Mar 15, 2005 |
As head of the Computational Biology Center at IBM's Thomas J. Watson Research Center, Ajay Royyuru is focused on Big Blue's bio-IT initiatives, including exciting applications of the Blue Gene supercomputer (see Oct. 2004 Bio·IT World, page 44). "There is a tremendous sense of excitement as we see more evidence that the industrialized approach to commercializing the biotech field is taking hold," Royyuru says.
As I have said before, bio-IT tools must be more broadly embraced across the greater life sciences "ecosystem" before we see meaningful revenue traction in this industry. This wave of industrialization will drive that adoption.
Royyuru, a molecular biologist by training, points to a number of recent developments that give cause for optimism: Greater dependence on open-source solutions is driving a greater sense of interdependence in the life sciences ecosystem, and the scale of computing has improved so dramatically that problems previously thought to be unsolvable are now within reach. "Early adopters will need to embrace complexity," Royyuru says. Biological systems are inherently complex, poorly understood, and do not readily lend themselves to analysis or so much of the pharma industry thinks. With proven discovery successes, customer adoption will improve.
This complexity is a central frustration for many bio-IT entrepreneurs, and ultimately explains why so many companies have struggled in recent years. Calculating the ROI for bio-IT investments is problematic when companies are unable to single out successful compounds derived by these tools. Having said that, much industry-academic collaboration is under way that should provide important proof of principle for these tools. For instance, IBM is working with MIT on the BioHaystack initiative in a collaborative research effort to drive interoperability. Three TrendsRoyyuru points to three emerging trends over the next 12 months that bio-IT entrepreneurs will find important:
· The broader acceptance of grid computing supported by open-source initiatives
· The improvement of dedicated high-end computing functionality (as represented by Blue Gene)
· The complexity of metabolic pathways that can be represented and analyzed "holistically"
The underlying theme is the acknowledgement that multi-scale simulations that span many levels of complexity can be detailed and their interdependencies better understood.
In addition to the industry collaborations that are so prevalent today, IBM is focusing increasingly on graduate schools training tomorrow's technical leaders to use these bio-IT tools. This new generation of scientists promises that the bio-IT industry will flourish. The debate is only about when not whether that happens.
So where are near-term opportunities? Royyuru says meaningful advancement of the bio-IT cause is predicated on platform technologies that will generate more relevant, complete data "that will allow for the interrogation of biological systems." These represent exciting entrepreneurial opportunities, he says. "We are all data-hungry."
From a software perspective, the most powerful opportunities revolve around the area of data integration. "We need to be able to integrate across all the layers of complexity in order to understand metabolic pathways," Royyuru says. The biologist is now the customer and an important champion of these tools. The distribution of computing power to the benchtop has driven much of the interoperability and open-standards debate. Point analytics solutions are just not that compelling in this environment.
So what is not to like about this scene? Royyuru worries most about the "revolution of rising expectations." Has the bio-IT industry over-promised, and does it risk under-delivering? Ultimately, customers will want to see a return on these investments, and that won't happen in two to three years.
Michael A. Greeley is managing general partner of IDG Ventures, a global family of funds operating in North America, Europe, and Asia, with approximately $600 million under management. E-mail: email@example.com.