Collaboration Would Allow Industry to Mine Data, and Apply Lessons, From Macher and Nickerson’s Research

This Wednesday, I interviewed Georgetown and Washington University professors Macher and Nickerson, whose research into FDA and drug manufacturing efficiencies was recently reported ( and mentioned in a previous post).  Their research stems from a study of the semiconductor industry that they did while graduate students in California. (It will be interesting to contrast findings from the two studies; We'll feature the interview and summarize benchmarking lessons in our next issue of Pharmaceutical Manufacturing). This first phase of their research suggests that increasing manufacturing complexity has a negative impact on drug yields and cycle times.  Given that increasing complexity is an inescapable reality for the industry, especially as it moves to "personalized medicine" and combination devices, the need for better management of drug manufacturing operations is urgent.  As Professor Macher noted, the most complex semiconductor process involves between 400 and 500 process steps; some AIDS medications today already require 100 to 150 manufacturing steps. Their research suggests that drug companies could save well over $50 billion* a year by improving manufacturing---allowing them to invest more in discovery and R&D, and reduce the cost of drugs to the consumer. It also suggests that FDA is definitely moving in the right direction with many of its new initiatives: notably risk-based enforcement and the Inspectorate Training program. To watch/listen to an audio/powerpoint presentation summarizing findings, click here. Georgetown and Washington university paid for the research, and neither professor received any additional reimbursement for this work, ensuring that the data are truly trustworthy and relevant. But the numbers beg to be mined, and interpreted.  Only when they're analyzed can individual manufacturers and the industry determine causes and best practices----and destroy whatever is impeding manufacturing efficiency. Nickerson and Macher are planning to do that, as they can, over the next six months. But they do have "day jobs" as academics. Both professors were extremely complimentary about other researchers working in this whole area of "drug manufacturing science."   But it occurred to me: Several academic groups are currently examining drug manufacturing issues---Purdue, via NIPTE, CAMP and CPPR, MIT and Rutgers, to name a few---and so many industry groups should care a great deal about this  information (PhRMA first among them). Wouldn't it make sense to collaborate with Macher and Nickerson and help advance the next stage of this research---the data analysis? Responding to this survey required a large investment of time on the part of the companies that took part and required a huge leap of faith, and their disclosing "secrets" that would ordinarily be well hidden. Why not speed the interpretation required to make sense of the data ? Doing so will serve the industry, but more importantly, it will serve the public at large. As this study indicated, manufacturing is still the industry's stepchild---and an extremely expensive one at that. Like Casper Hauser, it has been hidden away for years.  It's time to bring manufacturing issues into the light of day.  Studies like this one are the only way to do that. So why can't academic groups put aside their competitiveness and individual desires for funding, and work together to interpret this information, under the auspices of a consortium? Drug manufacturing, as "unsexy" as the topic may be (compared with the glamor of discovery), is the industry's final frontier; isn't it time that more groups joined forces to explore it? -AMS *As it turns out, the "$50 billion" potential savings number alluded to in the press release accompanying the report, was probably conservative.  After exhaustive interviews, Macher and Nickerson found that respondents said they could save from 15% to over 50%  of the "cost of goods sold" (COGS) figure by improving manufacturing processes; Nickerson and Macher used the lowest figure of 15% COGS to be conservative.