All of BigT's Comments + Replies

In the last five years the NIH (National Institutes of Health) has never spent more than 2% of its budget on aging research. To a first approximation, the availability of grant support is proportional to the number of academic researchers, or at least to the amount of academic research effort being put into a problem. This is evidence against aging already getting enough attention. Especially considering that age is a major risk factor for just about every disease. It's as if we tried to treat AIDS by spending 2% on HIV research and 98% on all the hundreds of opportunistic infections that are the proximal causes any individual AIDS patient's death. I would think that curing several hundred proximal problems is more ambitious than trying to understand and intervene in a few underlying causes. I have no illusions of single-handedly curing aging in the next two decades. I will be as satisfied as any other stiff in the cryofacility if I manage remove one or more major road-blocks to a practical anti-aging intervention or at least a well-defined and valid mechanistic model of aging.

This is 'new' data in the sense that it is only now becoming available for research purposes, and if I have my way, it is going to be in a very flexible and analysis-friendly format. It is the core mission of my team to make the data available to researchers (insofar as permitted by law, patients' right to privacy, and contractual obligations to the owners of the data). If I ran "academia", tool and method development would take at least as much priority as traditional hypothesis-driven research. I think a major take-home message of LW is that hypotheses are a dime a dozen-- what we need are practical ways to rank them and update their rankings on new data. A good tool that lets you crank through thousands of hypotheses is worth a lot more than any individual hypothesis. I have all kinds of fun ideas for tools. But for the purposes of this post, I'm assuming that I'm stuck with the academia we have, I have access to a large anonymized clinical dataset, and I want to make the best possible use of it (I'll address your points about aging as a choice of topic in a separate reply). The academia we're stuck with (at least in the biomedical field) effectively requires faculty to have a research plan describable by "Determine whether FOO is true or false" rather than "Create a FOO that does BAR". So the nobrainer approach would be for me to take the tool I most want to develop, slap some age-related disease onto it as a motivating use-case, and make that my grant. But, this optimizes for the wrong thing-- I don't want to find excuses for engaging in fascinating intellectual exercises. I want to find the problems with the greatest potential to advance human longevity, and then bring my assets to bear on those problems even if the work turns out to be uglier and more tedious than my ideal informatics project. The reason I'm asking for the LW community's perspective on what's on the critical path to human longevity is that I spent too much time around excuse-driven^H^H^H