Wavefunction has a good post in response to this article, which speculates "If we designed airplanes the way we design drugs. . ." I think the original article is worth reading, but some - perhaps many - of its points are arguable. For example:
Every drug that fails in a clinical trial or after it reaches the market due to some adverse effect was “bad” from the day it was first drawn by the chemist. State-of-the-art in silico structure–property prediction tools are not yet able to predict every possible toxicity for new molecular structures, but they are able to predict many of them with good enough accuracy to eliminate many poor molecules prior to synthesis. This process can be done on large chemical libraries in very little time. Why would anyone design, synthesize, and test molecules that are clearly problematic, when so many others are available that can also hit the target? It would be like aerospace companies making and testing every possible rocket motor design rather than running the simulations that would have told them ahead of time that disaster or failure to meet performance specifications was inevitable for most of them.
This particular argument mixes up several important points which should remain separate. Would these simulations have predicted those adverse-effect failures the author mentions? Can they do so now, ex post facto? That would be a very useful piece of information, but in its absence I can't help but wonder if the tools he's talking about would have cheerfully passed Vioxx, or torcetrapib, or the other big failures of recent years. Another question to ask is how many currently successful drugs these tox simulations would have killed off - any numbers there?
The whole essay recalls Lazebnik's famous paper "Can A Biologist Fix A Radio?" (PDF). This is an excellent place to start if you want to explore what I've called the Andy Grove Fallacy. Lazebnik's not having any of the reasons I give for it being a fallacy - for example:
A related argument is that engineering approaches are not applicable to cells because these little wonders are fundamentally different from objects studied by engineers. What is so special about cells is not usually specified, but it is implied that real biologists feel the difference. I consider this argument as a sign of what I call the urea syndrome because of the shock that the scientific community had two hundred years ago after learning that urea can be synthesized by a chemist from inorganic materials. It was assumed that organic chemicals could only be produced by a vital force present in living organisms. Perhaps, when we describe signal transduction pathways properly, we would realize that their similarity to the radio is not superficial. . .
That paper goes on to call for biology to come up with some sort of formal language and notation to describe biochemical systems, something that would facilitate learning and discovery in the same way as circuit diagrams and the like. And that's a really interesting proposal on several levels: would that help? Is it even possible? If so, where to even start? Engineers, like the two authors of the papers I've quoted from, tend to answer "Yes", "Certainly", and "Start anywhere, because it's got to be more useful than what you people have to work with now". But I'm still not convinced.
I've talked about my reasons for this before, but let me add another one: algorithmic complexity. Fields more closely based on physics can take advantage of what's been called "the unreasonable effectiveness" of mathematics. And mathematics, and the principles of physics that can be stated in that form, give an amazingly compact and efficient description of the physical world. Maxwell's equations are a perfect example: there's classical electromagnetism for you, wrapped up into a beautiful little sculpture.
But biological systems are harder to reduce - much harder. There are so many nonlinear effects, so many crazy little things that can add up to so much more than you'd ever think. Here's an example - I've been writing about this problem for years now. It's very hard to imagine compressing these things into a formalism, at least not one that would be useful enough to save anyone time or effort.
That doesn't mean it isn't worth trying. Just the fact that I have trouble picturing something doesn't mean it can't exist, that's for sure. And I'd definitely like to be wrong about this one. But where to begin?