I've mentioned before that one of our big problems in the drug industry seems to be finding compounds that work in man. I know, that sounds pretty obvious, but the statement improves when you consider the reasons why compounds fail. Recent studies have suggested that these days, fewer compounds are failing through some of the traditional pathways, like unexpectedly poor blood levels or severe toxicity.
In the current era, we seem to be getting more compounds that make it to man with reasonable pharmacokinetics (absorption from the gut, distribution and blood levels, etc.) and reasonably clean toxicity profiles. Not all of them, by any means - there are still surprises - but the stuff that makes it into the clinic these days is of a higher standard than it was twenty years ago. But that leaves the biggest single reason for clinical failure now as lack of efficacy against the disease.
That failure is the sum of several others. We're attacking some diseases that are harder to understand (Alzheimer's, for example), and we're doing so with some kind of mechanistic reason behind most of the compounds. Which is fine, as long as your understanding of the disease is good enough to be pretty sure that the mechanism is as important as you think it is. But the floor is deep with the sweepings of mechanistically compelling ideas that didn't work out at all in the clinic - dopamine D3 ligands for schizophrenia, leptin (and galanin, and neutropeptide Y) for obesity, renin inhibitors for hypertension. I'm tempted to add "highly targeted angiogenesis inhibitors for cancer" to the list. The old-fashioned way of finding a compound that works, and no matter how, probably led to fewer efficacy breakdowns (for all that method's other problems.)
Another basic problem is that our methods of evaluating efficacy, short of just giving the compound to a sick person and watching them for a while, aren't very reliable. If I had to pick the therapeutic area that's most in need of a revamp, I'd have to say cancer. The animal models there are numerous, rich in data, and will tell you things that you want to hear. It's just that they don't seem to do a very good job telling you about what's going to work in man. I will point out that Iressa, for one, works just fine in many of the putatively relevant models.
The journal Nature Reviews: Drug Discovery (which is probably the best single journal to read for someone trying to understand pharma research) published a provocative article a couple of years ago on this subject. The author (the now late) David Horrobin, compared some parts of modern drug discovery to Hesse's Glass Bead Game: complex, interesting, internally consistent and of no relevance to the world outside. They got a lot of mail. Now the journal has promised a series of papers over the next few months on animal models and their relevance to human disease, and I'm looking forward to them. We need to hit the reset button on some of our favorites.