Novartis has been looking pretty impressive lately. They've announced promising data for their odd immunosuppresive drug Fingolimod (FTY720) in multiple sclerosis therapy. The study isn't very large (255 patients), but the statistics versus placebo look pretty strong. The compound is also showing promise in transplantation, and no doubt the company is looking into other autoimmune disorders as well.
I should note that the drug's target (which appears to be a sphingosine phosphate receptor) wasn't known for many years. It started out as a structural variation on another compound with known effects, it but turned out to have a different (and more useful) profile. This one, if it works, will be more a triumph of persistance and deep pockets rather than drug design, but we'll take 'em where we can get 'em.
The company also has reported data on a new bisphosphonate (Aclasta, aka Reclast) for osteoporosis, notable because it's only dosed once a year. This one had over seven thousand patients, followed for three years, so it's a substantial piece of work, with what appear to be very strong statistics indeed. Novartis appears ready to hammer Fosamax (aledendronate), which has been coining money for Merck for many years now, since they specifically studied a subgroup of patients who were switched from that drug.
One of the notable things about these two drugs is that they're addressing chronic, slow-moving diseases with difficult clinical endpoints. These therapeutic areas are tough to work with in the clinic, and very costly to explore. There are many companies in the industry that would immediately try to outlicense a new osteoporosis clinical candidate rather than try to develop it themselves. You won't see many small biotechs trying to go it alone in areas like this, that's for sure.
So even though I make fun of Pfizer (especially) for being too huge, Novartis is one of the counterexamples. They (along with Merck and GlaxoSmithKline) show that size can have advantages, if you use some of that muscle in the research buildings. FIguring out why some large research organizations are more productive than others, and what part of that isn't due just to chance, has stumped better pundits than me, though. . .