376 CATALYZING INQUIRY
of one person at a 2003 seminar, “This is work for [biological] scientists, not bioinformaticists.” For this
reason, further large-scale business investment in bioinformatics—and indeed for any research with a
long time horizon—is difficult to justify on the basis of relatively short-term returns and thus is unlikely
to occur.
These comments should not be taken to imply that bioinformatics and information technology have
not been useful to the pharmaceutical industry. Indeed, bioinformatics has been integrated into the
entire drug development process from gene discovery to physical drug discovery, even to computer-
based support for clinical trials. Also, there is a continuing belief that bioinformatics (e.g., simulations of
biological systems in silico and predictive technologies) will be important to drug discovery in the long
term.
10.3.4.2 Reduced Workforces
The cultural differences between life scientists and computer scientists described in Section 10.3.2
have ramifications in industry as well. For example, a sense that bioinformatics is in essence technical
work or programming in a biological environment leads easily to the conclusion that the use of formally
trained computer scientists is just an expensive way of gaining a year or two on the bioinformatics
learning curve. After all, if all of the scientists in the company use computers and software as a matter
of course and can write SQL (Structured Query Language) queries themselves, why should the com-
pany have on its payroll a dedicated bioinformaticist to serve as an interface between scientists and
software? In a time of expansion and easy money, perhaps such expenditures are reasonable, but when
cash must be conserved, such a person on staff seems like an expensive luxury.
10.3.4.3 Proprietary Systems
In all environments, there is often a tension between systems built in a proprietary manner and
those built in an open manner, and the bioinformatics domain is no exception. Proprietary systems are
often not compatible or interoperable with each other, and yet vendors often think that they can maxi-
mize revenues through the use of such systems. This tendency is particularly vexing in bioinformatics
where integration and interoperability have so much value for the research enterprise. Standards and
open application programming interfaces are one approach to addressing the interoperability problem.
But as is often the case, many vendors support standards only to the extent that they are already
incorporated into existing product lines.
10.3.4.4 Cultural Differences Between Industry and Academia
As a general rule, private industry has done better than academia in fostering and supporting
interdisciplinary work. The essential reason is that disciplinary barriers tend to be lower and teamwork
is emphasized when all are focused on the common goals of making profits and developing new and
useful products. By contrast, the coin of the realm in academic science is individual recognition for a
principal investigator as measured by his or her publication record.
This difference appears to have consequences in a variety of areas. For example, expertise related to
laboratory technique is important to many areas of life sciences research. In an industrial setting, this
expertise is highly valued, because individuals with such expertise are essential to the implementation
of processes that lead to marketable products. These individuals receive considerable reward and
recognition in an industrial setting. Although such expertise is also necessary for success in academic
research, lab technicians rarely—if ever—receive rewards that are comparable to the rewards accrued
by the principal investigator.
Related to this is the matter of staffing a laboratory. In today’s job environment, it is common for a
newly minted Ph.D. to take several postdoctoral positions. If in those positions an individual does not