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.
Although there is a significant desire for more mature, industrial-strength IT to manage the enormous amounts of information generated by the life sciences industry, researchers have been careful in their embrace of the advances in information processing and management.
Historically, research was an isolated process. Each scientist would undertake projects in an individual manner and the resulting data would be stored or managed in isolated silos. Furthermore, companies purchased IT applications that ran only on one box, on one operating system, or in a client-server architecture, adding to the siloed operations.
The huge effort that has been undertaken to map the human genome catalysed the adoption of technology to become a part of the scientific discovery framework. For example, without the advances we've seen in just the past 10 years in technology (such as the use of computational chemistry and high throughput screening), the field of pharmacogenomics would not be something that researchers are beginning to explore. Pharmacogenomics targets the creation of medicines for specific genetic make-ups.
This concept will require vast amounts of structured and unstructured data on a scale that has not been seen before, because it seeks to pinpoint genetic make-ups that require new medicines and treatment.
The more data that is generated, the more powerful IT must become. The revolution that lies ahead will be driven more by information-based science than the traditional laboratory-based science of the past. Information-based science will accelerate all phases of drug discovery, development, and manufacturing.
Information, and the technology to master that information effectively, is now the enabler. Information will be more useful for researchers and clinicians in the future, once data is centralised. IT and discovery will be seamlessly linked. At present, researchers and clinicians must collaborate to create opportunities for personalised medicine.
How will all this information be managed today and tomorrow? Enter grid computing.
Grid computing's role in the life sciences industry is simple: it enhances the ability to access distributed data, integrate a variety of data types, manage vast quantities of data, collaborate securely, and find patterns and insights.
Grid computing is based on two simple components: virtualisation and provisioning. Virtualisation severs the hard-coded association of resources to systems. Provisioning makes resources available whenever and wherever needed.
For example, instead of attaching disks to each computer, storage can be virtualised into a central pool, and allocated or provisioned to computers when they need it.
Many larger pharmaceutical companies have very fragmented IT infrastructures filled with customised applications, resulting in major problems for data consolidation.
Research scientists need to query data from distributed sources, which adds considerable time and effort to the overall process.
Grid computing provides for consolidation, but not by building one giant computer. Grid computing is distributed consolidation - a smaller number of larger resource pools and processing centres - and dynamically allocates resources as needed. Allocating these resources allows researchers to access critical information to accelerate the discovery pipeline. Grid computing adapts to and dynamically aligns with the life sciences industry.
Grid computing also enables standardisation. Standardisation allows different networks to communicate with each other, offering far more collaboration among research groups. The silos of information may become a part of the past as collaboration technologies become Grid-centric. Standard components will build the best grids, and the most powerful grids will be built with the lowest-cost hardware. Businesses will save money, as well as having faster computers and receiving better allocation for higher utilisation and responsiveness.
Information technology will help pave the path to a future marked by life sciences innovation and discovery. How fast we want the life sciences industry to grow, and how efficient we want it to be, depends on our ability to accept and use the tools given to us, to collect information and meld it with other key life sciences elements (e.g. Chemistry and Biology) into a tangible form to benefit human life.
Dr Susie Stephens: Principal Product Manager, Life Sciences
Dennis Constantinou: Senior Director of Life Sciences
Oracle Corporation
