AT A GLANCE
Management consultants for life sciences companies at PRTM (Pittiglio Rabin Todd and McGrath).
Blanchette recently helped Rosetta Inpharmatics scale its systems from the lab to a 40,000-square foot data factory.
Kulkarni has a PhD in pharmaceutics and worked at American Home Products and Chiron before joining PRTM.
Q Where will bioinformatics be in two years? Five years?
A MB: The way we see this evolving is from sequencing to the proteomics area. Proteomics is where the rubber meets the road in this and is really going to leverage the tools and expertise that have been built up through sequencing.
Q What impact will this growth in proteomics have on bioinformatics?
A MB: Youve already got significant amounts of data, but if you start looking at the proteomics side theres significant growth in the amount of data that needs to be handled, stored, transferred, and viewed.
AK: Theres a huge issue in handling the terabytes of data, but theres an ancillary problem, which is that proteins have these huge amorphous regions and people just dont know how to characterize them right now. So theres a technology barrier thats linked to the data barrier or the data complexity issue that is just being breached using standard techniques.
Q Do you see any promising technology out there that may help this situation?
A AK: There are many technologies in place right now on the instrumentation side. We need to move toward better X-ray crystallography at a better level of discernment and speed. Theres many approaches and a lot of them are software-based. Thats where the solution is going to be. We dont think the dominance will be in the pure physical instrument. It will be in the software model.
MB: Its got to be a combination of techniques that will really allow this to take off.
Q What other challenges do you see for bioinformatics as it moves beyond sequence analysis?
A MB: If you look at the business side there are challenges in terms of integrating the new technologies into the R&D process. Thats going to require massive changes in how, for example, pharma companies conduct their research. Youve got research teams accustomed to using certain sets of tools, theyre educated in using those techniques, and just getting them up to speed on how these tools are used is one challenge. Trying to get over that hurdle to the point where theyre actually integrating them into the development process is another.
Whats really going to be challenging is trying to integrate the tools across the development process so that multiple teams can share the information and use it effectively.
If you look at the Merck acquisition of Rosetta, that could be an interesting case study in taking these folks that have a developed set of tools, a developed expertise, and trying to integrate them into a larger development effort.
Q What non-existing bioinformatics technology is number one on your clients wish list?
A AK: The issue becomes, once you have this knowledge base from genomics, how can you develop a therapeutic? That requires a very complex transformation to cheminformatics. Theres a crying need to bridge this gap quickly so you can start thinking about a cure and not just a description of the problem. Theres a whole missing element of standardization that needs to be breached so people can devote their time and assets appropriately.
Everything from data storage to the software for analysis on the biology side through to making the crystallography models and finally to the chemical side, theres huge standardization barriers in all of these areas. If there were a standardization mechanism, thered be this leapfrogging of efficiency in this market.
Q Do you expect to see more M&A activity in the bioinformatics sector?
A AK: From the fall of 1999 there was lots of money available and the sector got hugely crowded. Now theres plenty of reasons consolidation will take place. The biggest reason of all is that big pharma needs to manage the discovery process and integrate that with the bioinformatics and expected revolution in proteomics. Pharma will have two options: A loose alliance or a tight alliance. I think the Merck-Rosetta model is perfect when good technology exists, big pharma will scoop it up and link it to its discovery platform so they can very quickly transformation pure knowledge into therapeutic entities.