Globalization of Science
Edison Liu, President and CEO, The Jackson Laboratory
March 2012 | The past ten years have seen tremendous changes in the power and utility of sequence information, and in the pace of globalization. The advance of genomics technologies has dramatically increased the impact of genetic information on biological investigations. Gene hunting is no longer a molecular exercise but a computational sport and the scale of the studies have elevated from single gene analysis to whole genome reconstructions. Just as analytical firepower from computers enabled robotics thus moving analysis to action, genomics is enabling synthetic biology, which promises to be a game-changer.
The second trend, globalization of science, has more important social and political ramifications. In the last 10-15 years, the balance of scientific productivity has equilibrated to include Asia. Science and innovation is no longer just the domain of North America and Europe. In fact, in certain areas, Asia is potentially leading. The location of the world’s most powerful genomics center—BGI in China—was inconceivable just ten years ago. More than the simple production of data, this means that innovation, which is the fuel for the new economy, will be found in the East.
In the years ahead, I predict that we will be using massive biological data that includes genomic, transcriptomic, and metabolomic data to reconstruct complete systems. Understanding and harnessing biological/genetic complexity will provide more nuanced (and correct) medical predictions, and will allow us to reconstruct complex biological systems for production. The latter will give us whole organism solutions to crop improvements, environmental remediation, and biomass conversion.
Medical solutions for sustaining health will now come from a systems understanding of disease. The systems comparisons between disease models in the mouse and the human will be the key to new medicine. For example, why a mutation causes disease in one species and not the other provides the genetic clues for new cures. Moreover, the understanding of disease mechanisms will be used to reconstruct the necessary components to enhance an individual’s robustness against disease and infirmity—which will be the foundation for future preventative medicine. This shift from data generation to complexity analysis, to systems reconstruction will require deep understanding of model systems such as the mouse.
What will the key challenges be for the entire biomedical research community? I project that they will be mainly cultural, managerial, and pedagogical. Indeed, limiting resources because of economic austerity are challenging. But, many of our systems are outdated and insufficiently forward looking. Our Ph.D. programs will need to be more quantitative, modular, and less domain intensive. This means that fewer individuals should be trained as focused cancer biologists but as individuals who use cancer biology as a model system to answer fundamental biological and technological problems. Our promotion systems that reward isolated brilliance will have to accommodate collective contributions. As a community, we will need to find ways to establish enabling infrastructures that will position us for future strength rather than to support historical biases. All this means that some old structures must be taken down to allow for new ones to be built. This is never easy.
But what would the benefit be? The 21st century will be among the most challenging for humanity as food and energy become scarcer, as our populations age, and as the environment continues to degrade. It will be innovations in biosciences—and their implementation—that will save us all.