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Sustainable Investment Authors: Pat Romanski

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Sustainable Investment: Article

The Life Sciences Revolution

The Life Sciences Revolution

In the past few years we've seen a revolution taking place in the life sciences, a revolution driven by information technology, which has become the engine of experimental biology. As a result, we are seeing the convergence of information technology and the biological sciences, a convergence that will affect the way we live and that holds the potential to greatly improve the quality and effectiveness of medical care.

Perhaps the term "life sciences" is new to you. The life sciences market includes the pharmaceutical, biotechnology, genomic, e-health, and agri-science industries. This market is essentially dedicated to drug discovery, to understanding genomics, proteomics, structural biology, and emerging areas associated with the study of metabolic regulation, as well as focusing on improving health care as we move toward e-health.

The focus by IT vendors on the life sciences market, and the tremendous excitement associated with it, began in earnest with the nearly complete sequencing of the human genome, a scientific breakthrough that has opened vast opportunities. For the first time in the history of mankind the book of human life has been opened. Jeff Augen, director of strategy for IBM Life Sciences, points out that whereas the industrial and information eras provided us with tools to make our lives easier and to enable effective communications, the next wave, the biology wave, will allow us to improve health and longevity and create a sustainable environment.

This breakthrough wouldn't have occurred without information technology, which is increasingly becoming an integral part of medical research and of the drug discovery process.

Put another way, biotechnology in the 21st century is characterized by the convergence of the life sciences and information technology, which, it is hoped, will result in discoveries that will improve the quality of health care and the quality of our lives. This is not trivial. We are seeing a true revolution in science - exciting, challenging, rewarding, awe-inspiring.

Market Forces Driving the Convergence of Biotechnology and IT
A number of market forces are driving this revolution, the first of which is the application of new techniques to biological research.

New IT Techniques in Biology
Pharmaceutical and biotech companies, as well as academic and government labs, are making increasing use of information technology to handle the large amounts of genomic information needed to accelerate discovery of new targets. Two IT approaches have emerged to address the challenges of generating and dealing with genomic information: one based on automated sequence sample matching and another aimed at computer modeling of biological processes such as protein and cellular interactions. The latter is known as systems biology; it is analogous to the migration that took place in electronic design from using discrete parts to using computer-aided engineering systems. The ultimate migration will be to "in silico" (experimentation by computer simulation). It is this migration to "in silico" research, computer simulation of biological processes, that holds the greatest promise. By using the computer to simulate the experiments and clinical trials that used to take years, we can drastically reduce the costs and increase the efficiency of the drug discovery process. The ultimate goal is to model the disease process at the molecular level. When we are able to accomplish this, we can begin to deliver personalized medicine, delivering the correct drug based on the genetic patterns of the patient. However, we are only on the cusp of this revolution.

We are, however, at a point where the application of information technology to the biological sciences is producing dramatic results. The most obvious of these, as we mentioned earlier, is the Human Genome Project, an international research effort to characterize the genomes of human and selected model organisms through complete mapping and sequencing of their DNA. This project resulted in the coding of the yeast genome in 1998 and the coding of the human genome in 2001.

The reason these breakthroughs are so important is that the human genome not only determines physical characteristics such as the color of our eyes, but also drives the biochemical processes that keep our hearts beating, enable our blood to clot and, most importantly, fight disease. As we begin to understand the structure of the genome, we can begin to understand how it triggers the reactions that fight disease, improving our understanding of how to fight, and ultimately prevent, disease.

Thus the first market force driving the life sciences revolution is the development of new IT techniques in biology. The challenges being faced by the pharmaceutical industry form the second driving force.

Challenges to the Pharmaceutical Industry
The first challenge facing the pharmaceutical industry is really a basic business problem, the time and cost to bring a new drug to market. The average cost of developing a new drug is $802 million, according to the Tufts Center for the Study of Drug Development. It can take over 10 years to develop and get FDA approval for a new drug, and a very small percentage of those approved recoup their development costs.

There are many other statistics: the failure rate of drugs that do appear on the market, the number of those drugs that don't offer a return on the development investment, the number of drugs that complicate rather than heal. One of the most frightening statistics is that nearly 100,000 people a year die taking the wrong medicine. This is the fourth leading cause of death in the U.S., according to a November 1999 Institute of Medicine Report.

The bottom line is that the pharmaceutical industry must change the drug development process. Information technology can help. Informatics, which involves taking available data and applying it, comparing and contrasting, enables companies to leverage IT across the drug development process, resulting in shorter cycle times, cost efficiencies, and more products getting to market.

In addition to the cost of drug development, the industry faces other challenges. Drug pipelines are thinning. It is estimated that more than $30 billion worth of drugs will fall off patent protection in the next five years.

Drug profitability is also a challenge. The length of the approval process (in the U.S.) has been marginally reduced, but scrutiny of clinical trials and manufacturing has become more rigorous.. On average, less than 1 percent of all hits identified during drug discovery are commercialized and less than 30% of new drugs recover their R&D costs during their commercial lifetime. And then there is the gap between expenditures and sales. In the past seven years, the top pharmaceutical companies have seen their R&D expenditures more than double, while the number of drugs entering the market have remained about the same. Blockbusters are harder to come by - the industry can no longer rely on blockbuster drugs to cover the expenses and costs of new research, especially as new drugs are targeting smaller populations. When juxtaposed to the declining rate of new chemical entries (NCEs), this suggests a need to improve efficiency in drug discovery that only IT can provide.

There is also the need to increase productivity to maintain growth. Just to keep pace with the annual industry growth rate of 10%, the top 10 global pharmaceutical players will need to launch at least five significant NCEs per year, according to an Andersen Consulting report, "Pharmaceutical and Medical Products Briefing." The industry is not on track to do this.

And then there is the challenge of managing merger activity. Mergers and acquisitions will continue in order to maintain a critical mass of resources. Managing this activity, coordinating resources, integrating data, will be a major challenge, according to IBM's Institute of Business Value. A large percentage of new drugs come from biotechs. However, biotechs lack the marketing infrastructure; thus there will be increasing collaboration between pharmaceuticals and biotechs, which will require additional IT.

While these are significant challenges to the pharmaceutical industry, they represent an opportunity for us, as the use of information technology will be key to meeting these challenges.

In addition to new IT techniques in biology and challenges to the pharmaceutical industry, the last market force driving the life sciences revolution is the move toward personalized medicine and the promotion of wellness.

The Rise of Personalized Medicine and the Promotion of Wellness
Personalized medicine aims to design and deliver treatments tailored to the specific genetic makeup of the patient. If we could associate the genetic makeup of the patient with how specific drugs affect that genetic type, we could take giant steps toward saving lives.

Personalized medicine can reduce the danger of side effects, cross effects from other medications, and the possibility of a wrong drug being received. It can increase the effectiveness of treatments and chances for recovery. It can provide a new focus on diagnostics and preventive medicine for high-risk population groups. We can look to new diagnostic technologies based on genetic makeup analysis.

The overall direction in health care is a shift from treating sickness to promoting wellness. Health care delivery and personalized medicine will require extensive use of information technology. There is an enormous amount of information on patients, information that could be used to move us toward personalized medicine. However, almost all this information is cached in paper files in doctors' offices. Digitizing and correlating this information is a huge task, one that absolutely depends on information technology.

The Opportunity
Why is this revolution in the biological sciences so important to us? The answer is that computational intensity, the ability to manage massive amounts of data and solve computationally intense problems, is critical to success. Consider some of these statistics:

  • There are between 32,000 and 40,000 genes in the human genome. Simulating the complex set of events that allows 30,000+ genes to code more than one million proteins is one of the most computationally intensive problems facing researchers.
  • The Human Genome Database is approximately three terabytes (one terabyte equals 1024 gigabytes) of data That is equivalent to a stack of paper 17 times as high as Mount Everest.
  • If we were to store the data captured by medical imaging electronically, we would be talking about 150 petabytes (one petabyte equals 1024 terabytes) of data annually. The cost in storage alone would run $45 billion, and would require 150,000 systems professionals to manage.
  • To simulate the folding of a single protein requires 2x1021 floating point operations. This would take a petaflop supercomputer like Blue Gene (capable of a thousand trillion floating point operations per second) a solid month of calculations to code the smallest of proteins, according to Jeffrey Augen.
  • The volume of life sciences data in the average biotech company is doubling every six months. Huge amounts of computing resources are required to integrate and analyze this data.

    Put in the most basic of terms, the life sciences are going to require huge amounts of computing power. And not just ordinary computing power; we're talking about the power of supercomputers, clusters, and grids.

    The Demand for Supercomputing Will Continue to Grow
    The advances we've made in supercomputing are astounding. I'm sure you remember Deep Blue, the computer that beat chess grandmaster Gary Kasparov in May 1997. Now consider that Deep Blue essentially had a mental capacity comparable to that of a lizard.

    Just three years later, in June 2000, IBM announced that it had built the most powerful ultracomputer in the world. This ultracomputer, called Accelerated Strategic Computing Initiative White, or ASCI White, covers about 12,000 square feet of floor space - an area greater than that of two NBA basketball courts - and weighs 106 tons. The ultracomputer is able to process more operations in one second than a person with a calculator could in 10 million years. ASCI White is smarter than a lizard - almost as smart, in fact, as a mouse.

    In December 1999, IBM announced a new supercomputer, christened Blue Gene, that will approach speeds of 1,000 teraflops (1,000 trillion computer operations - or one petaflop) per second, making Blue Gene a thousand times more powerful than the Deep Blue, and about two million times more powerful than today's top desktop PCs.

    Supercomputers are key to developments in the life sciences as researchers move toward "in silico" experimentation. One immediate use is to simulate protein folding in an effort to improve the target identification phase of the drug development process. Simulating protein folding is extremely computational intensive, thus driving the need for supercomputers on the scale of the Blue Gene project.

    Some people feel this rapid increase in the need for computational power and massive amounts of storage in the biological sciences is comparable to the exponential growth laws we've seen in information technology over the past 30 years. Caroline Kovac, general manager of IBM Life Sciences, said in a Frost & Sullivan interview that if you look at the metrics associated with the increase of biological information, it becomes clear that we are seeing the developments of an exponential scaling law in much the same way as Moore's law represents the exponential increase in transistors per chip.

    As a result, we can expect to see an exponential increase in the amount of data and an exponential increase in the computing power and storage required to generate and manage this data. Put another way, the IT market in life sciences is exploding.

    Companies Are Meeting These Challenges
    Let's look for a moment at how some companies are meeting these challenges. The British Columbia Cancer Agency's Genome Sciences Centre ( implemented an IBM server and storage solution to maximize scalability for life sciences research. MDS Proteomics (, also in Canada, uses Linux-based servers to build supercomputing solutions, enabling advanced analytical capability to determine the function of hundreds of genes and thousands of proteins each month.

    Executives at Aventis (, formed by the merger of Hoechst AG of Germany and Rhone-Poulenc S.A. of France, wanted to create a truly global system to allow scientific resources and results to be shared, regardless of the locations of the individual scientists. Critical to the success of a collaborative environment was an infrastructure that would allow secure access to and optimize querying of heterogeneous data. Working closely with an international Aventis scientific and IT team, IBM Life Sciences Solutions developed a technical and support architecture - including servers, global support capability, and IBM DiscoveryLink middleware - to provide Aventis with the global capabilities to streamline the drug discovery process.

    The University of Pennsylvania, in Philadelphia, received grants over several years to develop a revolutionary Electronic Medical Record (EMR) data grid and repository. The challenge was to develop a visionary patient-centric medical record system that could capture the full range of health care files, including high-fidelity patient medical images (CT, MRI, mammograms), records, and clinical history. This meant building a networked system for electronic data capture of patient records; managing and storing huge files for fast retrieval, comparison, and diagnostic review; and ensuring the security and privacy standards required for patient records.

    The solution, which includes IBM eServers, DB2 Universal Database, and a GPFS file system, provides secure, scalable, diagnostic electronic patient files in under 90 seconds. Built with open standards, the University of Pennsylvania Grid is a massive distributed computer that delivers computing resources as a utility-like service over a secure Internet connection. Enabling up to thousands of hospitals to store mammograms in digital form, it will also give authorized medical personnel near-instantaneous access to patient records and reduce the need for expensive X-ray films. The system is capable of serving thousands of hospitals. In the future, the University of Pennsylvania will work to extend the grid to additional medical institutions.

    IBM's Commitment
    This is obviously a huge IT opportunity and IBM is committed to this market. We have over $200 million invested in strategic relationships and development. We continue to form strategic alliances with industry leaders, and collaborate with customers. We have dedicated life sciences teams in sales, development, marketing, consulting, and research, many of whom hold advanced degrees in the life sciences disciplines. We continue to expand our investment in research, especially in the Blue Gene supercomputing project, and in the IBM Computational Biology Center.

    IBM Life Sciences is developing solutions to address the IT aspects of drug discovery, drug development, clinical trials, regulatory compliance, and information-based medicine, a system of medical care that supplements traditional opinion-based diagnoses with new insights gleaned through computerized data acquisition, management, and analysis. Using digitized medical images to improve collaboration and analysis between physicians would be an example of information-based medicine.

    Our strategy is to leverage our core competencies, and to collaborate to deliver the complete solution. We provide the hardware and infrastructure, the IBM Life Sciences Framework provides the structure for the integration platform. We count on our business partners to provide additional components of the integration platform, as well as the applications and the tools.

    The application of technology to the biological sciences will continue to drive scientific discovery. As supercomputers continue to help us analyze the genetic code, high capacity storage will facilitate the storage life sciences data, enabling collaboration between disciplines such as biology and chemistry, and between research teams around the world.

    The application of informatics to the drug discovery process will reduce the time to market, and we hope, improve the return on the pharmaceutical investment. We are beginning to make advances both in scientific discovery and in improving the development of new drugs and treatments.

    The last revolution - that in health care - lies more in the future. The dream is to simulate "in silico" the role of proteins in causing disease, determining the chemical compounds that will alter that process. Further, by understanding the genetic makeup of the patient, chemicals can be selected that will help rather than harm that particular individual.

    This is what makes our work so exciting and rewarding. We are developing the tools and technologies that will enhance the quality of life. Lofty goals, to be sure, but goals definitely worth striving for.


  • IBM Life Science Solutions:
  • National Human Genome Research Institute:
  • IBM Institute of Business Value paper on Pharmaceutical Mergers and Acquisitions at .
  • IBM's Blue Gene Project:
  • ASCI White:
  • Frost & Sullivan Interview with Dr. Caroline Kovac:
  • More Stories By Barbara Burian

    Barbara Burian directs the internal marketing communications and knowledge management programs within IBM Life Sciences Solutions. She has over 20 years of teaching credentials within the corporate and academic communities,has served on the faculties of New York University and Fairfield University, and been an instructor with IBM's Advanced Business Institute.

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