When the Channel Starts Teaching You

Information asymmetry is not a simple fix

There’s a figure doing the rounds this week: something like 35-40% of GLP-1 volume now moving through manufacturer-direct channels. I’d treat it with care, though not because I think it’s too high. The trouble is that nobody says whether they mean scripts or revenue, new starts or refills, diabetes or obesity - and that last distinction carries most of the weight. Type 2 diabetes is largely an insured business. Obesity increasingly isn’t. Around 60% of people have no commercial cover for Zepbound, employers are quietly declining to expand what they’ll pay for, and when oral semaglutide launched it took roughly a third of new-to-brand prescriptions with the majority of that volume moving through cash-pay routes.

So if anything the direct number is conservative for the part of the market that matters most. But the argument I want to make doesn’t depend on it, which is why I’m happy to give it away at the top. Forty per cent or fifteen, something has changed in the shape of the business, and the change is more interesting than the share.

Most of the commentary has stayed on commercial ground. Cutting out PBMs, cash pricing, competing with compounders, simplifying access. All true, all useful. The quieter shift is structural.

Manufacturers have mostly lived downstream of their own products. Prescribing behaviour, real persistence, dose titration in the wild, who drops off and when - these signals arrived late, filtered and shared. You waited for the claims data, the syndicated reports, the secondary analyses, and by the time you had a picture everyone else had a version of it too.

Mostly, but not entirely. Rare disease and specialty have run hubs and patient support programmes for years, and those functions have sat close to the patient for a long time. It’s worth saying, because it means we aren’t speculating about whether the mechanism works. We know it does. What’s new is the scale: the same proximity applied to a category with tens of millions of patients rather than a few thousand.

When a meaningful share of volume runs through your own channel, the lag collapses. You see the market closer to the moment it happens. Not perfectly and not completely, but earlier, and with a fidelity the traditional distribution system cannot match. What used to be a shared lagging indicator becomes a private leading one.

The commercial advantage is obvious enough. The longer-term effect is subtler. Future assets launch into a different information environment, because you already know something about how patients use the class, where the friction sits, which segments persist. That shapes what you optimise for next - formulation, support services, the design of the clinical programme itself. The company that sees the real-world patterns first gets to decide what “next” looks like while everyone else is still reconciling last quarter’s claims.

The obvious objection, and I don’t think it has a clean answer, is that the people who arrive through a direct channel are not a random sample. In obesity this is subtler than it first looks, because cash-pay isn’t some fringe of the market. It’s close to the centre of it. But the patient who can find several hundred dollars a month is still not the patient who can’t, and direct-channel populations skew to the younger and wealthier, telehealth-acquired, lighter on comorbidity, more likely to be treating something nearer to appearance than disease. The proprietary leading indicator leads on a self-selected group, and the speed with which you learn about that group can look a great deal like knowing the market.

There’s a related loss. Volume that moves out of the traditional system stops generating the signals you used to buy, expensively. You gain resolution on your own patients and give up a little on everyone else’s.

None of that is a reason to dismiss the advantage. It’s a reason to be careful about what kind of advantage it is. Fast, biased data is a difficult thing to hold well, more dangerous in some ways than slow, representative data, because the confidence it produces doesn’t announce its own limits. The companies that get this right will be the ones treating their channel as one instrument among several rather than the definitive read.

There’s a second constraint, less discussed and probably more binding. Collecting the data is the easy part. Whether anyone in R&D is permitted to see it is another question entirely. Commercial operations and development sit under different governance, and the consent basis on which a patient signs up to a direct pharmacy is not obviously the basis on which you feed their behaviour into a development decision. Most organisations will find that the pipe exists and the valve is shut, and that opening it is a legal and structural problem rather than a data one.

I’ve written before about the movement from molecule to product. What’s happening now is the step after that, from product to a learning system built around the product.

Readers here will recognise the shape of it. The argument I keep making about development is that the same asset handed to two different teams produces two different outcomes, and the gap is almost never talent or budget. It’s that one team planned to learn and the other planned to prove. One treated the programme as a way to know something the competition didn’t. The other ran the studies it was told to run and found out what it already suspected.

What’s interesting about the direct channel is that this is the same argument arriving at the far end of the lifecycle, where it has been conspicuously absent. Commercial is usually where organisations stop learning and start executing. The plan is set, the launch happens, the numbers come in, and such learning as occurs is retrospective and shared with everyone who buys the same reports. Owning the channel changes what’s possible there. Whether it changes what actually happens is a separate question.

Because a direct channel is a learning design decision dressed up as a distribution decision. Most companies will take it as a distribution decision - margin, access, competing with compounders, all the things the commentary is currently about - and will get precisely what a distribution decision gets you. The ones who take it as a learning decision will start somewhere else entirely: not with how much volume we can route through this, but with what we want to find out, and what we’d have to build in order to find it out first.

Two companies can put identical assets through identical channels and end up in different places. They always could. The channel simply raises the ceiling on how different.

So I don’t think the interesting question is who builds the pharmacy. Everybody will build the pharmacy. The question is who has an organisation capable of being changed by what it learns there. That’s rarer than a distribution strategy and far harder to buy, because it asks you to be willing to discover you were wrong about something you’d already signed off.