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How pharmaceutical industry financial modelers think about rare diseases

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Re: How pharmaceutical industry financial modelers think about rare diseases

#111
post #38

Having been through the early phases of this (both as bench scientist and management, up through Phase II) I can say that this author's analysis is right on. There is a macro wrinkle he doesn't mention and that makes things worse: as we increasingly succeed on stopping the big killers (e.g. lung cancer, CIs, various accidents that constituted most of the causes of death into the 1990s) the histogram of death starts t…

Reminds me if improving process performance, getting from 60% to 80% is easy, 80 to 90ish already hard, 90-95% really hard and everything above 98% is either luck or killing single deviations or both. Not counting for all the new causes that pop up. Anyway, it is an interesting angle, also economic wise. As causes are getting narrower all the time the increasing development costs can be shared by a lot less patients. I can see the incentive of not going after these treatments.

Re: How pharmaceutical industry financial modelers think about rare diseases

#112

Earlier quoted context omitted.

[1] was a mouse study. Do you have any examples of human studies? I have this picture in my mind of someone showing up to a doctors office with a thumb drive of 30 PDFs of nonclinical studies they found through a Google search and demanding treatment x, diet y, and so on.

Why throwaway?

Provably an affected person.

Re: How pharmaceutical industry financial modelers think about rare diseases

#113
post #40

Looking at these numbers, I wonder whether the FDA process is a bit too conservative with respect to safety. There were the articles yesterday about diabetics yesterday creating closed-loop feedback systems out of old insecure parts, because a FDA-certified alternative is decades out. I've heard also of folks joining studies for newer-and-better IUDs that are approved by European regulators, but need to be re-certifi…

Every study I'm aware of that's looked into this issue says that the FDA is too conservative and we'd be better off using the looser systems found in other developed countries. Though it's gotten a lot better over the last few decades, we probably aren't going to get a repeat of the early beta blocker situation where the FDA saved 100s of people from liver failure from early drugs at the cost of 100,000s of excess deaths due to heart failure.

Re: How pharmaceutical industry financial modelers think about rare diseases

#114
post #58
post #40

Looking at these numbers, I wonder whether the FDA process is a bit too conservative with respect to safety. There were the articles yesterday about diabetics yesterday creating closed-loop feedback systems out of old insecure parts, because a FDA-certified alternative is decades out. I've heard also of folks joining studies for newer-and-better IUDs that are approved by European regulators, but need to be re-certifi…

Many people have asked that question, it is a hard complex problem. If the FDA approves a drug and it turns out bad we hate them, if they fail to approve a drug we hate them without knowing if it is worse than nothing. Those old parts work. Is modern technology better? Sometimes yes, but sometime change for the sake of change is bad (I hate modern bathrooms cause the water never comes on, old manual valves worked)

Generally when the FDA fails to approve a drug nobody outside the industry ever hears about it. It's only in rare cases where you have lethal infections that take a very long time to kill, such as with AIDS, that the FDA faces strong political blowback over non-approvals.

Re: How pharmaceutical industry financial modelers think about rare diseases

#115

This is a pretty solid breakdown. IRR isn't mathematically valid though. I might take a run at cleaning up this spreadsheet tonight to make it look a little more professional. Need to include things like tax and exit valuations to get to the correct decision.

There are a few very important caveats that they miss though. Revenue determinants are heavily based on conversations with healthcare payers to determine market size which dramatically effects revenue projections. Most firms that do deep development plan to sell successful drugs and exit as early as possible so transaction costs need to be included in the terminal value, which isn't calculated terribly well in this m…

I'd also use corporate bonds for pharma companies (or biotechs, depending on which you are looking at) for the cost of capital, as ultimately that's what debt costs

Re: How pharmaceutical industry financial modelers think about rare diseases

#116
post #77
post #42

This is an impressive article and an impressive couple. From the site's about page: My name is Eric Vallabh Minikel and I’m on a lifelong quest to develop a treatment or cure for human prion diseases. I originally trained as a city planner at M.I.T. and was working as a software engineer and data analyst in the transportation sector when, in December 2011, I got some bad news. My wife and the love of my life, Sonia V…

It's instances like these that I believe why the medical-pharma industrial complex isn't necessary, and likely more inefficient and soaking up more money - directing them towards profits, or other less efficiently than individuals who are passionate for a solution; yes, we need the institutions like Harvard Medical School to support these people - however the capitalism that then takes advantage of innovation through…

Glad down voting has supported healthy community discussion on HN once again. I'm glad to find out that at least the 5 people to down vote me (so far) all agree it's great that people pay so much for medications.

Re: How pharmaceutical industry financial modelers think about rare diseases

#117
post #68

The author ignores two obvious, extremely high leverage changes that would solve the problems in his model. First, on the revenue side, extend patents on pharmaceuticals as long as possible. His model assumes a very narrow window of payback; quadrupling or quintupling that window would make many more drugs feasible to investigate. Second, to use the author’s word, “de-risk” all trials. The best way to do this would b…

Extending patents wouldn't work that well in his model - as you can see from the graphs it is already discounted crazily (I'd argue for a 6% discount rate, not 8, but it hadly changes the calculus). Besides market exclusivity can often be extended by adding indications and pediatric studies, so they aren't as short as first stated. Plus on some drugs you then get other patents - see inhalers where you have patents on the devices as well as the drugs.

Equally asking to prove safety only... you still have to do the studies, and need a lot of exposure so why not capture outcomes too? I'm not convinced it would be a lot cheaper to omit the outcomes - you still have to recruit the patients, and monitor them. Take HIV, if you don't test blood, you don't know what is happening to patients blood counts, since you have the blood, why not also check for efficacy in viral supression?

Regulatory is also based on benefit:risk, without evidence of benefit, why tolerate any risk? Also how many clinicians would give new drugs with only theoretical efficacy?Hopefully none. All the drugs that fail trials we also think should work, and spend money to prove it! Not to mention the market for pharmaceutical is worldwide, the EMA, Health Canada, Swissmedic and others would throw something out with no evidence of benefit, greatly limiting your market, even in the US.

Are the FDA perfect? No. Are they excellent? Yes. Some of my research touches up against what they do, and my respect for them grows with every interaction. They're also continually improving. The fundamental problem is that we're looking at a 'better than the Beatles' problem https://en.wikipedia.org/wiki/Eroom%27s_law

What might work? More collaboration between companies. If we can enrol one placebo arm, but test 4 active products against it, we cut the costs (and improve the ethics by giving fewer patients placebo). There are a few other minor tweaks too, but it is something we all want to improve, and are trying to do so!

Re: How pharmaceutical industry financial modelers think about rare diseases

#118
post #42

This is an impressive article and an impressive couple. From the site's about page: My name is Eric Vallabh Minikel and I’m on a lifelong quest to develop a treatment or cure for human prion diseases. I originally trained as a city planner at M.I.T. and was working as a software engineer and data analyst in the transportation sector when, in December 2011, I got some bad news. My wife and the love of my life, Sonia V…

> One thing I've learned from smart family and friends about medical care is that you can sometimes improve outcomes quite a lot if you apply brains and effort.

I'd be very careful with this sentiment though, because it is easy to turn it into the toxic notion that if a loved one dies from some disease (which is pretty inevitable), you didn't put enough brains or effort in it.

Re: How pharmaceutical industry financial modelers think about rare diseases

#119
post #84

Earlier quoted context omitted.

If you google for studies, at this point you'll see an abundance of research on this with positive results, which apparently was just getting started when they dug into it and perhaps not well known to the average doctor. My memory plus a quick look into one [1] suggests it's because brain tumor cells largely feed on glucose, whereas normal brain cells can also metabolise ketone bodies for energy. So you're starving…

[1] was a mouse study. Do you have any examples of human studies? I have this picture in my mind of someone showing up to a doctors office with a thumb drive of 30 PDFs of nonclinical studies they found through a Google search and demanding treatment x, diet y, and so on.

And the effect seems mostly due to caloric restriction, not the (C)KetoCal bla bla diet.

Re: How pharmaceutical industry financial modelers think about rare diseases

#120
So I work on the opposite end to discovery, in the interpretation, and estimation of outcomes seen beyond the studies i.e. what impact will the drug have. Applied statistics essentially.

The author is completely right about the raw mechanics of investment decisions (and sometimes they are just that when a pharma company is sizing up buying an asset), but has written up a really thought provoking piece which was interesting to read. Though I deal with time preference every day, I hadn't quite internalised how much influence it had for early spending.

In terms of my experience, very similar, I worked in global HQ for a large pharma company, responsible for my small part of things for 4 products. 2 failed in Phase 2, and the other 2 failed their Phase 3s. I moved to another pharma company where I was focussing on launch products, but every now and then one would disappear off the radar. For other the trial results would come in, and it only worked on half the patients. We expected all these to work - the science was impeccable, the animal models demonstrate a good basis for belief... it just didn't happen. Every drug that works really is a needle in a haystack.

On the making development attracting, I've been forutnate enough to be able to volunteer some of my professional time to a patient group trying to attack the problem in a different way, and make it possible to get medicines commercialised in Duchenne Muscular Dystrophy. The approach is led by a couple of really impressive executives* and is trying to get companies to collaborate to pull together some of the materials the author mentions (rather than all do them in isolation with variable quality). They recently won an award for their work, and thoroughly deserve it. These kind of initiatives are what can really make a difference, and de-risk an area for many companies - the lay of the land is known, and there is high quality understanding of what matters to patietns, and the natural progression of disease. It also means that companies developing medicines can engage to make sure their trial program targets the right patients, and measures the right things. If anyone is interested: https://hercules.duchenneuk.org/publicity

* I say executives because that's what they are, and the role they play. They all have sons with DMD which is their motivation, but that label that doesn't do justice to the amazing work the group does - as an example where there are generic medicines that might help, they are funding trials to find out!

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