Pharma’s Cutting Edge

Pharma’s Cutting Edge

Pharmaceutical and biotech science and business

 
 
 
 

Entry order as a consideration for innovation strategies : Nature Reviews Drug Discovery

I’m pleased to report that NRDD has published as an advanced online publication the above article that will appear in print in the April edition of the journal. A PDF is also available at the PGS website: http://www.pharmagrowth.com/library.html

As you’ll see, the article is a combination of a brief overview of what is known about market entry order and eventual commercial success, particularly as it relates to pharmaceuticals, and an exploration of additional factors that describe and hopefully illuminate this relationship. As you’ll see, first to market is not always best, at least as far as share of revenues is concerned. Yet that hasn’t stopped most firms from furiously pursuing a pioneer strategy for nearly all of their products. Exactly when firms should pursue the less costly and less risky watch-and-wait (and learn!) strategy remains to be fully fleshed out, but what is clear to me at least is that the decision will rarely be obvious.

The issue described in this article is part of the much broader issue of best practices for strategic thinking for complex, risky, protracted scientifically based innovation. Ill-informed intuition probably still has a role in modern pharmaceutical innovation strategy, but I strongly advocate the idea that science must be applied to the management of scientific innovation if firms are to improve research productivity meaningfully. Measurements (metrics) alone are not enough. Indeed, metrics can be misleading if used to advance a preconceived outcome, as is usual practice. Measurements must be preceded by hypotheses and followed by tests of the hypotheses to be successfully applied. Unsuccessful hypotheses must be rejected. Models incorporating metrics and relationship assumptions derived from successful hypotheses should be created and then used to drive decision-making rather than decision-justification. Lacking adequate quantitative models, strategists might resort to intuition, but at least it should be well-informed.

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