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Outside Perspectives Beget Better Outcomes

Posted on January 26th, 2016 by in Pharma R&D

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My favorite quote about why drug discovery, despite very productive decades of productivity and innovation, has seemed to have reached the drought is from Ashutosh Jogalekar in Scientific American blog:

“We are dealing with a biological system that still escapes our rational understanding and because we are trying to engineer a molecule that perturbs this incompletely understood system, and that too while being forced to satisfy multiple constraints. It’s like being asked to find a black cat in the dark, with the added constraint that one of your feet is bound to the top of your head, and you only get three tries.”

So: drug discovery is hard. And the industry responds by pouring more money into R&D, selling off therapeutic areas, buying other ones, merging, acquiring, in-licensing, out-licensing, partnering with academic institutions and foundations. The newspapers can barely keep up with all of the sweeping strategic changes.

But I’m always surprised that more simple things are rarely done. Things, for example, like data sharing and integration from outside companies or institutions.

It’s not flashy, and it definitely won’t make the news. But some people think it might make for better research.

Simon Bailey, Senior Director, Oncology Chemistry at Pfizer, is one of them. Referring to some research he and his team were working on a few years ago, “The situation we found ourselves in was actually making sure that we weren’t unconsciously biasing ourselves to include the data that kind of supported our conclusions and dismiss the data that didn’t,” he says of his paper, “Physiochemical drug properties associated with in vivo toxicological outcomes,” which relied significantly on an examination of outside sources. “The bulk of that paper was based on our internal data. But what we tried to do was validate and provide a kind of check and balance that what we were finding at least matched with what was out there in the literature.”

Considering how many assets progress into the clinic only to fail very expensively, it seems to make sense to validate as much as you can as early as possible. Resources to progress an asset are also finite – especially so for mid-size and smaller companies.

“Generally what you can learn from the literature is way cheaper than what you can learn through your own experience,” he says, insisting that what is really costly is lab time. “If you save lab time by doing literature – licenses and seats are dirt cheap compared to what they’re going to pay in the lab. So if I was advising any small company, I would say buy every search tool that your scientist needs because they’re going to pay for themselves over and over.”

For large companies, too, why not get the most mileage out of tools already in the hands of researchers? Searching specifically for data sets that can be integrated not only saves time doing actual bench research, but also can save dollars down the line by making sure the science is as sound as possible.

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