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December 10, 2013 comments

Monte Carlo models of drug R&D focus attention on cutting costs – Part 1

There is a theme behind many of DrugBaron’s musings over the last three years: pharma R&D is just too expensive to make economic sense.  Given high failure rates throughout the process, including in particular a significant rate of late stage failures when the capital at risk is very high, either attrition must fall or costs must come down.


Almost everyone in the industry recognizes this equation.  But for most, particularly those who are guardians of large (and expensive) R&D infrastructure, it has been more palatable to talk of improving success rates than decreasing costs.


What cost cutting there has been has been quantitatively and qualitatively wrong.  Pruning a few percentage points off R&D budgets that have tripled in just a little over a decade has no discernible impact on the overall economics of drug discovery and development.  And cutting costs by reducing the number of projects, rather than reducing the cost per project, is not only ineffective but counter-productive as DrugBaron has already noted, on more than one occasion.


But there is a fundamental tension in the equation: success rates are assumed to be heavily tied to expenditure.  If you spend less per project, attrition rates will go up (assuming at least a proportion of the money is being wisely spent) and you will not improve the overall economics.  You might even make it worse.


So what makes DrugBaron so confident that dramatically cutting the cost per project makes sense? That even if decision quality declines slightly, it will be offset by a greater gain in productivity?


The “evidence” comes from sophisticated computer simulations of early stage drug development that underpin the ‘asset-centric’ investment model at Index Ventures.  Models that have remained unpublished – until now.


Drug development is a stochastic process.  That much is indisputable, given the level of failure.  Processes that we understand and control fail rarely, if ever.  But such is the complexity of biology that even the parts we think we understand relatively well still conceal secrets that can de-rail a drug development program at the last hurdle.


The fundamental premise of drug discovery and development is therefore one of sequential de-risking.  Each activity costs money and removes risk, so that the final step (usually substantial pivotal clinical trials that test whether a drug safely treats a particular disease) is positive as often as possible.


Exactly how often this last step IS positive is open to some debate.   A figure often cited for the phase 3 success rate is 50%.  But this headline figure masks considerably heterogeneity.  For example, once a drug has been shown …

December 9, 2013 comments

Monte Carlo models of drug R&D focus attention on cutting costs – Part 2 (the caveat!)

“So DrugBaron tells me that drug discovery and …


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