Epistemic status: Big if true, I don't have much time now but I might try and write part of this up into a more formal scientific letter to a journal or something later. I am reasonably confident in my models here but I do not have much experience in the field and I've written this up over the past weekend instead of revising for my exams.
Results from EET-A human trials (if they go ahead) will improve patient outcomes in AD (60%), conditioning on EET-A being an effective agonist of PGC-1α in humans (80%)
EET-A will show positive results in models of HD (40%) low as I think the mechanism of mHTT toxicity (binding to DNA to prevent PGC-1α production) means EET-A cannot act upstream of it and can only act on the same level.
EET-A will show temporary benefits as an anti-ageing therapy (
70% as above) (more like 35%, this has clearly slipped past proofreading and various sanity checks on my part) and will work "better" that senolytics in that it will actually reverse ageing rather than needing to be taken at higher concentrations over time ( 40%) (20%? These both seem wildly overconfident with some afterthought).
I think this perspective on AD and HD is probably useful, and it's not one I've seen before. Scientists are awful at sharing high-level models of diseases as they do not generally involve novel research and are (I suspect) very difficult to get published in high-impact journals. The authors of the paper using EET-A to treat AD did not seem to know why their treatment works, whereas I built a model whereby EET-A should effectively treat AD before I even considered "testing" my theory by simply looking to see if anyone else had done the experiment (Having made the prediction first gives me extra confidence in my own models but I don't expect it to be a strong argument to anyone reading this).
The remarkable thing about this investigation was how little time it took me, about three days. I expect there are many more intelligent and experienced people than me who could be drawing up similar links and conclusions with a small amount of effort. Building models of diseases based on existing studies is a clear way to guide new research, if I was a researcher about to start a new clinical trial (which could take years of my life) then even a 1% increase in success rate ought to be more than worth a short amount of analysis. I suspect this is not a mental habit which many scientists are in, perhaps due to social pressure to "stick to their lane" and just work on one small area of research. On the other hand maybe there are many scientists who are doing this but just not telling anyone.
If we are to cure ageing at some point (something I plan to be involved in) I suspect it will involve similar levels of modelling cellular processes. Having an overarching model (or several competing models) of which different parts can be tested independently seems like a structure which is very amenable towards different scientists, so I am disappointed none of the biological/medical community has started doing something like this.