[briggsbio]

Actually overall, in vivo animal testing on vaccines, antivirals, and antibiotics are typically quite predictive from animals to humans. These types of tests are not historically very predictive when moving from in vitro to in vivo animal studies, however. This is typically because the treatments and vaccines are structural and/or expression-based (exploit a bacterial surface protein and poke holes in the cell, use a virus to get into T-cells and inject genetic material to let them identify and kill polio, etc). (yes, oversimplified). But moving from cell culture to a living organism This doesnt always work out. If it does, then it's relatively easy to confirm the effect if it works in animals to humans (virus is gone/never infects, etc). So more antibiotics and vaccines fail from in vitro to in vivo than from animal to human data.

In treating diseases of inflammation, rheumatic disease, pain, etc., it is generally quite predictive when moving from in vitro to in vivo animal studies (e.g. is it down-regulating inflammatory transcription factor NF-kB, or not?). But it becomes much less predictive translating endpoints from animals to humans. That's, very generally, because it is difficult to assess disease measures of improvement in inflammation in animals and translate that to humans (pain, discomfort, edema, these processes may present much differently in rats versus humans, for example). Great animal data may not mean you'll get such a strong effect in human subjects, and thus the failure rate for these drugs in clinical studies is quite high compared to vaccine and antibiotic human trials, because those vaccines were shown to be ineffective earlier in development. This was a very general explanation, to be sure, and I'll dig through my archives for some papers on this and try to add links later.

[fauigerzigerk]

That's very interesting. Do you have an idea in which of these two categories cancer treatments typically fall?

[briggsbio]

That depends on the cancer and depends on the approach (structural, genetic, or immunological).

The difficulty in cancer treatment is that you're dealing with a natural biological process gone awry. It's not like viral or bacterial infections, where you're fighting something off. You're dealing with aggregations of unwanted mutations and cellular proliferation (over simplification warning).

Chemotherapy is less trying to alter a process than it is dropping a bomb in the body and hoping that you kill the cancer before killing the patient. There are some incredibly effective chemotherapy agents that will never make it to market because they are just too toxic.

Gene therapy approaches are making promising moves, but it is very early.

There are some pretty cool structural approaches, such as protein conjugated nanotubes that lyse cancer cells under infrared light (Stanford and Oklahoma researchers), but these too are early, and for only specific tumor types.

Cancer is a huge problem that takes a multifaceted, case-by-case approach. Lots of tools in the tool shed, and it's growing every year. I feel in my heart that one day in the future, cancer will be called "the biggest problem of the last generation." But there is much work to be done.

[DavidSJ]

In this case, they did successful in vivo tests on mice with H1N1.

[briggsbio]

Exactly my point. The previous commenter worried about the rash of "amazingly promising research" articles followed by "FAIL." With this type of promising animal data, the prospects are good.