3 ms·

Another concern with approving drugs more easily: you might then never find out if they really work or not. The reason we need very large, expensive, and stric

Another concern with approving drugs more easily: you might then never find out if they really work or not. The reason we need very large, expensive, and strict clinical trials is because it's hard to see if a drug actually works or not otherwise - too many confounders. So if we pass drugs through with a higher error rate, we'll likely never know if some of them actually work or not. Maybe not a problem for a disease with no treatment at all, but imagine you have 10 treatments and you suspect that 7 of them don't actually work, but you don't know which 7. Is that better than just having 3 available treatments where only 1 of them doesn't actually work?

rayiner 11y ago
This is the heart of it. People like to paint this as a regulatory problem--the FDA keeping all these potentially useful drugs off the market due to its bureaucracy. But he fact is that 85-90% of drugs that hit early Stage I clinical testing don't make it through approval. That means the science is bad at predicting what will work and what won't work, and spectacularly so. That's a science problem, not a regulatory. People bring up the "more harm than good" issue, but they're only thinking of one kind of harm: drugs that actually hurt people. But having ineffective drugs on the market also has a cost, and it's probably the bigger one. The market for effective drugs is almost certainly not efficient given the difficulty of ascertaining efficacy and the information asymmetries involved. Thus, there is a real risk of people dying because the inefficient market selects for drugs with good marketing over ones that work.
- danieltillett 11y ago
  Drugs die for all sorts of reasons other than being ineffective. A major one is the cost of getting a drug approved is now so expensive that you can’t make money off it. The vast majority of diseases are effectively beyond treatment because the market for them is not large enough to support the cost of developing a new drug for them. The other major reason for failure at Stage I/II is that the preclinical models we are using are not a good match for human disease. This means that a drug that works in a mouse model can’t ever work in humans because the mouse model does not reflect the human disease (Alzheimer's is the classic for this). We are using preclinical models we know are useless and are then surprised when the drugs found using them don’t work in humans.
eitally 11y ago
Precisely. Here's a specific example: infantile spasms. I was helping my wife research this condition yesterday (for work -- thankfully neither of our children were affected). I found this[1] really great summary article from 2006 that synthesized the findings of numerous trials over the past 50 years and presented the data in a very clear and understandable way. If you want to medicine to build on the foundations of history, you need to be able to reference the history. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1464162/ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1464162/
danieltillett 11y ago
Of course you can - what you do is grant approval conditional on you showing that they are effective once on the market (this is already done with Stage IV trials). With technology it would be much easier to track all patients using a conditionally approved drug and we would get far more useful data too.
refurb 11y ago
This has somewhat already been solved. Avastin works really well for colorectal cancer, so it was tried in a really small trial in breast cancer. There was a small signal there, so the FDA gave conditional approval with the agreement that the company would run a larger test to confirm the results. Well, they ran the bigger trial and it showed no benefit at all. The FDA rescinded conditional approval.
- danieltillett 11y ago
  The crazy thing with the current regulations is the company would have been better off financially not ever doing the study. Since doctors can proscribe off-label, if they had not done the larger study they could have kept selling Avastin to breast cancer patients on the sly. Avastin probably does work for some breast cancer patients if they have a cancer with the right mutations, but if the percentage is a small enough then the large study would not be able to detect this effect in the broad population.
BurningFrog 11y ago
It is very hard to believe that it is impossible to collect data from regular use. That should generate vastly more data. Besides, the proposal is not to approve all drugs easier. Drugs for same conditions would be harder to approve under the proposed model.

rayiner 11y ago

This is the heart of it. People like to paint this as a regulatory problem--the FDA keeping all these potentially useful drugs off the market due to its bureaucracy. But he fact is that 85-90% of drugs that hit early Stage I clinical testing don't make it through approval. That means the science is bad at predicting what will work and what won't work, and spectacularly so. That's a science problem, not a regulatory. People bring up the "more harm than good" issue, but they're only thinking of one kind of harm: drugs that actually hurt people. But having ineffective drugs on the market also has a cost, and it's probably the bigger one. The market for effective drugs is almost certainly not efficient given the difficulty of ascertaining efficacy and the information asymmetries involved. Thus, there is a real risk of people dying because the inefficient market selects for drugs with good marketing over ones that work.

danieltillett 11y ago
Drugs die for all sorts of reasons other than being ineffective. A major one is the cost of getting a drug approved is now so expensive that you can’t make money off it. The vast majority of diseases are effectively beyond treatment because the market for them is not large enough to support the cost of developing a new drug for them. The other major reason for failure at Stage I/II is that the preclinical models we are using are not a good match for human disease. This means that a drug that works in a mouse model can’t ever work in humans because the mouse model does not reflect the human disease (Alzheimer's is the classic for this). We are using preclinical models we know are useless and are then surprised when the drugs found using them don’t work in humans.

eitally 11y ago

Precisely. Here's a specific example: infantile spasms. I was helping my wife research this condition yesterday (for work -- thankfully neither of our children were affected). I found this[1] really great summary article from 2006 that synthesized the findings of numerous trials over the past 50 years and presented the data in a very clear and understandable way. If you want to medicine to build on the foundations of history, you need to be able to reference the history. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1464162/ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1464162/

danieltillett 11y ago

Of course you can - what you do is grant approval conditional on you showing that they are effective once on the market (this is already done with Stage IV trials). With technology it would be much easier to track all patients using a conditionally approved drug and we would get far more useful data too.

refurb 11y ago

This has somewhat already been solved. Avastin works really well for colorectal cancer, so it was tried in a really small trial in breast cancer. There was a small signal there, so the FDA gave conditional approval with the agreement that the company would run a larger test to confirm the results. Well, they ran the bigger trial and it showed no benefit at all. The FDA rescinded conditional approval.

danieltillett 11y ago
The crazy thing with the current regulations is the company would have been better off financially not ever doing the study. Since doctors can proscribe off-label, if they had not done the larger study they could have kept selling Avastin to breast cancer patients on the sly. Avastin probably does work for some breast cancer patients if they have a cancer with the right mutations, but if the percentage is a small enough then the large study would not be able to detect this effect in the broad population.

BurningFrog 11y ago

It is very hard to believe that it is impossible to collect data from regular use. That should generate vastly more data. Besides, the proposal is not to approve all drugs easier. Drugs for same conditions would be harder to approve under the proposed model.