IBM thinks that the life sciences industry, where it has had little presence to date, is now big enough and ripe enough to be worth pursuing. It aims to get in at the start of the value chain via bioinformatics. The computing giant has bigger plans than smaller players that moved earlier to focus on bioinformatics-and it has the means to see them through. Pioneers got stuck doing fee-for-service work, but IBM can sell Big Pharmas hardware, software and most importantly, all sorts of services. IBM's debut product in life sciences is DiscoveryLink, which lets data from disparate sources be queried as though they were all in one, giant database. It's also meant to broadly support software created by specialized applications developers. Installations will have to be custom jobs-ideally, part of bigger IT contracts. Other computing concerns also perceive opportunity in life sciences; indeed it's clear a battle is brewing between big hardware suppliers. But they're cooperating to a degree: calling for data standards, so they can compete on products not technology. IBM has credibility from other sectors, but it's uncertain how applicable it expertise will be in life sciences, even if it can find and train enough people. Also unclear: whether drugmakers actually want and will pay big money for integrated solutions. Though a newcomer to life sciences, IBM may be uniquely suited to serve the industry-not only because of its own deep and ongoing research into computational biology, but because it can offer drugmakers one-stop shopping.

In the course of validating disease targets or developing drugs, researchers need tissue samples from patients with specific types of diseases as well as from healthy patients.BioSample Inc., has an internet-enabled biological material procurement solution to the pharmaceutical/biotech community.

Advice of Counsel addresses the question of whether genomics companies are using new business models and deal structures to commercialize their technologies.

New technologies enable the rapid processing of genetic information, but since gene data isn't associated with specific diseases and diseased tissues, in and of itself it isn't clinically useful. A new breed of start-ups aims to provide both the phenotypic and genotypic sides of the equation by creating databases of patients and patient samples. Still unclear is how much drug firms will pay for disease-associated gene data; genetics firms are taking various approaches to monetizing their databases, from focusing initially on high-value diagnostics to creating true target-discovery businesses, to selling their data along with associated software and services. There are also ethical issues to hammer out. The new companies must take care to protect patients' rights. They must consider the need for explicit consent to use the information collected from patients, especially when they are participating in research whose purpose is as yet undefined.