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Automating Eureka

The most obvious way to improve the chances of a compound’s surviving the drug development process, though, is to start off with the right molecule in the first place. Traditionally, this has meant a mix of good old-fashioned intuition, a vast knowledge of different compounds, and lots of chemical ingenuity.

Take Pfizer’s billion-dollar arthritis drug Celebrex. In the early 1990s, John Talley was a medicinal chemist at G. D. Searle, the drug unit of Monsanto, when university researchers discovered the gene that makes an enzyme thought to be involved in causing inflammation. (Pharmacia merged with Monsanto in 2000; in turn, Pfizer bought Pharmacia early last year.) The enzyme was called cox-2, and the finding ignited an industrywide race to produce an arthritis drug that would inhibit it. It’s at this point in reciting the story that Talley grows animated; it is when the chemistry really begins.

At a scientific conference, a Searle colleague of Talley’s heard about a compound DuPont researchers had synthesized that seemed to have anti-inflammatory properties. For various reasons, it clearly was not the right compound to make into an anti-arthritis drug, but Talley realized that it could be a starting point, providing critical clues to the chemistry of a drug that might serve as a cox-2 inhibitor. Talley and his coworkers began to chemically tear apart the DuPont molecule to figure out what gave it its biological activity. Armed with that insight, the Searle chemists then began to systematically design a new molecule that would both be effective in blocking cox-2 and have the properties required of any drug, such as lack of toxicity. After more than a year and a half of testing, redesigning, and tweaking more than 2,500 compounds, Talley and his coworkers finally produced a suitable molecule. “The eureka moment comes when you’ve made the compound,” says Talley, who is now vice president of drug discovery at Microbia, a Cambridge, MA-based biotech startup. If you can’t make the right compound, he says, the biological knowledge is “just a cool idea.”

Talley’s belief in chemistry as the linchpin of drug discovery is widely shared by Pfizer’s researchers and R&D executives. Genomics and other biological tools may provide new disease targets, but the hard-and expensive-job is still to come up with the right compound. “Genomics is not the savior of the industry. The renaissance is in chemistry,” says Rod MacKenzie, Pfizer’s vice president of discovery research in Ann Arbor, MI.

Pfizer considers its huge library of compounds, housed in a large windowless room at its Groton research labs, the Sistine Chapel of that renaissance. Like any library, this one tells of a collective history-of numerous failures, a few spectacular successes, and most commonly, long-forgotten efforts that never made much of an impression either way. In this library, however, the tales are told in small glass vials, each neatly labeled with a bar code that describes the properties of the compound within and how it was made. Pfizer’s chemists around the world can request a chemical, and a robotic librarian scoots down the aisle, retrieving the vial and neatly depositing it on a tray, where it waits to be shipped off.

Pfizer is spending $500 million over the next five years to upgrade and enlarge this collection of millions of druglike chemicals. Not only will the library give Pfizer’s chemists ideas and lessons on what works and what doesn’t, but it will provide the seed corn for a highly automated, ultrafast new system for discovering drugs. In essence, the system will perform many of the same tasks-chemically designing, testing, and refining a molecule-that Talley and his coworkers handled in inventing Celebrex. But instead of relying on instinct and intuition, the drug discovery machines will rely on automation and brute computing power to quickly perform and interpret a vast number of experiments.

While automation has become routine in pharmaceutical labs, MacKenzie says high-throughput instruments have been limited in the types of chemical reactions they can carry out. That, he says, has changed recently, and automated machines can now produce many more of the types of compounds that interest drug developers. Throw in improvements in the rapid screening of compounds for biological activity and toxicity, as well as improved computational design tools, and an automated system could soon take over much of the drug discovery process, says MacKenzie.

Here’s how it might work. A molecule is plucked out of the company’s library. The automated system screens it against multiple disease targets and tests it for such things as toxicity. The results are fed back into a computational design and synthesis process, which tweaks the structure of the molecule. The cycle repeats, continually optimizing the compounds based on the results of the screening and testing. Pieces of such a system are already in place, says MacKenzie, and this year Pfizer researchers will begin to link them together into a “closed loop” technology. “It’s the old traditional process for doing drug discovery, but it’s enabled in a parallel world to move incredibly fast,” says MacKenzie. “It is now ready to change the paradigm of drug discovery.”

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Tagged: Biomedicine

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