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By Morris R. Levitt

Morris R. Levitt, Ph.D. June 12, 2002 | All of us working in the bio-IT industry — scientists, IT and informatics managers, and executives — have been aware for some time that we seem to be suspended between an acute sense of crisis and a field of boundless opportunity.

The opportunity is easy to delineate conceptually. It is the promised land of tailored genetic and drug therapies focusing on specific groups of targets associated with (genetically) identifiable segments of the population—as revealed by pharmacogenomics.

The crisis, like the fabled Hydra, seems to have many heads — from problems in data integration and analytics, to gross inefficiencies in clinical trials. Ultimately, the crisis is reflected in the deteriorating economics of drug development and deployment. It just costs too much in R&D and testing compared with the ultimate revenue generated and the risk of failure of a new pharmaceutical. In 2001, for example, the pharmaceutical industry spent $30 billion on research, up 300 percent from 10 years ago. But the industry launched only 24 drugs, half the number of just five years ago.

What if the deeper cause of the crisis is the basic economic paradigm associated with the biopharmaceutical industry? The key assumption of that model is the development of a continuing series of high-risk "blockbuster" drugs produced by Big Pharma, each targeted at generating a billion dollars or more in revenue. If, however, as has widely been suggested, this is the wrong paradigm (i.e., one that's running into its historical risk-management limits), then efforts at optimizing the individual steps within the associated value chain are bound to run into fundamental problems. In fact, pursuit of optimization within the old paradigm is an exercise in diminishing returns and cannot lead to improvements in either ROI or profit.

It is, therefore, worth considering an alternative, or at least a competitive, paradigm. The core element of this model would be the proliferation of "mini-blockbusters," or even niche pharmaceuticals, providing therapeutics to specific, but smaller, patient populations (i.e., less than millions). This might occur at an introductory rate, say, five to 10 times greater than at present, with each drug generating tens to hundreds of millions of dollars in revenue. A great deal of work, requiring detailed quantitative market analysis, is required to evaluate whether this option, involving much greater patient and treatment diversity, is economically viable, let alone superior, to the current dogma. If it is, then many shifts must occur within the biopharmaceutical value chain, including:

Strategic repositioning of some of the largest biopharmaceutical companies to focus the core of their efforts on highly efficient development, manufacturing, and distribution of a much larger number of promising drugs. (A rough analogy with the motion picture or computer industry's evolution comes to mind.)

Shifting drug discovery — in pharmaceutical, biotech, and academic research settings — to the search for new classes of drugs, using the most advanced and integrated scientific, bioinformatics, and IT techniques (as exemplified by Millennium Pharmaceuticals). This can also provide a more rigorous, expansive, and fruitful environment for venture capital and other forms of financial investment in bio-IT companies.

A radical realignment of FDA policies and procedures to significantly reduce the time for clinical trials (see "FDA Fosters Pharmacogenomics"). Emphasis would be on rapid screening for major toxicity problems and establishing evidence of clinical efficacy for precisely defined populations as early in the product development cycle as possible. This will also require that information and communications technologies be fully deployed to optimize clinical, financial, and market data gathering and transmission.

Expanding the size and number of industry and academic centers for the training of tens of thousands of life science, IT, and informatics professionals in the most advanced bio-IT research and development techniques and strategies (see "Informatics Moves to the Head of the Class").

Ultimately, adoption of this new bio-IT paradigm has the potential to not only improve the productivity and economics of drug discovery and utilization, but also to help catalyze new thinking and needed reforms in the broader context of the healthcare system as a whole.

Morris R. Levitt, Ph.D.

President and CEO

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