In a way, it's unsurprising that the world's reliance on mathematics has rocketed over the last decade. Throughout history, there has been a growing use and sophistication of calculations underlying advances in technology and science. What's unprecedented now is the tremendous rate of increase.
July / August 2004
The 10th anniversary of a publication like Scientific Computing World is an excellent time to take stock of the rapidly developing field of scientific computing, whose importance and impact is still in the early stages of maturity in comparison to the impact of computerisation in other industries.
The past several years have been challenging for most sectors of the economy, and the pharmaceutical industry has been no exception. Although the demand for superior medicines remains high, there is continuing pressure to deliver more, better, and increasingly sophisticated new therapies at decreased cost and under an increasingly stringent regulatory burden. As a result, the industry faces dramatic challenges to increase the efficiency and productivity of its research - challenges that can be met only through substantive changes to the research and development process.
The industrialisation of the laboratory has resulted in the generation of more data than ever before. Whether scientists are performing medical research, manufacturing steel, or testing the quality of food, the challenge is the same: more samples, more experiments, and more data must be processed in less time, with better quality, and at less cost. The pressure is on for laboratory managers, and traditional informatics solutions such as LIMS need to adapt to support these tougher requirements in a wider, enterprise environment.
Developments in the life sciences are resulting in enormous amounts of information being generated at an unstoppable pace.
In the past decade, technology has evolved to create ever-growing volumes of data, and new software is being created to manage it. Information technology (IT) is no longer just an administrative function for life sciences. IT is now a critical foundation for the present and for the future of science.
The stage is set for accelerating the pace of discovery in engineering and science. The vast and rapidly growing amount of data and information, with increasingly complex interrelationships, is becoming so much more accessible to researchers and analysts. Massive databases, the internet, and powerful search engines enable these data to be accessed and shared easily and quickly. The information is rich and varied, due to inexpensive and sensitive measurement systems, improvements in sensors, and technologies in new areas such as proteomics and genomics.
The past decade has seen what J. P. Garnier, chief executive of GlaxoSmithKline, describes as a 'productivity crisis' in pharmaceutical research and development. In 1992, hopes were high that the human genome project heralded an era abundant in new, targeted medicines. However, since that time, the number of new chemical entities (NCEs) launched has declined by 30 per cent, while pharmaceutical R&D expenditure has grown by 20 per cent each year. Why this apparent dichotomy?
For hundreds of years, formal scientific communication could be characterised as the publication and exchange of papers consisting of words, mathematical equations, and pictures. The knowledge gained by the readers of such papers consists solely of what can be absorbed through their eyes and into their minds.
We have long known about the complex interactions among various areas of physics, and these interactions are becoming more complex. For instance, a structural-mechanics model in the area of MEMS (microelectromechanical systems) must take into account thermal strains, fluid interaction, and forces induced from electromagnetic phenomena, all of which typically interact in a nonlinear way. Only recently have we developed tools to model such complex interactions accurately.
Over the past decade, advances in informatics have had a '10X' effect on the life sciences, catapulting the genomics revolution and helping to lead the way to the era of personalised medicine. Today, information technology is a ubiquitous part of every research laboratory, complementing traditional laboratory research with knowledge-rich tools for biological studies.
Sophia Ktori investigates the use of informatics software to increase data integrity in the laboratory
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As AMD launches its latest FirePro GPU, Robert Roe investigates a new suite of open-source tools, released by the company that convert code from CUDA into C++