Drug companies also have identified the need to gain better control of their development and manufacturing process. The FDA guidance not only encourages the application of statistical tools such as DOE, according to Julia O’Neill, director of engineering at Merck & Co.’s West Point, Pa., facility, it is forcing companies to use them. “There is a new expectation that manufacturers will be able to demonstrate they are using statistical methods for monitoring results and monitoring processes to ensure they remain in a validated state,” O’Neill says. “That drives an expectation back upstream that statistical methods will also be used during the design and qualification stages.”
O’Neill, a chemical engineer who came to Merck from the chemical maker Rohm and Haas eight years ago, acknowledges that, prior to the recent push from FDA, the chemical industry had made more headway than the pharmaceutical industry on DOE. In doing so it also paved the way for the drug industry. “There is a whole set of tools just waiting to be taken off the shelf and used to achieve similar goals in pharma,” O’Neill says.
But the cultural divide between chemical engineers and chemists may be harder to cross. “I have heard people say that statistics are for people who don’t know the science,” she says. “I totally disagree.”
Some chief executive officers say they are anxious to close the divide. “Concepts like statistical design of experiment have gained a lot of ground in recent years, but for mainstream chemists they are somewhat anti-intuitive,” says Siegfried CEO Rudolf Hanko. “They are 180 degrees against what you learn in grad school, where you learn to look for a cause-consequence relationship and the fundamental rule is you only change one parameter at a time.”
In an industrial setting, where the focus is on efficiency, changing one parameter at a time takes too long, Hanko says. “With DOE, you create a hyperdimensional space from which you determine the highest optimum of whatever parameter you are looking at. The fact that this is against the nature or at least the education of most technical people has led to a situation where the uptake was very slow in the industry.”I have a bit of a suspicion that there is some level of strawmanning going on here. I think most chemists recognize that DOE is a very powerful tool, especially for situations in which all the interactions between different variables are not fully understood. I think that most chemists also intuitively understand that one-variable-at-a-time is not the most efficient way of running experiments. I would like to hear specific examples of resistance to DOE before I believe that there's a real cultural divide.
(Also, I would like to hear from DOE supporters about areas where they believe that this tool would not be helpful. I think that would be important, too.)