Trust in early pharmaceutical pipeline product valuation has all but evaporated. And yet views of value are increasingly important to the improvement in effectiveness of R&D that is so sorely needed in the pharmaceuticals sector. Where does this paradox come from and what can be done about it?
By Andrew Chadwick and Tom Parke
Why isn’t value trusted?
Pharmaceutical R&D teams are distinctly uncomfortable about attributing value to an R&D project before proof of efficacy. Teams don’t see a drug as a tangible option until they have results that benchmark the new therapy against either current treatments, or, for treatment of unmet needs, at least reveal the critical information on patient tolerability. The trouble is that by the time the project reaches this stage, most of the dice have already been thrown.
One reason for this systematic lack of trust in value estimates is that retrospective comparison of forecasts and outcomes for peak sales show clearly that drug markets bring surprises, both pleasant (e.g. sales of Lipitor Ref. 1 ) and unpleasant (e.g. sales of Exubera Ref. 2)
Decision-making about project progression and conduct in early Development, or Discovery, is, or should be, affected by concerns about wasted cost when there is failure in late development – and so lack of trust in forecast market value is compounded by the fact that late failure is still unpredictable. This isn’t just a question of taking a bet in an area where there is a known risk of failure, since there is often also considerable uncertainty about the failure rate across a complete therapeutic or disease area.
Why is a view of value important?
Assuming that the aim of a pharmaceutical company is to maximise the value that it creates, then estimates of value enter inescapably into an optimised decision-making process. The key decisions are not just at the portfolio level about which projects to start or stop, but also at the level of optimising, within the conduct of projects and programmes, the right balance between cost, risk, value and time.
Even an averaged value is useful
The industry can improve performance, despite the random nature of much of its raw material, by systematically placing better bets and evolving ‘smarter’ R&D designs that make the best of the available information and build in basic business value thinking into planning of experiments and trials.
Even an average figure for value of a project, at a given stage of R&D, set against potential costs, can often help in reaching the best planning decision.
For example, in designing screening cascades, value estimates strongly enter the calculation of best cutoff, since the opportunity cost of false rejection is the eNPV (expected Net Present Value) for the option wrongly rejected, allowing for other independent risks further downstream in the process. The value impact of lost opportunities can be alarmingly high, when taken together with the modest predictive power of many Discovery methods and the natural human instinct to believe in and act on the most recent information (Ref. 3) .
Another need for eNPV estimates in decision-making on project conduct is where there is an option to invest in a way that can save time in development, e.g. adaptive clinical trial designs. For these assessments, the value of time saving is, in the simplest terms, the discounted worth of bringing value earlier. Then, if required, a more sophisticated view of competition might be added, that relates product value to order of market entry.
Differentiated strategies demand differentiated planning
Where companies are trying to find the right way to run each project for value, and moving away from fixed, monolithic processes, then again any estimates of difference in value between projects or programmes can inform objective, value-maximising decisions on where to take risk and accelerate, or to mitigate risks through a more staged chain of commitments. Factors leading to value differences between projects can include the use of personalised medicine, decisions to target rare diseases, and work that excludes or includes different regional markets and/or phenotypes.
The virtual research team has new commercial hand-offs
The third reason why valuations are inescapable comes from the trend to increased ‘virtualisation’ of R&D. Even for outsourcing decisions, cost becomes more explicit and has to be justified against the value that it adds. But where ‘virtual’ means buying in more research options, then good valuation can make the difference between long-run business success and failure.
The in-licensing transaction itself may have myriad associated options that need to be valued: for example, what extra de-risking information is it worth paying the provider to generate before you know the identity of the molecule; what de-risking work should you undertake before unconditional acceptance; what is the right structure of payments according to the value of resolving critical uncertainties?
So what’s to be done?
We have found that it helps them to show, preferably in a highly visual, interactive way, how sensitive the optimal decisions are to an estimate of value: where people see that information on value (or any other critical decision variable) makes a big difference to their long-run success, then they will start to care about getting a better handle on this information.
Value estimates are controversial. They are sorely needed, in the context of helping R&D teams make value-adding choices about the way forward, in a world where on average pharma R&D is failing to create net value. Better thinking and decisions above value can help effective innovation that yields the most consistent crops from the creators’ intellectual seedcorn.
- “The original peak sales predictions for Lipitor were on the order of $700 – 800 million, as it was the fifth statin to reach the marketplace … Lipitor that would … generate annual sales of [over] $12 billion” from http://johnlamattina.wordpress.com/tag/lipitor/
- “Exubera had long been touted as the next blockbuster hit for Pfizer, but the company withdrew the product last October, after only a year on the market. Pfizer had expected to reach nearly $2bn/year in Exubera sales, but product sales hit just $12m before getting pulled. Pfizer took a $2.8bn hit to its revenues” (from http://bit.ly/1b0aXaV).
- Overcoming psychological barriers to good discovery decisions, Andrew T. Chadwick and Matthew D. SegallChadwick and Segall, Drug Discovery Today, Volume 15, Numbers 13/14, July 2010.