All opinions are my own and do not necessarily reflect those of Novo Nordisk

Another in a series about parallels between baseball and drug development

A recent post by Phil Birnbaum, who runs a baseball research site, did a nice job of highlighting how he feels stastisical analysis may best serve baseball organizations:  by ensuring that they don’t make losing moves.  While everyone is trying to win, in an industry where so much is uncertain, in many cases, it may be most effective to  “First, concentrate on eliminating bad decisions, not on making good decisions better.  And, second, figure out what  everyone else knows, but we don’t.”

This is a terrific observation, and one he backs up through the body of his post with examples from baseball and gambling strategy.  I think it applies quite well to drug development too.  I’ve made the earlier conjecture that drug development can be thought of as existing on the adaptive landscape, with improvements to drugs or drug classes getting harder and harder as you climb up that mountain of efficacy.  But when you’re on a slope, it’s really easy to go sideways or backwards.  So, the analogy here is that drug development, like baseball, needs to throw a lot of resources (not just statistical and analytical ones, either) into preventing a bad decision.

This thinking is also influenced by the ecology of pharma and biotech.  Let me be very clear about my initial assumption:  drug development is filled with really smart people, almost all of whom are dedicated, sharp, innovative, and really interested in winning.  So is baseball, (well, except maybe for the Kansas City Royals).  But it’s hard to put together a good drug development pipeline.  Resources help.  Resources often help.  But they aren’t enough.  And since the talent is there, the explanation for lackluster drug development progress may partly be found in companies still making poor decisions on assets.

Let me zero in on the second part of the quote in the first paragraph:  “And, second, figure out what everyone else knows, but we don’t.”  Here’s something else that companies could possibly do differently:  share data.  A really fascinating blurb in ScienceInsider just highlighted an effort by people at Johns Hopkins to try and get clinical trial information published, as long as it’s been publicly released in other formats such as through litigation or Freedom of Information Act requests.  While all the companies would prefer this not happen, if it happens uniformly, that can only be good for drug development as researchers learn more about why given trials were halted or failed.  If R&D costs as much as it does, part of the reason lies in duplicated effort.

To conclude, let me throw out another thought on decision making:  send in the crowds.  Crowdsourcing as a method for making decisions has been tried in a number of contexts and often has been found to lead to better overall decision making than more traditional methods.  If we want to make decisions on, for example, which drugs should move forward, setting up a system to poll everyone in the organization in a controlled, anonymous way might be enlightening.  I know this would not be a popular development for people in the C-suite, since, after all, that is their domain.  And I believe the assertion Malcolm Gladwell makes in Outliers that initial, small differences in environment can eventually lead to great differences in ability down the road as individuals get training and experiences not widely available.  Therefore those who are in the C-suite are different in their knowledge and outlook and know more about strategic decisions.  But they still don’t know everything, they still are human, they still have biases.  And a technician working in a lab in Boston may have noticed something in his cell cultures that  no one else is aware of.  If we want to make good decisions, shouldn’t we make sure that everyone possible has a voice?