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.
The completion of the Human Genome Project has shifted research emphasis to the functional aspects of cell biology, including the role of proteins and pathways. Today, proteomic research is generating terabytes of data and, compared with genomic data, these data are much more complex due to the structure of proteins and the multiple pathways in which they are involved.
In fact, the next wave of critical advances in mass spectrometry, a fundamental proteomics tool, is more likely to be in the informatics for mining the data produced from the machines than in instrument improvements alone.
An example of one such advance is the Applied Biosystems 4700 Proteomics Discovery System, which enables a new class of powerful experiments called Results Dependent Analysis (RDA). In RDA, protein identification resulting from mass spectrometry drives the further acquisition of data from complex samples, and the automatic searching of these results against protein databases to derive definitive identification. Further, the software provides direct links to biological/molecular function, SNP sites, alternate splice forms, and comprehensive genetic information available online through the Celera Discovery System.
Advances in genomics and proteomics, and increasing throughput levels, have meant an increase in operating complexity - a challenge that can be solved only with sophisticated informatics tools. Managing an ever-more complicated workflow has become vital for laboratories to increase productivity, improve data quality, and reduce costs. The elaborate network of interrelated biological processes in living systems cannot be studied or understood using a single technology, necessitating the development of highly advanced informatics solutions capable of integrating disparate data and research applications.
As a result, there is an increasing focus on workflow-based solutions. Advances in Laboratory Information Management Systems (LIMS) are geared toward enabling a more seamless transition along the continuum of research applications. Every lab is unique, however, in terms of workflow management, processes, and technologies employed and added over time, so a LIMS must be flexible, user-configurable, and open, while ensuring security and complying with governmental regulations, such as FDA 21 CFR Part 11.
Other recent advances in LIMS technology include the use of web services to simplify the deployment and maintenance of the system over geographic sites, and the ability to link to other mission critical applications such as Electronic Document Management Systems (EDMS), Manufacturing Resource Planning (MRP), Enterprise Resource Planning (ERP), and Manufacturing Execution Systems (MES). Future advances are expected to streamline the information management process across the entire continuum of discovery and development.
More sophisticated technologies for visualising and modelling biological data and cellular systems also are needed to make use of the available data more efficiently and intelligently. For example, the ability to predict the function of a gene or protein before wet-lab experimentation can save not only time, but also significant costs by reducing the experimental failure rate. Future progress in this area will depend on access to high-quality, functional data, new algorithms, 3-D modelling and visualisation software, and increased computing power.
There is little doubt that the increasing availability of high-quality biological data and advances in technology are transforming the study of complex biological systems. Further integration of raw biological information with annotated content, and better linkage between in silico biology and wet-biology assays, instruments, and software will be required to enable the next generation of life science discovery. Additionally, higher levels of automation and miniaturisation will be required to make large-scale studies more efficient and affordable.
Finding the critical interfaces where further integration and automation are required is the responsibility of technology and data providers. We recognise and embrace this challenge and have implemented an Integrated Science initiative, iScience, focused on tailoring our research and development activities on the design of innovative new products, services, and knowledge resources to integrate the myriad aspects of the discovery process.
Advances in informatics technology will continue to shape the life sciences. The ultimate goal is that researchers will be able to more easily and cost-effectively advance their understanding of the genome, proteome, and cell biology to conquer the remaining complex challenges in understanding human health and preventing, treating, and curing disease.
Bruce von Herrmann is senior director and general manager for the Global Informatics Software and Professional Services, of Applied Biosystems
