Drug Companies on Speed

Drug Companies on Speed

Bioinformatics may also be the only way drug companies can deal with the gigabytes of data they produce and receive every day. The pharmaceutical trade organisation Pharma-ceutical Research and Manufacturers of America predicts that by 2003, scientists will have discovered more than 10,000 potential targets for drug development, resulting in what some call "target glut" And that number will only get larger thanks to the 30,000 genes and an exponentially greater number of proteins being identified and analysed in the Human Genome Project. At the same time, combinatorial chemistry allows companies to synthesise more than 100 compounds per chemist per year. "Informatics is how you deal with the amount of data being generated,"says Rick Roberts, global head of discovery research informatics for Pfizer.

In the past five years, most big drug companies have created official informatics departments, either by integrating their research and IT departments or by creating close ties between the two. But the unofficial origins go back further. "It started as an outgrowth of the scientific discipline as opposed to IT,"says Nathan Siemers, group leader of bioinformatics at New York City-based Bristol-Myers Squibb. "Basically it's been a research endeavour, but over its evolution it's become more infrastructure-related. More people need access to this information, and the scale of information we have to disseminate to our clients - the researchers - is growing drastically. So our ties to IT, which originally were almost non-existent, have become stronger and stronger."

Today, there are informatics technologies popping up to help at nearly every stage of the drug development process. Early on in the process, bioinformatics technology allows researchers to analyse the terabytes of data being produced by the Human Genome Project. Gene sequence databases, gene expression databases (which track how genes react to various stimuli), protein sequence databases and related analysis tools all help scientists determine whether and how a particular molecule is directly involved in a disease process. That, in turn, helps them find new and better drug targets.

Using IT analysis tools and genomic databases, for example, Merck researchers were able to compare the entire genome sequence for mice and humans. They not only discovered that the two genomes were 90 per cent identical, but they also found a gene in mice that might have the same function as a gene that may be involved in schizophrenia in humans, says Richard Blevins, who has been Merck's director of bioinformatics for three years. Currently Merck is working with genetically altered, or "knock-out", mice, in which certain genes are altered to create a specific mutation (schizophrenia, in this case) to see how the animals react to drug candidates. This research, still in the very early stages, could eventually lead to a target for a new schizophrenia drug, Blevins says.

Similarly, Bristol-Myers Squibb has discovered a novel method for treating epilepsy using gene-sequencing mining tools. The particular drug candidate isolated for this research has since shown strong efficacy in knock-out mice and is nearing clinical trials, according to Siemers of Bristol-Myers Squibb.

Drug companies also employ a variety of cheminformatics software - tools that can predict the activity of a particular compound by studying its molecular structure. For instance, scientists can use molecular modelling software (tools that rely on interactive 3-D visualisation or mathematical algorithms) to discover and design safe and effective compounds. Chemical databases allow researchers to store and retrieve compounds and related data. Robotics makes it possible for chemists to synthesise hundreds of thousands of chemical compound variations from a library of simpler molecules in a short amount of time. High-throughput screening technology (see "The Definitions of Life", page 121 ) allows researchers to screen thousands of compounds at once, rather than just 10 or 20.

Technology may help at the clinical testing stage too, though it has been a bit slower to catch on. Virtual patient simulation software, like the Asthma PhysioLab program that showcased virtual patients Alan and Bill, can simulate patients, targets and therapies in order to predict experimental outcomes before companies commit major resources to lab research and clinical trials. Essentially, this software helps predict the effect particular compounds have on the human body.

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