Science is an evolutionary driving force; discoveries go on all the time, largely independent of other major influences like the economy or politics. Every so often, though, a revolutionary paradigm shift occurs that surfaces in multiple forms, each of them radical in its own right. Systems biology is a good example.
The Economist ran an article this week on systems biology that focuses mostly on - as one might expect - the economic implications. Here's the link, with the caveat that you may need an Economist subscription to look at the full article: Biology | All systems go | Economist.com.
The rationale for systems biology is described in the article as follows:
A central tenet of most scientific endeavour is the notion of reductionism—the idea that things can best be understood by reducing them to their smallest components. This turns out to be immensely useful in physics and chemistry, because the smallest components coming from a particle accelerator or a test tube behave individually in predictable ways.
In biology, though, the idea has its limits. The Human Genome Project, for example, was a triumph of reductionism. But merely listing genes does not explain how they collaborate to build and run an organism. Nor do isolated cells or biological molecules give full insight into the causes and development of diseases that ravage whole organs or organisms. A complete understanding of biological processes means putting the bits back together again—and that is what systems biologists are trying to do, by using the results of a zillion analytical experiments to build software models that behave like parts of living organisms.
The article spends a good bit of time talking about the work of Denis Noble, founder of The Physiome Project. The physiome is yet another addition to the list of "*omics" that are revolutionizing biology and biomedical research. the Project defines it as follows:
The physiome is the quantitative and integrated description of the functional behavior of the physiological state of an individual or species. The physiome describes the physiological dynamics of the normal intact organism and is built upon information and structure (genome, proteome, and morphome). The term comes from "physio-" (life) and "-ome" (as a whole). In its broadest sense, the physiome should define relationships from genome to organism and from functional behavior to gene regulation. In context of the Physiome Project, it includes integrated models of components of organisms, such as particular organs or cell systems, biochemical, or endocrine systems.
The implication is that physiomics encompasses all the other *omics. In keeping with this idea, physiomicists like Noble are creating vast holistic mathematical models of organs and even whole organisms. The pharmaceutical industry is gradually moving to a systems biology approach to research, out of necessity, as the Economist article demonstrates:
Around 40% of the compounds that drug companies test cause arrhythmia, a disturbance to the normal heart rate. Drugs such as the anti-inflammatory medicine Vioxx and the diabetes treatment Avandia have been linked with an increased risk of heart disease. The result is that billions have been wiped off their makers' share prices.
...Dr Noble is now part of a consortium involving four drug firms—Roche, Novartis, GlaxoSmithKline and AstraZeneca—that is trying to unravel how new drugs may affect the heart. Virtual drugs are introduced into the model and researchers monitor the changes they cause just as if the medicines were being applied to a real heart. The production of some proteins increases while others are throttled back; these changes affect the flow of blood and electrical activity. The drugs can then be tweaked in order to boost the beneficial effects and reduce the harmful ones.
Systems biology thus speeds up the drug-testing process. Malcolm Young is the head of a firm called e-Therapeutics, which is based in Newcastle upon Tyne. Using databases of tens of thousands of interactions between the components of a cell, his company claims to have developed the world's fastest drug-profiling system. In contrast to the two years it takes to assess the effects of a new compound using conventional research methods, Dr Young's approach takes an average of just two weeks. Moreover, the company has been looking at drugs known to have damaging side effects and has found that its method would have predicted them.
Discovering deleterious side effects thus reduces the potential liability faced by marketers of new drugs, and also creates highly efficient new ways to discover indications to which a candidate drug may be applicable.
Systems biology is a driving force underlying our scenario, but in and of itself it is largely predetermined due to its evolutionary nature. Applications of it, though, might emerge as critical uncertainties. Imagine a scenario in which systems biology leads to a breakthrough cure for breast cancer or melanoma. Such a discovery is highly uncertain, but if the scenario did play out, it could lead to a dramatic increase in funding for translational clinical research. Most scenarios that are "realistic" extrapolations from the present will assume that funding stays the same or reduces, the logic being that with the wars underway and the Feds pushing for a universally interoperable EHR, and with the NIH's historical leaning toward basic science, translational research could at best sustain its current funding levels.
Hmmm... I'll have to go back to the drawing board and see how systems biology affects the diagram I've been creating. More news at 11...