Text Box: Bioinformatics Opportunities

Date Published: February 2005, Pages: 274, Tables: 7, Figures: 16    

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Summary
Text Box: Sample Pages  CONVERGENCE OF INDUSTRIES The convergence of biotechnology and computing has already resulted in a number of alliances, which could result in mergers between previously distinct industries. In future, we may see a combination of pharmaceutical and computing firms bringing together their research as well as IT capabilities. Using the computer to extract, understanding and manipulate genomes and other biological macromolecules depend on the quality of the collaborations which are established in the field. We are witnessing the convergence of biotechnology and computing in the form of alliances and mergers. Some instances include the alliance between Lion Bioscience AG of Germany and IBM. Other technology firms such as Compaq Computer Corp, Sun Microsystems and Motorola have also entered into alliances with biotechnology as well as research institutes. The alliance types range from DNA-sensitive gene chips, software to integrate biochemical libraries and "in silico" research, involving modelling drug effects in computers. A prime focus in many cases is the fast-growing field of proteomics - the interaction of genes, proteins and disease - which requires computing power measured in teraflops, or trillions of operations per second. Proteomic alliances include US firm Myriad Genetics Inc's link with Hitachi Ltd and Oracle Corp; IBM's deal with MDS Inc of Canada; and Britain's Oxford GlycoSciences Plc's joint venture with telecom equipment group Marconi Plc. In future we may see alliances between pharmaceutical, software as well as firms, which have strong marketing capabilities. The field would also witness the entry of new players such as computing and telecommunication firms. One possibility is that information technology (IT) companies, aware that biotech cannot function without their help, might end up taking a royalty of drugs their technology has helped develop. As researchers probe beyond the 35,000 or so genes in our bodies to unravel the role of myriad proteins in disease, the complexity of datasets is being multiplied many times over. Hewlett-Packard, Hitachi, IBM, Oracle, Sun and SGI are among the IT companies that are most involved in bioinformatics. There are between 5O and 100 standalone companies, the majority of which are small, venture capital-backed outfits. They include bioscience firms that do both gene discovery and contract gene-data analysis, such as Gene Logic, Millenium, Curagen, Human Genome Sciences; specialists in data content, such as Structural Bioinformatics, Celera and Incyte; and software and system peddlers such as Rosetta Inpharmatics, Compugen, Netgenenics and InforMax. In addition, there are outsourcing companies-Lion Bioscience is the best known of these, because it has signed a $100-million bioinformatics deal with German pharmaceutical giant Bayer AG. PROTEINS AS A DRIVER Proteins are twenty times more numerous than genes and play a role in nearly all human diseases. There are massive efforts on to define the structure and the interaction among proteins and the relationship of their morphology to functions in the body. Unlike genes, proteins are variable, and change function with their shape. Measuring and studying them in the lab has a much lower throughput than with genes-hence the drive to apply computation to the field. Proteomics' complexity is escalating at a very fast pace and in this case, Computing power and applied mathematical algorithms are the big limiting factors.  In biotechnology, the data is going from terabytes (a trillion) to pedabytes (a quadrillion) sooner than in any other industry. To break through these limits, IBM is building a dedicated bioinformatics machine called Big Gene at a cost of about $100 million. Its mission is to model the way human proteins fold into various shapes. At 1,000 times more powerful than Deep Blue-IBM's computer that defeated legendary chess master Garry Kasparov Big Gene will process at speeds 5,000 times faster than a typical PC. Its water-cooled, custom-designed silicon chips contain only 57 instructions. By comparison, today's RISC and CISC chips have hundreds of them. Having fewer instructions helps streamline processing tasks. Big Gene represents a major step toward the distant goal of continuous computing, since it has the capacity to diagnose glitches, breakdowns and malfunctions of hardware or software and take appropriate remedies. In another manifestation of the convergence of biology and electronics, companies such as Hitachi Ltd., Oracle Corp. and Compaq have stepped across IT frontiers to make seed investments in life-science firms. Compaq expects its life-sciences portfolio to reach at least $100 million within a few years. Celera used hundreds of Compaq's AlphaServers in its race with the National Institutes for Health-- backed Human Genome Project to complete the mapping of the human genome. The historic-and often antagonistic-race of algorithms, software, hardware and knowledge management ended when the two sides made a joint announcement in June 2000. The transformation and synthesis of biological research and IT is irreversible. Bioinformatics is on the verge of a big evolutionary step-the development of in silico biology (essentially what Big Gene will do) wedded to traditional "wet" or in vivo bench biology. Here the bench researcher works in tight conjunction with the computer-each advancing the process in their, or its, own way. The researcher makes sure, for example, that a data-mining exercise does not fall into the frequent mistake of going down the wrong path; the computer works through algorithms that test a particular hypothesis and may save years of bench work. BIOTECH ALLIANCES In total, there are more than 150 biotechnology related alliances, covering a range of technologies including DNA-sensitive gene chips, software to integrate biochemical libraries and "in silico” research, involving modeling drug effects in computers. Proteomics is an area, which is fast growing and witnessing a number of alliances. Proteomics studies the interaction of genes, proteins and disease - which requires computing power measured in teraflops, or trillions of operations per second. Proteomic alliances include IBM's deal with MDS Inc of Canada, US firm Myriad Genetics Inc's alliance with Hitachi Ltd and Oracle Corp and Britain's Oxford GlycoSciences Plc's joint venture with telecom equipment company Marconi Plc. In bioinformatics, IBM has entered into an alliance with Lion Bioscience to offer biocomputing tools to drugmakers. Alliances are also being witnessed in areas such as gene chips or microarrays wherein semiconductor manufacturers are joining with biopharmaceutical firms to cater to the growing market for the diagnostic devices.  Text Box: Abstract With vast amounts of information being generated due to advancements in biotechnology, there arises a need to effectively control and manage the information so generated. Information Technology provides a mechanism more popularly known as bioinformatics, which facilitates this process. Information technology (IT) has become a critical factor in pharmaceutical research and development (R&D). Bioinformatics is the computer-assisted data management discipline that helps us gather, analyze, and represent information in order to educate ourselves, understand life’s processes in the healthy and disease states, and find new or better drugs. This field has exploded out of the world of molecular biology and the Human Genome Project. Pharmaceutical companies are achieving increased research efficiency by the introduction of new approaches to the design, synthesis, screening and optimization of drug candidates. IT is an important support function for all of those activities and there are certain functions and operations that cannot be performed without IT. Informatics represents the deployment of Information Technology to manage, analyze, and store biological data. Beyond data management, informatics represents the only way to analyze large pools of genomic information. Informatics finds application in Target Validation, Lead Optimization, Exploratory development etc. Bioinformatics plays a key role in functionalities such as gather, store, classify, analyze, and distribute biological information derived from sequencing and functional analysis projects. In Bioinformatics, the real long-term value lies in converting the data into useful therapeutics and hence efforts are on to make the bioinformatics tools as standardized and easy as possible, which is similar to the development of standardized computer operating systems. Most publicly held informatics companies had initial public offerings in the second half of 2000. Since then, the biotechnology index has suffered a major setback, and informatics stocks have reacted in sympathy mostly to the downside. Growth in the informatics industry is largely contingent on continued spending on drug discovery. The market for Bioinformatics isn't large enough to support a company built around one or two high-cost software programs targeted to a relatively small user group. As we assess the market or potential market of Bioinformatics we must consider the strategies effective to reach different, or all, parts of the potential market. Strategies focused at the high margin big Pharma market (limited in opportunities) or strategies designed to embrace all biological scientist (but of reduced or variable margin). Also, certain bioinformatics-based companies are leveraging their technologies to become fully integrated drug discovery operations. Other bioinformatics companies are merging with drug discovery companies, resulting in a substitute technological approach to drug development. The convergence of biotechnology and computing has already resulted in a number of alliances, which could result in mergers between previously distinct industries. In future, we may see a combination of pharmaceutical and computing firms bringing together their research as well as IT capabilities. In future we may see alliances between pharmaceutical, software as well as firms, which have strong marketing capabilities. The field would also witness the entry of new players such as computing and telecommunication firms. The challenge facing bioinformatics researchers is simply making sense of the plethora of genomic data while constantly refining their technology, research approaches. The real opportunities are in finding out how all the shards of information relate to one another, and what this means for real world applications.