This is a good review from AstraZeneca scientists on phenotypic screening in neurodegenerative disease (by which one means Parkinson’s, Huntington’s, frontotemporal dementia, Lewy body dementia, and of course Alzheimer’s). And it’ll serve as a good intro to the challenges in these two fields in general, and to why they intersect. Put simply, we don’t have a detailed enough understanding of neurodegeneration to be able to pick out the key steps (the most important enzymes, receptors, or other proteins) and screen against them individually. You can try (and people most certainly have) but you’re taking a huge, expensive, risky shot into the unknown – which is what the history of Alzheimer’s drugs in clinical trials will tell you. You target a proteins, you develop a clinical candidate, you test it in humans, and it doesn’t do them any good (or, in some cases, does this outright harm instead): so is that target a bad idea? Or did your drug not hit it hard enough, or in quite the right way? Or did it do other things that you weren’t aware of that cancelled out whatever good effects it might have had? Want to drop another half-a-billion dollars to try to find out (no guarantees you’ll understand the second or third answers, either)? Welcome to the field! Reductionism has taken us a long way in all areas of science, but the nervous system and its functions are one of the areas where that particular magic wand is least effective.
So phenotypic screening has a lot of appeal. Grow yourself some neurons that do what they do in the human disease, and test your compounds against them directly. Instead of trying to understand the whole disease process up front, find compounds that alter it and go in both directions: forward into the clinic and backwards into the disease mechanism with your new research tools. Ideally, that is exactly what a phenotypic effort is supposed to do for you.
But experienced screeners and CNS types will note that I have performed a silent broad jump in that last paragraph that more resembles the migration of the Arctic tern: grow yourself some neurons that do what they do in the human disease. Oh, yeah. Just go do that. The problem is that neuronal cell culture is a black art, full of nonphysiological oddities, mostly because in vivo neuronal architecture is so complex and (still) poorly understood. Progress has been made, for sure, with moves into three-dimensional cell culture and co-culturing of more than one kind of cell as a mixture (both of which try to recapitulate important features of actual nervous system tissue). But as can be easily appreciated, both of them introduce a huge number of new choices and variables into the culture conditions.
And over all these considerations is the problem that the cells you’re using may not be able to reproduce human biology very well at all – a line from this review is “Perhaps the historical mainstay of neuroscience-driven phenotypic screens is based on the use of immortalized cell lines“, and the cynical reply is “Yeah, and just look at it”. As the authors go on to discuss, two ways around that problem are to use primary cells or stem-cell-derived cultures, but both of those have their difficulties too, of course. Just to pick one, your primary neuronal cells are almost certainly going to be from rodents (at best) since there is, for obvious reasons, a supply problem with living human neuronal tissue for running screening assays.
That’s the cell-culture end of things. On the other end of the process, it’s not always clear how you’ll even know that you’ve hit on the right conditions that mimic the real in vivo situation. You can try to match up with the larger histological features of the disease (generally known best from the late stages, i.e. autopsy), but the earlier stages are harder to recognize and aim for. You may also find that you’ve made something that looks kind of like the disease state in the end, but got there through a completely different path, and that may do you less than no good at all. There is always the option (reviewed in the current paper as well) of going outside of human cells entirely and screening in a smaller model organism (all the way down to yeast or nematodes). Relating those phenotypes to human neuronal ones, though, takes a peculiar mix of bravery and caution, although there have been some discoveries made nonetheless.
As much as I like a good phenotypic screen, I’m fond of saying that a bad phenotypic screen is the worst of both worlds: harder to do and full of even more uncertainties than ever. It should go without saying that there is (for example) no such thing as a reliable cellular phenotypic screen for Alzheimer’s. I attended a phenotypic screening conference earlier this year and gave a talk that hammered on some points that Jack Scannell and Jim Bosley made in this article (blogged here) – namely, that there is no possible substitute for predictive validity in a screening cascade. Small increases in PV and thus assay “transferability” towards clinical relevance are worth a great deal, although they’re frustratingly hard to measure. The entire idea behind running phenotypic assays in the first place is to have improved predictive validity compared to the alternatives, so if you haven’t done that, you are setting up for a waste of time, money, and resources.
But with all of these concerns, this is still a very worthwhile area of research, because it still has the best possibilities for finding new modes of action and new chemical matter. (That does tell you something about the alternatives). This review has a lot of solid advice about compound screening libraries, secondary assays, hit triage and more, and anyone getting into this sort of work for the first time had better read up to make sure that they haven’t missed some of the issues. As with many other areas of drug discovery, the state of the field is simultaneously a warning signal and an invitation: any advance that can be made will be very welcome indeed, and there are still a huge number of things that haven’t been tried. Go in with a clear head and appropriate skepticism, and you’ll increase your chances of actually finding something – and there’s a lot that needs to be found.