Biomedical Engineering Reference
In-Depth Information
Intellectual Property
When it comes to collaboration, there are two major camps: academia and business. At the individual
researcher level, the motivations for collaboration are typically the same in each camp—the thrill and
challenge of pushing the envelope of scientific discovery while achieving personal career
advancement. At higher levels in business and academia, the dimension of economics is usually
added to the mix. Lab administrators are necessarily concerned with continuing funding from
corporate, government, or other sources. With the prospect of substantial economic gain looming on
the horizon, many organizations have taken steps to secure their intellectual property rights through
the U.S. Patent and Trademark Office before revealing or sharing their research findings with other
researchers.
This practice of obtaining temporary exclusivity to use a gene or gene sequence is much more
prevalent in commercial laboratories than in academia. As in other industries, patents provide the
holder with some degree of protection for their economic investment in developing a particular
molecule. For example, a pharmaceutical firm would be foolish to invest millions of dollars toward the
development of a molecule that it hadn't patented or licensed from the patent owner.
The publication of significant research findings is often delayed by years because of the slow review
process used within the U.S. Patent and Trademark Office. Although some of this delay is attributable
to the normal workings of the patent office, much of the delay is due to the huge number of genetic
patent applications submitted to the office in the past few years. Companies are quick to patent
every new sequence in the event that it might prove to be invaluable one day. As a lottery of sorts,
the odds are very good that several patents will pay off handsomely in the near future, with big
Pharma paying for licensing rights.
Although much has been made of the patent practices of companies such as Celera Genomics,
academia has its own problems. For example, there are several suits pending over who should be
credited with the original sequencing technology. Apparently, the sequencing method developed by a
researcher was patented surreptitiously by the lab director. As a result, millions of dollars of income
and the academic credit for the R&D were allegedly misdirected. The converse condition exists as
well, in that there is a practice of intellectual property theft by researchers working in commercial
and academic laboratories. This problem is apparently especially prevalent with foreign researchers
who come to work in U.S. laboratories.
Economics
In every commercial or academic endeavor, progress is a function of operating costs and the
availability of funding. For example, overhead, payroll, hardware, software, and infrastructure costs
represent the main expenditures for a typical bioinformatics laboratory. Web servers, workstations,
and network cables, routers, firewalls, and related hardware are fortunately commodity items that
tend to follow a trend of decreasing price-to-performance ratio.
One of the largest variables in the economics of establishing and maintaining a bioinformatics
laboratory capable of collaborating with the larger bioinformatics community is obtaining software for
servers, workstations, and high-performance clusters. Throughout most of this topic, the focus has
been on open-source and freely available academic software. The intent is to introduce readers who
are interested in gaining practical experience in bioinformatics computing to software that can be
downloaded from the Web and run within a few minutes. However, from an economic perspective,
"free" software isn't necessarily superior to commercial software.
Consider the criteria for evaluating the suitability of a commercial product for a hypothetical
bioinformatics project. As illustrated in
Figure 10-6
, the typical criteria for evaluating a software or
hardware solution range from price (the initial cost) to synergies with previously installed hardware
and software. Assuming a typical software product, such as a database for storing sequence data, a
primary concern is the technology fit, which is a measure of the compatibility of the product with
