Technology, Information, and Decision Making

The decline in pharma productivity—an astounding 33% per year for the past 30 years1—has generated a great deal of hand-wringing but little in the way of suggestions about how to improve the situation. Why, for example, has the substantial investment in technology (primarily in web-based electronic data capture) not helped productivity? 

This problem is hardly unique to pharma. It is well enough recognized in other industries to have a name, the IT Productivity Paradox. The lessons from other industries boil down to three factors: mismeasurement, mismanagement, and lack of usability. 2 Walking the floor at DIA this week, I could not help but be struck with the thought we are painfully re-learning the same lessons so painfully learned in other contexts, with at least the same measure of pain as reflected by productivity measures. I saw lots of systems that presented massive amounts of data as well as other that tracked the minutest of details. My presentation on strategic relationships, suggesting that perhaps sponsors should measure the worth of suppliers by assessing sponsors’ ability to enable earlier decisions, was met with a ripple of perfunctory applause but no questions.

This, in a nutshell, is the myopia that I believe bedevils our industry: lack of focus on what’s important. We are finely attuned to details but miss the big picture.

I believe the answer to pharma’s productivity quandary is pretty simple: earlier, better decision making. How do we do that? Let’s start with informatics, as opposed to technology:

  • What information do you need to do your job better?
  • How can this information be streamed?
  • How can it be made actionable?

This capability is what directly affects productivity and ultimately success in pharma: the ability to generate clean, immediate, and actionable information. This includes information on how studies are conducted (for example, adaptive enrollment and monitoring) as well as overall success (adaptive designs, including Bayesian approaches). The common element is that every day incorporates the cumulative knowledge garnered and enables us to improve what we do tomorrow, ultimately leading to (1) generating information faster and (2) using that information to kill weak candidates earlier and (3) progress promising candidates faster.

Isn’t that what productivity is all about?

 

 

References

1.    Scannell JW, Blanckley A, Boldon H, Warrington B. Diagnosing the Decline in Pharmaceutical R&D Efficiency. Nat Rev Drug Disc 2012; 11:191-200.

2.    Jones SS, Heaton PS, Rudin RS, et al. Unraveling the IT Productivity Paradox — Lessons for Health Care. New Engl J Med 2012: 366:2243-5.

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