Drug Baron

January 23, 2014
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Even odds-on favourites can lose: lessons from the Prosensa story

With the details from the DEMAND-III study, the full extent of the failure of Prosensa’s exon-skipping drug drisapersen to arrest progression of Duchenne Muscular Dystrophy (DMD) has become clear.

There are few grounds for optimism among the plethora of secondary end-points, no trends, not even a statistically significant post hoc sub-group analysis.  Only pages and pages of convincingly negative data.

While its obviously a relief that concerns about liver toxicities proved unfounded – the treatment was very safe – the safety profile is unlikely to be much consolation for such a convincing lack of efficacy.

But clear-cut as the data is, it leaves one very important question entirely unanswered: was the failure due to insufficient dystrophin production, or – more worryingly – because successfully elevating dystrophin is much less effective than has been assumed?

There are also lessons to be learned beyond DMD: the infinite subtlety of biology means that no phase 3 study is a “slam dunk” – failure lurks round every corner, even in the most unexpected of places.  Public market investors, in particular, can pump up asset valuations on an over-optimistic assessment of early clinical data (as the recent Intercept episode illustrates).  The chastening experience at Prosensa should serve as a warning that translating promise and potential into regulatory approval and sales is often more difficult than it first appears.

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January 3, 2014
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Never mind how many, feel the sales potential – the Class of 2013 FDA Approvals

With thirty-nine approvals from the FDA, 2012 triggered a wave of optimism in the pharmaceutical industry.  But if 2012 was characterized by an increased number of approvals, the sales potential of many of those new products was underwhelming.  For 2013, the number of approvals may have gone down, but the quality (in terms of clinical impact and sales potential) has increased dramatically.

Twenty-seven approvals (twenty four of them drugs) in 2013 may be twelve less than the 2012 haul, but it is still above average across the last two decades.  And in any case, the number of approvals is a poor surrogate for the productivity of the industry.

With between five and seven products headed for blockbuster status, and Sovaldi™ potentially reaching peak sales in excess of $10billion annually, the output from the global pharmaceutical industry in 2013 shows signs of return to the glory days of the late 1990s.  Indeed, arguably, 2013 may be the best year ever in terms of future sales potential for newly-approved products.  Predicted global sales of these medicines five years after launch dwarf the equivalent figure for the class of 2012 by as much as 10-fold.  With this kind of R&D productivity, things look rosier for the global pharmaceutical industry than they have done for more than a decade.

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December 10, 2013
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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.

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