They may be the most inspiring words one can hear at a conference. One certainly doesn’t hear them very often. But at last week’s Clinical Trial Congress (CTC), we heard a version of one of our favorite sentences: “And we didn’t have to do a single trial.” Ahhh. We have heard so many people doubt the role of technology in clinical trials that it is a bit of a relief to hear this stuff can be genuinely game-changing.

Pfizer’s Mike Collins, VP of development operations, was not, strictly speaking, talking technology at all. He’s deeply focused on process and spoke to the CTC about a massive, years-long effort to simplify some of the tasks at the company.

His official biography for the CTC conference notes his statistical training, and a move from the United Kingdom to Manhattan: “Work related interests include the detection of fraud in clinical trials, managing change, performance metrics and the development and implementation of efficient and standardized business processes within the clinical trial area.”

The Winnowing

He concurred with Lilly’s Alan Breier: “We are in the data information business,” Collins said of the pharmaceutical trade. Just getting his arms around what Pfizer does was clearly a challenge.

Collins described a vast effort to study every Pfizer task and process in the clinical arena. There were initially 5,000 processes. The number was first reduced to 1,200-1,500 or so. And by the time the Pfizer group really knuckled down, it decided it could cut the list down to 100 processes or so. “This was staggering,” Collins said. Just for good measure, the team linked all the standard operating procedures (SOPs) to the newly slim list of process-tasks.

1 Template, Not 50

Before the exercise, Pfizer calculated that it might take 15 days to get a case report form approved. If someone was on vacation, or didn’t watch their email, the whole process could grind to a halt. Now it takes just a few days. Pfizer once had 50 clinical study templates. Now it has … one. “By having smaller, more focused teams, we really believe we’ve reduced waste,” Collins says.

Just when drug supplies are considered, he said, rough estimates show better supply estimation might save $40-100 million annually. “We have cases in which teams ordered five times as much supply as they needed,” he noted. “We can save considerable amounts of money just by not wasting drug supply.”

Legacy Data

Collins mused that the sheer breadth of Pfizer’s research means that it would be nice to peer back into time and look at older clinical trial data. That, alas, is not always easy at Pfizer (or other places in the industry.)

Except for the exception, a blockbuster for men. As it turned out, that product did have its own data repository. The people at Pfizer got to looking around inside that repository, only to discover interesting data. Perfectly usable data that had not been sent to regulators. That was shortly rectified, and the label duly updated.

The Winnowing

Sensitive readers still sipping their morning coffee may wish to click to another story. Just a thought.

What the Pfizer scientists discovered in their repository was data showing that, ahem, softness, a previously unknown medical malady, was in fact treated by Pfizer’s product. Hardness, by the same token, entered the scientific lexicon as a new medical indication.

Pfizer’s data repository, Collins said, was key: “It enabled us to reposition the brand last year around hardness without doing any additional clinical trials,” he said. Readers who are scratching their heads can read up on the details here, not that there are many details.

Data Mining

Periodically, this correspondent has listened to industry veterans wondering if all the data gathered on case report forms (CRFs) is truly necessary. This anecdote would suggest that the more data, the better. Stories like this one are sure to inspire the use of data elements relating to all manner of personal physiological metrics that, well, will be recorded across a variety of trials. One never knows where the data will lead.

The heterogeneity of clinical data and the multiplicity of trial designs, we’re guessing, means other Pfizer blockbusters cannot be reinvigorated so easily. “That is the only product we can do this with at the moment,” Collins said. Which begs another question.

What is so difficult about data repositories? With this sort of return on investment for one therapeutic area, and unlimited financial resources, why wouldn’t Pfizer already have built 15 or 16 additional repositories? It’s not a Pfizer thing, clearly. This is industry wide.

ClinPage would love some reader to explain the distinguishing feature that sets apart a data warehouse and a data repository. It’s always seemed like arguing about pail vs. bucket. Along this long road, we have met people who feel strongly about “bucket.” We have also encountered those who get excited about “pail.” Warehouse? Repository? Let know.