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{bio,medical} informatics

Friday, September 20, 2002

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find related articles. powered by google. Genomeweb Gathered at Gambling Mecca, Genomics Types Ask Why Pharmas Have Quit Betting on Them

"In a so-called Masterminds Panel here this morning, four life sciences-industry execs pondered the question, "When and how will '-omic' technologies have a positive impact on pharma's output?" They were generally optimistic, and agreed that genomics and proteomics have had a significant effect on the drug-discovery trade--albeit a different one from what investors desired.

Genomic technologies have generated "lots of target ideas, but the bottleneck [exists] in understanding which target is for which disease," said Mark Crockett, executive director of functional genomics for Bristol Myers Squibb. The effect so far from genomic technologies has been to create more work for pharmas, Crockett said. "New targets have no literature associated with them. There are an average of seven publications on any given protein, which means that pharmas have to do a lot more basic biology.""

redux [12.14.01]
find related articles. powered by google. GenomeWeb Big Pharma, On the Ropes, Says it Knows What it Wants from Genomics. But Will That Spur a Turnaround?

"And although the drug industry remains the most profitable worldwide--it generated profits as a percentage of revenues four times the median rate for all Fortune 500 firms during the end of the last decade, according to a Kaiser Family Foundation report released that day--an editorial in this month's Nature Biotechnology by David Horrobin, CEO of Laxdale Research, in Stirling, Scotland, had this to say: "With rare exceptions, most of the top 20 multinational pharmaceutical companies are not generating in-house the new products needed to sustain the rates of growth they have enjoyed in the past.

redux [05.26.00]
find related articles. powered by google. Biospace Biotech Productivity: Myth or Method?

""The data suggest that the biotechnology industry used to be more productive than Big Pharma, but not any longer," said Rebecca Henderson, a professor at MIT's Sloan School of Management whose been studying the question for six years. "The public biotechs have declining productivity... and look as if they are running into the same problems as Big Pharma."

On every metric that Henderson has studied---number of scientific papers and patents per R&D dollar, cost per new drug--she found that biotech and Pharma productivity were quickly converging, and both were getting worse. After spending six years of studying the question, Henderson says she has found "no systematic evidence that small firms are more productive.""

redux [11.29.01]
find related articles. powered by google. The Scientist A Flood in Genomics
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"Glenn Giovanetti at Ernst & Young Life Sciences Industry Services, comments "You could really compare [today's situation] to a large degree with the first biotech boom in the late eighties and early nineties where the thought was, 'Hey, this is going to lead to better drugs faster,' and clearly that hasn't been the case." Having the genome in hand has brought about more drug targets, but, explains Ma, "People are getting more concerned that novel targets are going to have a higher rate of failures because there is less information on them." And when working in 10-year drug-development cycles, failures are costly.

Ma points to a trend of growth in clinical informatics that would effectively garner more information from expensive clinical trials instead of simply treating them as regulatory hurdles. "People are beginning to think through to how ... to take greater advantage of that information," he adds. But increasingly, the suppliers of genomic information have been looking to do the same thing.

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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