The effectiveness of drug industry is very depressive – no doubts about it! A nice illustration in oncology is here. The analysis is based on the following report. The summary picture:
Several very clever ideas and remarks:
We used a different database than the PhRMA report (Thomson Pipeline vs ADIS Insights) but count roughly the same number of active programs in oncology (990 vs ~981)*. Of those, the concentration of clinical development effort around a handful of targets is staggering: 8 targets are addressed by >20% of the projects, each of which has more than 24 projects in clinical development. Clinical projects that target VEGF lead the charge at an amazing 70 – and this only includes the one’s addressing oncology.
Sure – I do agree! Let's go further:
Does the industry really need 25+ clinical or commercial stage programs against each of these targets to exploit the full anti-cancer potential of those mechanisms? Even more puzzling than the clinical development congestion on these targets, what about the huge numbers of preclinical projects addressing these targets (in red above)? Some may be unique angles (e.g., receptor mutant-selective inhibitors that spare wildtype), but most are probably not.
A quick back of the envelope suggest there’s a ton of wasted industry resource across these programs. Assume every clinical program has cumulatively spent $20M, and the preclinical ones at $5M (both conservative estimates), this implies well north of $5B+ in R&D dollars has been tossed at this set of programs over the past few years.
Absolutely, the resources are not distributed in a proper way if we are talking about efficiency of the R&D.
How many winners are likely to emerge from this? Maybe a small handful per target, at most. That implies lots of zombie programs being funded by budgets and investors that will never be of value. This is of course always the case in R&D: programs more often than not fail. But the concentration of industry activity on these privileged targets feels way outside the norm, and in aggregate represents a lot of wasted energy. Beyond money and time, it also is a waste for patients. Clinical trial recruitment is hard enough for exciting programs, but doing work on all these unlikely-to-matter programs on crowded targets seems borderline unethical frankly.
I think that ethical implications are not relevant here – business course basically has nothing to do with ethical burden and pharmaceutical business is not an exception.
The real reason for this concentration isn’t about the arguments above – it’s fundamentally a reflection of our industry’s collective risk avoidance, as well as a misperception of aggregate risk.
Portfolio decision-making in large and small companies leads to an overwhelming bias towards precedented mechanisms as a means to reduce biologic risk. No head of discovery ever got fired for producing too many Development Candidates, and the lowest risk way of doing that is through “fast follower” (and even slow “fast follower”) incremental improvements. In the shot on goal mentality of R&D, more of these shots are better. Most R&D portfolio prioritizations punish novel target programs as low “confidence in mechanism”, and therefore riskier than precedented targets. The math from these models is hard to challenge, having made some of those models in a prior life.
Well, in order to change the situation we need to change the paradigm. This is Darwinian process – the smartest will survive - I think that a lot of resources will be burned in vain... 
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