GUEST COMMENTARY · Lessons for guiding the revolution in bioscience
BY PRASHANT TYAGI
Feb. 11, 2005 | The 20th century witnessed one of the biggest technology revolutions in history. Just as the industrial revolution led to exponential growth in manufacturing and related industries, the IT revolution led to an exponential growth in digitization of information. Will a similar revolution emerge in life sciences in the 21st century?
IT progress in the 20th century began with developments in solid-state physics, producing transistors, semi-conductors, and the hardware sector. Software growth derived from demand for higher levels of abstraction in instructions that drove this hardware.
The exponential growth of these sectors can be attributed to eight factors, four of which also apply to the life sciences:
Advantages of novel technology. The IT industry carried no hangovers that usually accompany an established industry.
Advances were revolutionary rather than evolutionary. Any industry in the revolutionary stage attracts the best minds. Biotechnology boasts this same advantage.
Opportunity factor. Entrepreneurs identified potential business opportunities for these new technologies, as evidenced by the likes of Microsoft, Oracle, and Google. Companies such as Genentech and Amgen have done the same in the life sciences.
Fear factor. More than opportunity, what drives businesses is the fear or threat that disruptive technologies bring. A good example is the lavish sums spent on fixing the hypothetical Y2K bug. Life sciences are also driven by fears, such as an aging population and drugs losing patent protection.
Wide-scale application. Information processing and exchange is essential in every industry — hence, the scope and application of IT spans all industries. Developments in biotechnology and other life science disciplines affect many other industries, such as agro, chemical, and so on.
By contrast, several factors unique to IT are lacking in the life science domain:
Inherent productivity gains (Moore's Law). The rapid increase in hardware performance, coupled with cost reduction, drove the development of high-performance applications. Even though the growth of raw biological data has outstripped Moore's Law, the enabling technologies (ultra-high-throughput screening, combinatorial chemistry, etc.) have failed to deliver such enormous productivity gains.
Switching costs for customers. Companies such as Google or eBay don't require a huge commitment or fees for customers to switch services. Ease of use and low learning curves are a large reason for the fast, high level of penetration. Final product offerings from the life science industry are very different and lack this advantage.
Opportunity for modular development. PCs, which helped drive development of all IT processes and products, could be assembled from component parts, like a manufacturing assembly line. Modular production leads to competing vendors, economies of scale, and encourages outsourcing, fueling increased productivity. This benefited development of both hardware and software.
From revolutionary to evolutionary. Modularity also provides opportunity for reuse, which leads to higher efficiency, such as the code-reuse paradigm in software.
Hindering a 21st-century revolution is the inherent vertical integration in the life sciences. Drugs cannot be split up into components or modules, and new products are not easily created based on past successes, resulting in high costs.
Here, then, lies the challenge in the life science industry. As the product offering itself cannot be easily modularized, life science companies should make their processes modular, thereby improving productivity and efficiency. Modularity can be applied to each primary area of the pharma pipeline — discovery, development, trials, manufacturing, and marketing — either individually or to the entire process. Such modularization has begun, to some extent. The evolution of the biotech industry was an example of modularizing of the value chain, with biotech offering the innovation required in the early discovery phase for the pharma industry, and pharma providing the muscle required for downstream activities such as marketing.
But lack of industry standards, concerns for patent protection (which prevent sharing of information), and the inherent risks in R&D are just a few of the hazards that need to be overcome. Significant advances are being made to overcome these, but we still need creative ways of sharing information and knowledge in the life science domain to reach the extent to which it has been done successfully in IT — as evidenced by open source.
Prashant Tyagi leads product development at Sertanty Inc., a solutions provider for the drug discovery industry, and has worked at Affymax and Oracle. E-mail: firstname.lastname@example.org.