Most of the UFO sightings occurred around 8:15-9:00 PM, while the flairs were known to be ignited around 10:00 - 10:30 PM. Really bizarre fact about the Phoenix lights, the Governor of Arizona at that time has admitted he saw the UFO (UAP - whatever) [0].
Again want to say I really appreciate how thoughtful you are about this.
I just want to offer a few of my thoughts because you've been so generous with yours. So you know, I work in the industry. More on the biz side than the scientific. And I am intensely interested in this issue.
100-1000 times cheaper I don't think is achievable in the medium term, if ever. As long as we're running clinical trials I think costs will stay constrained to about a 5x decrease. A 100-1000x reduction, I think, implies a world where we can largely simulate the impact of drugs without resort to in vivo testing. A future I believe in, but one that has a lot big unknown technical obstacles to overcome - like entirely new fields of science and engineering. I'm thinking here on a 50-100 year horizon.
This would also entail a huge change for the regulatory environment, but I think we're so far in the future in this scenario that it's hard to predict what that will look like.
I think a 2x reduction is possible in the near-medium term. If we can change the probability of technical success for trials through better tox models - not testing - that creates an enormous amount of value. The stuff people are doing to design better molecules pales in comparison to doing this. I think the math and know-how exists to do it now - the challenges are more institutional - Who pays? Who provides data? Lot's of coordination problems between actors who are in economic knife fights with each other, though people are trying.
Data problems too. Pharma companies are terrible at databases. It's a mess.
Also, it's better to solve tox because it's not disease specific. The effort invested in building the model (or models) will be distributed over many development life-cycles and would remain valuable after a good drug for an indication is invented.
This is a huge win for the world because it makes diseases that are important but not economic easier to justify. The phrase 'important but not economic' churns my stomach, but there it is.
None of this will fix pricing. Not as long as the patent structure stays the same. If you can legally do it, people will do it. Doesn't matter what it costs. Coke is still charging you two bucks for something that costs them cents to produce, and they don't have a patent.
If you want a near term future with lower drug prices (as I do), I fear your route lies through congress. I think it can happen, but I'm an optimist.
Thanks again for your thoughts and your work. It's good to see other people pulling in the same direction.
Why do you think that cheaper development costs will ultimately lead to lower drug prices?
I think we would both agree that drugs are not priced based on cost. Even if R&D were 10X cheaper - all else equal - prices are not coming down.
So what is the mechanism you think will lead to lower prices given lower costs of R&D?
Another question: Maybe as a patient (or a doctor), I like the better than the beetles problem. I don't need a thousand drugs on the market to treat every indication. Especially ones that have not passed a high bar for efficacy. I need a few drugs, preferably outside of patent protection, with enough diversity in structure to avoid specific toxicity effects.
If lowering the efficacy standards doesn't get me treatment for new indications, why would I want it? It's not clear to me that solving better than the beetles gets me to new indications. Presumably if I'm in a regime where BTTB applies, I've got a drug for that.
First, really appreciate the engagement here. This is a hugely important problem and this interview and your presentation of it is a great contribution.
I think one of the things that gets lost when we talk about Eroom's law is that the original data points were established before congress passed the Kefauver-Harris amendments in 1962 which set standards for clinical trials, iNDA process, and basically required that drugs show efficacy before they could be marketed.
An important part of those amendments is they made the drug companies go back and review the 4,000 drugs already on the market and provide evidence on their efficacy. It took FDA a long time to work through that backlog, but when they did:
"In January 1968, the Drug Efficacy Study panels finally reported their conclusions to the FDA. They had reviewed over 16,500 therapeutic claims for 4,000 pre-1962 drugs. Only 434, about 12 percent of those examined, delivered on all their promised claims. Seven hundred and sixty-nine were marked as 'ineffective'" [0].
I bring that up to say two things:
1) Our baseline in examining Eroom's law is a bit skewed because standards have been going up since the graph begins.
2) We should be careful in how we change those standards. Many of them were bought with patients lives.
I need to go now, but I do want to address your comment on pricing later.
I think we're saying the same thing. The disease model itself is necessarily limited. Sure you have a molecule that hits the target, great. But the struggle comes from being able to get that molecule to target in vivo without causing toxic effects.
Maybe we're just missing on how we're using words. I don't see how having a better disease model necessarily gets you to a better place on this. Sure, you can get better SAR and can decrease the dose. But as you point out, dosage is not just a function of SAR.
Having better tox models seems like the highest value, albeit very difficult, route here. Which to me is a separate, more general, problem than a specific disease model.
I'm having a hard time making the connection between declining efficiency and there necessarily being something broken about the science.
To expand just a bit: Scannell seems to be primarily focused on the disease model as the root issue here. This is curious to me. My understanding is that drugs fail primarily in two ways:
1) It's ineffective - fails to treat the disease. Which is partially covered by model validity, but also impacted by pharmacokinetics and distribution. Essentially your molecule can work, it just can't get where it needs to go in a high enough concentration to make a difference.
2) It's unsafe - your molecule is toxic either acutely or long term.
The data[0] I'm aware of indicates that these issues occur with roughly equal frequency. (My assumptions being: failure in Phase 1 trials are an issue of safety, failure in phase 2 can be caused by safety or effectiveness). Which for me calls into question the focus solely on good disease models.
[0] https://www.amazon.com/UFOs-Generals-Pilots-Government-Offic...