, nor am I qualified to play one on tv.

What burden of disease are we talking about here?

Ask the question would you be comfortable allowing babies to be maimed or killed in a medical experiment to develop a treatment to some malady?

Make no mistake that is what we are talking about here. You are testing a therapy. Because you are editing the genome adverse effects of the therapy are irreversible and present at birth. Those adverse effects may include maiming or death.

So now that we have established what the stakes are, I ask again, what set of diseases do you think it is worth the risk of maiming and killing babies to develop a cure?

I think fatal monogenic diseases could be justifiable. But even there a valid argument could be raised about alternative approaches - ex. Cystic fibrosis.

Once you get beyond that things start getting dicey pretty quickly. Only a hop, skip, and a jump to nazi medical experiments on the “mentally retarded”. Check out the Belmont Report for more formalized ethical framework for medical experimentation on people.

This is pretty ridiculous, just stupid enough for a bit of silly Friday watercooler conversation.

I have questions. How do facial expression, clothes, and hairstyle impact the model’s predictions? How about Facetune and insta filters? Would putting a clickbaity YouTube thumbnail at the top of my resume make me more employable?

This lines up with what I once heard “second hand” from faculty at a business school about publishing in academic business journals. It was something along the lines of being a bunch of dancing monkeys pumping out entertaining, to readers of HBR and such, content.

The word “smart” is doing a lot of work here. And I think both the author and a lot of commenters in this thread are equating it with IQ.

What about EQ? I would also consider people with high EQ to be smart. It is a different kind of smart, and provably one more correlated with happiness.

My main point of skepticism about repurposing is whether this is giving any of new and actionable information. It seems to be reliant on pre existing target annotations, and qualified targets already have molecules designed for them. Is the off-target effect strong enough to give you a superior molecule? Why not just start by picking a qualified target and committing to designing a better molecule without doing all the off target assay stuff first?

This article kind of grinds my gears. I feel like there is an unstated assumption that people in pharma R&D are idiots and haven’t thought of this stuff.

Pharma companies care very much about off target effects. Molecules get screened against tox targets, and a bad tox readout can be a death sentence for an entire program. And you need to look at the toxicity of major metabolites too.

One of the major value propositions of non small molecule modalities like biologics is specificity, and alternative metabolism pathways; no need to worry about the CYPs.

Another thing they fail to account for is volume of distribution. Does it matter if it hits some receptor only expressed in microglia if it can’t cross the blood brain barrier?

Also the reason why off targets for a lot of FDA approved drugs are unknown is because they were approved in the steampunk industrial era.

To me this whole article reads like an advertisement for a screening assay.

The list price is mostly a starting point for negotiations with PBMs and payers. Drugs are also often aggregated and bundled. So in a lot of cases is unclear what a drug actually costs.

Ime, there are two causes of heated scientific debates. (1) Conflicting or insufficient data. (2) Communication issues.

Cause (1) cannot usually be resolved without some sort of technological innovation.

Cause (2) is quite interesting because it is a social problem.

For example, someone comes to you with a markov decision problem and insists that no form of reinforcement learning could be a viable solution. Why would they do this? Probably because their understanding of RL differs from yours. Or your understanding of the problem differs from theirs. This can be solved by communication.

Stated differently, the topology of your “semantic map” of the domain differs from theirs. To resolve it you must be able to obtain an accurate mapping of their local topology around the point of disagreement onto yours.

> One of the realities is more unyielding than the other.

Also ten or one hundred (people) is more than one.

That math can’t be reasoned out of existence either.

> They will follow instructions from a workplace superior with zero push-back

Zero push-back? Or zero push-back in front of the rest of the group?

Humans are pack animals, highly evolved for social connection, and ostracism can be life threatening. The benefits of group membership and cohesion are enough that it is worth tolerating some mistakes and suboptimal outcomes because over time the expected utility for individuals and in the aggregate is much higher when people are working together harmoniously as a group.

Big caveat here is how people are using the LLMs. Here they were using them for things like information recall and ideation. LLMs as producer and human as editor / curator. They did not test another (my preferred) mode of LLM use - human as producer and LLM as editor / curator.

In this mode of use, you write out all your core ideas as stream of consciousness, bullet points or whatever without constraints of structure or style. Like more content than will make it into the essay. And then have the LLM summarize and clean it up.

Would be curious to see how that would play out in a study like this. I suspect that the subjects would not be able to quote verbatim, but would be able to quote all the main ideas and feel a greater sense of ownership.

> Personally, I’ve been seeing the number of changes for a PR starting to reach into the mid-hundreds now. And fundamentally the developers who make them don’t understand how they work.

Could this be fixed by adjusting how tickets are scoped?

> But here’s the kicker: we were told AI would free us up for “higher-level work.” What actually happened? We just found more work to fill the space. That two-hour block AI created by automating your morning reports? It’s now packed with three new meetings. The 30 minutes you saved on data analysis? You’re using it to manage two more AI tools and review their outputs.

This is basically the definition of increased productivity and efficiency. Doing more stuff in the same amount of time. What I tell people who are anxious about whether their job might be automated away by AI is this:

We will never run out of the problems that need solving. The types of problems you spend your time solving will change. The key is to adapt your process to allocate your time to solving the right kinds of problems. You don’t want the be the person taking an hour to do arithmetic by hand, when you have access to spreadsheets.

Karpathy’s talk about computing 3.0 was spot on. Look at what is going on with pydantic and langchain. “LLM programming” is about to be a thing.

Hindsight is 20/20. The company I worked at went under because people questioned whether enough people would ever buy stuff over the internet to make the business viable. It was very much not obvious then.

> Gen-AI may be useful to some people, but it's not going to be a central feature of most people's lives—at least not in the forms it exists in today, or what can be clearly extrapolated from them…

The problem is that you are going to have to compete with people who are using AI. There is a learning curve, and some people are better at using it than others. Some people know how to use it really well.