Much DNA really is junk, say drug developers
Only a minimal number of useful drug targets have emerged since human genome information exploded with new data into the pharmaceutical field, speakers agreed at the BioSilico 2002 conference in New York this week.
From the drug development perspective, they agreed, much of the genome appears to be “garbage.”
In his presentation, the former head of the National Cancer Institute, Richard Klausner, told participants that he fears Congress’ interest in funding biomedical research may start to wane, because there has been “very little clear, realistic discussion of the amount of work left to do” balancing the “enormous amount of excitement or hype” surrounding the human genome project.
“I received several calls the day after the White House announcement [about the completion of the genome project] from members of Congress wanting to know what new treatments this had resulted in,” said Klausner, who is currently the counter-terrorism advisor at National Academies of Science. “I think there was a real disappointment that the genome project wasn’t it,” said Klausner, and that new drugs were not going to spring forth quickly.
“The human genome project has given us enormous volumes of data which need to be picked through over the next several years,” said Brian Moldover of Aventis Pharmaceuticals, who chaired a session at the meeting, which was hosted by Scientific American. Part of the problem, he told BioMedNet News later, is that the human genome database contains a lot of “dirty data” that needs to be cleaned.
“If we take all the expressed sequence tag (EST) data that has been generated through the years and map it against the human genome, anywhere from 20 to 30% doesn’t map,” he said. Many give the excuse that the genome is not fully mapped, and so the discrepancy may lie where gaps exist, he said. “But the reality is that a lot is not in the gaps. A lot of it is garbage.”
Another problem, Physiome’s Jeremy Levin told BioMedNet News, lies in the linear, vertical structure by which most pharmaceutical firms have been organized. “Most were organized around teams, each of which is then allocated a specific task,” he said. “This works beautifully and powerfully if you have completely validated target,” he said, because then all the resources and expertise of the organization can push the project down the drug discovery pipeline. But what happens when that company is now faced with the 30,000 genes described in the human genome?
“The bottom end of that pipeline is jammed,” Levin said, because everything above it is arranged to handle tasks in a linear fashion. If this linear mindset does not change, he said, the number of novel targets discovered will not be significant.
“Companies need to adopt high-throughput modality in their ability to analyze, identify, and validate potential targets,” he added.
Kenneth Carter from Avalon Pharmaceuticals also thinks that linear approaches should be dropped. The use of multiparameter analytical tools allows a firm to “circumvent the bottleneck [at the bottom end] by looking first at how a drug or potential drug affects multiple pathways in a cell, and then work backward to see which receptors or targets are involved.”
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