That's a good question, but in this context, seeing a variety of novel discoveries in the last few years indicates a somewhat successful field. By the same token, I'm curious what makes you think this isn't a successful field?
The fact that Big Pharma has to lay of a lot of scientists is a real world indication that the output of model of finding a drug target, screening thousands of components against it, runs those components through clinical trials to find whether they are any good and then coming out with drugs that cure important illnesses at the other end stops producing results. Eroom's law.
I've already mentioned the file drawer problem. I'm curious, do you think that is a theoretical problem?
Saying that there's a file drawer problem is quite easy. That however not a solution. I think your problem is that you can't imaging a theory that would solve the problem. That's typical. If it would be easy to imagine a theoretical breakthrough beforehand it wouldn't be much of a breakthrough.
Look at a theoretical breakthrough of moving from the model of numbers as IV+II=VI to 4+2=6. If you would have talked with a Pythagoras he probably couldn't imaging a theoretical breakthrough like that.
You seem to be treating biology to some extent like it is physics, But these are complex systems. What makes you think that such approaches will be at all successful?
I don't. I don't know much about physics. Paleo/Quantified Self people found the thing with Vitamin D in the morning through phenemology. The community is relatively small and the amount of work that's invested into the theoretical underpinning is small.
I think in my exposure with the field of biology from various angles that there are a lot of areas where things aren't clear and there room for improvement on the level on epistomolgy and ontology.
I just recently preordered two angel sensors from crowdsourcing website indiegogo. I think that the money that the company gets will do much more to advance medicine than the average NHI grant.
The fact that Big Pharma has to lay of a lot of scientists is a real world indication that the output of model of finding a drug target, screening thousands of components against it, runs those components through clinical trials to find whether they are any good and then coming out with drugs that cure important illnesses at the other end stops producing results.
This seems like extremely weak evidence. Diminishing marginal returns is a common thing in many areas. For example, engineering better trains happened a lot in the second half 19th century and ...
For those who haven't heard, NIH and NSF are no longer processing grants, leading to many negative downstream effects.
I've been directing my attention elsewhere lately and don't have anything informative to say about this. However, my uninformed intuition is that people who care about effective altruism (research in general, infrastructure development, X-risk mitigation, life-extension...basically everything, actually) or have transhumanist leanings should be very concerned.
The consequences have already been pretty disastrous. To provide just one, immediate example, the article says that the Center for Disease Control and Prevention has shut down. I think that this is almost certain to directly cause a nontrivial number of deaths. Each additional day that this continues could have huge negative impact down the line, perhaps delaying some key future discoveries by years. This event *might* be a small window of opportunity to prevent a lot of harm very cheaply.
So the question is:
1) Can we do anything to remedy the situation?
2) If so, is it worth doing it? (Opportunity costs, etc)