Assuming that technological innovations continue at their present rate, many of the biomaterial technologies envisioned by corporate and acade mic researchers, from self-replicating nanomaterials to smart materials will become available within the next decade. However, before the labora tories developing the technologies can become economically viable, sur geons and other end users of the technology will rst have to become familiar with and accept the new biomaterials. Furthermore, third-party payers will have to agree to cover the cost of these initially expensive ma terials, and the long-term viability of the technology will have to be as sessed. For example, rst-generation bioengineered skin may eventually

prove to be more susceptible to skin cancer, infection, or even premature wrinkling after 20 or 30 years.

Computing is an enabling technology at the core of the biotech revolution. Virtually all of the advances in molecular biology over the last two decades have been due in part to the introduction and rapid evolution of the per sonal computer, high-speed international and local networks, and innova tive software. The acceleration in the quantity of holdings in the online biological databases re ects the rapid growth of the Internet, constantly in creasing processor power, and a drop in the cost of computing power. Whether the task is diagnose and treat genetic diseases or to develop new pharmaceuticals, there is simply too much biological data to search through, manage and manipulate manually. What s more, not only is there more data than can reasonably be analyzed without computer-based tools, but also in some areas the data are still multiplying exponentially. Consider the growth of the freely accessible online gene database, GenBank, maintained by the federally funded U.S. National Center for Biotechnology Information (NCBI), as illustrated in Figure 1.6. GenBank was started in 1982 with a holding of only about 600 DNA sequences, all sequenced through manual methods. Thanks to automated gene-sequencing machines and highly publicized race between Celera Genomics and the government-funded Human Genome Project to map the human genome, GenBank has grown exponentially since about 1998, when it contained data on about three million entries. Similarly, Swiss-Prot, a protein data base that is funded and maintained by the Swiss Institute of Bioinformatics (SIB) and the European Bioinformatics Institute (EBI), has roughly doubled in size every ve years since 1986, when there were only a few hundred en tries in the database. Swiss-Prot is cross-referenced with over 60 different online molecular biology databases, including the Protein Data Bank (PDB), which is funded through collaboration between Rutgers, The State University of New Jersey, the San Diego Supercomputer Center at the Uni versity of California, San Diego, the University of Wisconsin, and the Na tional Institute of Standards and Technology. Additional online database programs in other countries include the EMBL (European Molecular Biol ogy Laboratory) Data Library and the DNA Data Bank of Japan. These and many other database systems are funded by government, either di rectly or through grants to academic institutions. Computers and networks such as the Internet have facilitated commu nication between collaborators, and imbedded computer processors form the basis of virtually every piece of modern laboratory equipment used in

15,0

GenBank Sequences (K)

10,0

5,00

0 1985 1990 1995 50 75 100

s (K)

databases from 1980 through 2003 is indicative of the research and development in biotech over the same period.

the biotech industry. Hardware and software are also being developed to handle the rising tide of data that has transformed molecular biology from an exclusively wet lab endeavor to an environment in which many re searchers conduct their research with an Internet-connected workstation.

The advances in computing and in biotech have much in common with each other and with improvements in digital communications. Historically, it helps to appreciate that only a few years after Mendel developed the laws of genetic inheritance in the 1860s, Alexander Bell was busy developing the telephone. By the time penicillin was introduced in 1928, not only had the transatlantic wireless and electronic ampli ers been developed, but the rst predecessors of modern electronic computers were in use. By 1950, main