Why Incrementalism Won’t Fix Clinical Development

A recent study by the UK’s Office of Health Economics shows no let-up in pharma’s efficiency crisis. OHE’s study sets the cost of R&D for a new medicine at $1.9 B. Discussions I’ve had this week with senior staff at several large pharma companies were a reminder of why efficiency remains a major issue for the industry: the desire to oversimplify the answer.

These companies’ attempts to increase efficiency span the range of options, from strategic outsourcing to keeping clinical development in house. What the diverse responses share is incrementalism: each company seems to believe that adding discrete capabilities is the key to future prosperity.

Our immediate topic was adaptive monitoring. Like other sponsors I mentioned in a recent post, most of these sponsors are interested in adaptive monitoring, including the ability to track overall and component risk elements and to track key risk indicators remotely. Then and now, the sponsors said what amounts to, “This is a great system. Can you bolt it onto what we are doing now?”

The answer is no, because each of the commercial systems used by these companies lacks the ability to collect and track the kind of performance data required for detailed continuous risk assessments and effective management responses.

On a more general level, a bolted-on quick fix is impossible for two reasons:

First, transformation doesn’t come from incremental change. As W. Edwards Deming stated:

Long-term commitment to new learning and new philosophy is required of any management that seeks transformation. The timid and the fainthearted, and the people that expect quick results, are doomed to disappointment. (Thanks, Paul).

Second, the true benefit of technology is not simply to keep doing what we do now but do it faster, but to enable new processes.

If our adaptive monitoring system could simply supplement what was currently done, would that help? Sure, and the savings from achieving high data quality while performing SDV on a substantially reduced percentage of data (as shown in the figure) are substantial.

Copyright 2012, Health Decisions. Used by permission

While reduced SDV provides great savings, even greater benefits flow from the ability of this system to manage sites better and faster than legions of individuals running around in the field. Centralized management based on immediate data enables a huge leap in how studies are done (another area I’ve blogged about). Our systems and data-driven centralized management approach have decreased labor in some studies by ~35% while increasing both timeliness and quality.

The real challenge that pharma companies face is whether they can change in a fundamental way. Historically, the answer has been a resounding (and echoing) NO. I was reminded of this while listening to an NPR discussion yesterday of how department stores responded to shifts in demographics and other key business drivers over past decades. Only one of the stores discussed survives today, Dayton Hudson. This beleaguered retailer responded to market changes by setting up a small subsidiary specifically to free it from incrementalism.

You may have heard of Dayton-Hudson’s offspring: Target.

Pharma has some recent spinoffs of its own, such as Abbott’s AbbVie for brand-name pharma products and Pfizer’s Zeotis for animal-health. However, none of the pharma spinoffs seems intended to liberate clinical development from traditional methods that evolve incrementally. There’s no sign that any of the pharma spinoffs has the desire or potential to become the Target of our industry.

Breaking with traditional inefficient development methods doesn’t necessarily require a spinoff. As Deming says, transformation requires commitment to new learning and new philosophy.

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