In fact, 3-D viewing of protein/enzyme structures has been around for quite some time. I remember seeing my first x-ray-determined 3-D structure of egg white lysozyme in the first half of the 1970s. But these were static images on a page (although viewed with the same 2 color glasses worn at movie theaters decades earlier). They could not be easily rotated or otherwise manipulated in real-time. High end graphics workstations were developed in the 1980s and 1990s that made this real-time manipulation possible (or maybe pseudo real-time) but the cost was also high and therefore the technology was limited to a few systems per company. Now that 3-D technology has made its way into sub-$200 video games (and without the need for special glasses), will it impact the every day practices of labs and offices across the industry?
While I know of several rather narrowly defined applications of this technology that should prove interesting—e.g. inhibitor/active site docking studies—in general it is hard for me to see where a 3-D viewing system will add advantage on a broad scale. Still, I would be excited to learn I am in error on this. Perhaps the greatest single reason for my doubts is that the really big problem in our current scientific efforts is that of how to make sense of multi-parameter test results. High content screening systems can produce tens of parameters per test point and gene array systems can produce millions of parameter measures per experiment. We have indeed developed some interesting 2-D viewing tools to help visualize these multi-parameter results (e.g. ‘heat-map’ type graphs) but will moving to 3-D viewing tools make a big difference?
Human Cognition and Multi-Parameter Space
However, in spite of my misgivings there may in fact be a new or at least undeveloped application to leverage the emerging power of inexpensive 3-D technology. I have often pontificated on the issue of multi-parameter space optimization in pharmaceutical R&D in general; and safety assessment in particular. We are producing hundreds to thousands of test parameters in our current pre-clinical safety studies and yet there is no recognized standard or successful example for how to interpret this wide array of information into a simple go/no-go development decision. In fact, I once claimed that the human mind was incapable of doing multi-parameter space optimization once the number of parameters exceeded three or maybe four. I was immediately challenged on this statement by an investigator that claimed facial recognition, speech recognition, and reading handwritten scripts are all examples of multi-parameter optimization that humans do “unconsciously” all the time. His assertion was that the key word I was leaving out in my claim was “conscious”, i.e. that conscious multi-parameter optimization seemed to be limited to just 3 to 4 parameters. So the question of whether there is a broad application for 3-D technology in pharma R&D may boil down to: does this technology allow us to more readily develop visualization tools that tap into our natural or innate abilities to conduct very complex multi-parameter space optimization processes nearly instantaneously?
Ernie Bush is VP and scientific director of Cambridge Health Associates. He can be reached at: firstname.lastname@example.org.