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Weekly UpdatesSUMMARY
The convergence of information science, nano-scale science and molecular biology is creating new technologies with potential to change radically industrial, economic and social structures in the 21st century. The development of convergent technologies such as bioinformatics, DNA diagnostics, molecular electronics and neural computation are revolutionizing the traditional interaction between researchers and industry and society. New models for research management are evolving based around networks which break down the barriers between traditional disciplines.
Examples of European networks are discussed in terms of stages of development and the implications for technology transfer and application of research results. The case of nanotechnology is explored and the need for rapid changes in the education system at all levels, enhanced understanding by industry decision makers and adequate dialogue with society is emphasized. The potential markets are enormous but lack of communication between all the parties involved could lead to poor technology transfer and poor returns for the very large sums expended in research.
KEYWORDS
converging technologies; European networks; nanotechnology; NBIC; change drivers; education changes; social impacts of new technologies; technology transfer
INTRODUCTION
The convergence of rapidly developing information, communication and media technologies together with the deregulation of international trade, capital and technology markets and of domestic economic systems has created a new world economic structure, the so-called Global Knowledge Economy. The defining characteristics of the Global Knowledge Economy are globalization and the rising knowledge intensity of goods and services (Sheehan and Tegart 1999).
The rise of the Global Knowledge Economy has changed the culture of research and it is now recognized that the most productive research is increasingly interdisciplinary and team-based. In this situation knowledge flows across interdisciplinary boundaries, human resources are more mobile and the organization of research is more open and flexible (Gibbons et al. 1994).
As a result of these changes we have seen the simultaneous development of three major new interdisciplinary areas of science and technology arising from the established disciplines of physics, chemistry, biology and engineering in different combinations, namely:
* Information Science--the understanding of the physical basis of information and application of this understanding to most efficiently gather, store, transmit and process information.
* Nanoscale Science--the understanding and control of matter on the nanometer length scale to create new materials, devices and systems.
* Molecular Biology--the understanding of the chemical basis of life and the ability to utilize this understanding for a new approach to biology, new avenues for drug development and drastic changes in healthcare systems.
The knowledge base in each of these areas has the capacity to increase exponentially for several decades into the future, assuming that the current rate of growth of the research effort is maintained. Each field by itself offers tremendous opportunities and also potential dangers for society. Great prospects and challenges are becoming evident in the convergence areas where two or all three of these areas overlap. The difficulties that are inherent in this convergence process are that:
1. each area by itself is so large and intricate that no single human being can be an expert in it;
2. each area has already developed a language and culture that is distinct and difficult to comprehend by those working in other areas, leading to communication problems;
3. there is a lack of interaction between researchers and potential users of the technologies.
These difficulties are leading to the recognition that cognitive science will become an increasingly important field of research in order to effectively link and employ the new technologies arising from convergence. In turn the new knowledge base developed in these technologies will enable major advances in the study and application of cognition by allowing construction of better models of brain function and of human performance. These are being referred to as the four major NBIC (nano-bio-info-cogno) technologies and are seen as the drivers of science and technology and their application for the benefit of society in the 21st century (Anton et al. 2001, Roco and Bainbridge 2002, APEC CTF 2002, APEC CTF 2003, Nordmann 2004).
An example of convergence at the info-bio interface is that of bioinformatics--the application of analytical theory and practical tools of mathematical science and computing to provide the computational management of biological information. The development of high-throughput gene sequencing has resulted in the identification of genome sequences of many organisms from bacteria to the human sequence, each of these with thousands of genes. Concurrently advances in protein separation and detection at a high throughput have led to the identification of millions of proteins expressed by genes under a given condition at a given time. The amount of data generated doubles approximately each year. The need to handle these vast amounts of data has led to new approaches to computing hardware and software and the creation of a new industry with a global market estimated to reach US$ 40 billion in 2005. The future growth of the information technology industry will be in bioinformatics and not communications.
A driver in high throughput analysis systems for genomics has been the development of DNA micro-arrays which arises from convergence at the bio-nano or rather small-scale since micro-technology is also involved) interface. The surface of the micro-array (about 1 sq. cm.) consists of a glass or silicon substrate on which fragments of DNA strands from a known source are fixed by chemical reaction. To analyze a sample, the target material, labeled with a fluorescent molecule, is then exposed to the array to see whether it reacts with any of the strands. By locating and quantifying the fluorescent signals in the array the nature of the target material can be identified in one step. It is possible to analyze tens of thousands of genes simultaneously on one array and thus determine gene sequences. Analogous micro-arrays are used for high throughput analysis of proteins using glass or plastic surfaces coated with molecules such as antibodies, antigens and enzymes. Such combinations of physical and biological structures for rapid DNA diagnostics open opportunities for new approaches to health care.
An example of another interface (i.e., infonano), arises from the limitations of silicon chip technology as it approaches smaller and smaller feature sizes following the continued exponential decrease in size achieved over the past few decades (so-called Moore's Law). Continuation of this trend suggests that feature sizes around 35 nm will be needed by 2015. A number of engineering challenges exist in achieving this target with existing technology such as increasing manufacturing defects, interconnections and thermal loadings associated with very high device densities. Further the extremely high cost of fabrication plants is a problem for investors. Thus research is proceeding on possible alternatives such as molecular electronic devices which could operate as logic switches through chemical means using synthesized organic compounds. These devices can be assembled chemically in very large numbers and organized to form a computer with very low power consumption. Significant challenges exist with regard to stability, defect density and interconnections but in the longer term molecular electronics could be competitive with silicon technology.
An example of a further interface (i.e., infocogno) arises from study of neural computation and neural networks. These are highly interdisciplinary fields drawing on statistics, neuroscience, psychology, physics and linguistics. The original motivation for the field was the modelling of the function of neurons and neuron assemblies within the human brain. Staring from this motivation and the models that have been developed, the fields have expanded in directions such as data analysis, on-line learning and systems control. A further development is the nano-cogno interface where computational neural networks are being used to predict properties of nanostructured materials and optimization and control of nanodevices. Conversely nanodevices can be used to monitor brain responses to vision, sound and touch stimuli and hence assist handicapped people.
These examples serve to show that the convergence of technologies is a powerful dynamic process which is revolutionizing the traditional interaction between science, technology and society. This has implications for education of both researchers and of professionals, technicians and managers in industry using these new technologies. The traditional separation of disciplines in academic institutions is being broken down by the move to team-based interdisciplinary research and this approach needs to be translated into new learning approaches. Policymakers and society in general need to be informed so that they can be involved in debates on applications of these technologies since many social, ethical and legal issues are raised.
NETWORKING BETWEEN RESEARCHERS
Of immediate concern is the need to ensure collaboration between researchers both on a national basis and on an international scale to ensure that breakthroughs are rapidly exploited and that duplication of expensive research is minimized. Such collaboration can also assist in identifying opportunities to use the technologies for the benefit of society. The creation of networks of likeminded people is a strong driver for collaboration.
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