And the goal of academia (publishing) are very different than the industry (identifying a new drug).
And the goal of academia (publishing) are very different than the industry (identifying a new drug).
[edit] I'm going to add something here. The grandparent refers to "stupidly misleading pre-clinical data." Pre-clinical data informs very inexpensive (relatively) Phase I studies. And there is a ton of it. You might have potentially misleading pre-clinical data that suggests the possibility of an entirely new therapeutic mechanism of action for a huge unmet need coupled with massive amounts of pre-clinical data that demonstrates a near certainty that the intervention will be safe. That's the entire point of moving forward to a Phase I or Ib (or maybe even II) study. The 1000x-10,000x more expensive phase 3's are not relying on pre-clinical studies.
I’m from the academic side in the sense have talked to many folks who quit industry to start jobs and come from a lab that did get a drug into the market eventually. I might not know this “secret data” you speak of but given the results are crap, I think they speak for themselves anyway.
I'm wondering how much you're actually involved in research to make a statement like that.
Scientists at these companies are likely out of a job if the trials aren't successful (especially for start-ups that have one shot).
The answer is - when you're developing a brand new molecule, often for a recently discovered pathway, in a biological organism that is so complex we barely understand it, failure shouldn't be surprising.
The large drug companies don't develop many new drugs anymore, and they don't fire their scientists when a trial fails. The people that make the decision on whether or not to move to clinical trials from preclinical data are not necessarily scientists either and they certainly will not be fired. Their decision on whether or not to proceed with trials is far more complicated than for an academic or an early startup such that it can make sense for a large pharma company to attempt a trial even if it is unlikely to work if the expected payoff is sufficient. They will definitely still get paid.
Yes, scientists still get paid but the draw of start ups (like tech) is lower pay, and potential upside through equity.
So if the drug fails, they just lost a significant amount of money versus staying in big pharma, and they lost their job.
And for big pharma, if you don’t create new drugs, the company revenue falls and lay offs occur (like what is happening right now at several big pharma).
The risk is much higher at a start up that it’s “do or die”, than big pharma, but it’s still there.
Go and look at the massive layoffs that Pfizer, BMS, and other big pharma have done over the years.
> So if the drug fails, they just lost a significant amount of money versus staying in big pharma, and they lost their job.
This is true of the scientists that aren't making the decisions. The ones that do make decisions are going to be able to retire if the startup was funded enough for clinical trials.
> And for big pharma, if you don’t create new drugs, the company revenue falls and lay offs occur (like what is happening right now at several big pharma).
Do you have data according to which the current layoffs in big pharmas are significantly affecting decision-makers? Because that's the matter at hand.
As far as revenue decline, sure, for a given definition of "new drugs". The actual argument I've put forwards is that for a big pharma, it can make sense to run trials which are unlikely to succeed and with limited clinical utility if the financial upside is sufficient, which is not true for uni labs or biotech startups.
> Go and look at the massive layoffs that Pfizer, BMS, and other big pharma have done over the years.
Pfizer does "massive" layoffs every year, and just like BMS, every time a lot of the affected employees aren't executives fired due to unsuccesful trials, but employees of companies they bought.
As far as researchers getting laid off, big pharmas are infamous nowadays for firing researchers when R&D pipelines are sucessful just as much as when they fail. Researchers are made redundant either way, unless for some reason further research in the same domain is needed (which often isn't the case). It also happens pretty often in startups that end up selling IP.
1. Produce a molecule that does what you want it to in the body
2. Figure out how to get that molecule where it needs to be in the body
3. Prevent it from doing all sorts of other gnarly things
4. Convince people you’ve succeeded in doing 1, 2, and 3 to the degree they’re willing to volunteer themselves to put this new molecule inside their bodies — without incentivizing them in any way
5. Convince enough people to do that and collect enough data about them to know for a fact that your drug does X and does not do Y
6. Convince regulators that not only have you done 1, 2, 3, 4, and 5, but that it’s also better on some dimension than the currently available treatment
In short: because it’s ridiculously hard. If it’s easy you should go give it a shot, help millions or billions of suffering people, and make billions of dollars in the process. Why wouldn’t you?