Are Pharmaceutical Probability of Success Benchmarks Useful?
03-28-11
Comments: 1
While teaching the Portfolio Management Course at Stanford (here), Jay Anderson of Eli Lilly offered a provokative tidbit during his guest lecture. Jay had conducted a 13-year study of the assessed probability of success for all Lilly’s drugs in development and compared then to the actual frequency of success.
His assessment committee is very well calibrated, for example, when they say “50% chance of success” the actual success occurs about half the time. Jay compared this result to industry benchmarks. He found that they had almost no predictive power. In other words, there is no relationship between what the benchmark says and the actual frequency of Lilly’s successes. Or as Jay politely puts it “The null hypothesis that the benchmarks have no predictive power cannot be rejected.”
Yet most companies use benchmarks as the basis of their probabilities! Jay points out that this practice misses the considerable private information that firms have about their compounds.
So what is the right role of Benchmarks in assessing probability of success? Food for thought.
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About industry benchmarks vs. Lilly experience.
If you toss the coin, then probability of tail is 50%. Everybody knows that. However, this result could be achieved after thousands experiments. If you do the same experiment, say 10 times, and do not repeat it, then probability of tail could be between 0 to 100%. (In my own experiment- 10 times tossed the coin – probability of tail was 70%). The experiment shows how dangerous is to make conclusions based on limited experience. Also, there are millions of other factors affecting probability of success. In my opinion, this is exactly what happened when Lilly compared its own probabilities with industry benchmarks.
Industry benchmarks do have more power then Lilly’s, because they are based on significantly larger number of “experiments” dissected across therapeutic areas and phases of development.
Sincerely,
Vladimir