Early stage asset identification – ‘backing a winner?’
Dr Paul Stuart-Kregor explores how using ‘Scenario Learning’ can improve your chances of turning an exciting new molecule into a commercially successful medicine.
Pharma’s global R&D teams are under immense pressure to discover and develop the next big thing. And after years of rationalisation, the need for successful clinical development has never been greater – but how do you increase your chances of ‘backing a winner’?
Making the right decisions during the early stages of development is the key to potential future success. What are the potential clinical targets for the molecule? How do these align with future market opportunities? What are the company’s capabilities in the therapy area? After all, unmet needs today will likely not be the same as unmet needs in the future.
It’s one thing to identify the questions which need to be asked, it’s another to know how to go about answering them correctly. Companies can maximise their chances of ‘backing a winner’ by adopting a flexible, strategic process using scientific evidence – but also the art of Scenario Learning.
Our starting point is the need to recognise that the science of drug discovery and development is challenging. A recent blog on Scientific American summed it up nicely: “It’s the science, stupid”…… “purely on a scientific level, taking a drug all the way from initial discovery to market is considered harder than putting a man on the moon.” That’s of course assuming you don’t pick the wrong opportunity at the outset or that the correctly identified, currently unmet needs of your chosen therapy area doesn’t turn out to be fully satisfied long before your new molecule is even launched.
A correct understanding of the science give us the best opportunity to assess those areas that are currently being investigated. We can then begin to develop different future scenarios based on how the scientific knowledge in that area may develop. Needless to say, only one of these scenarios will play out, but understanding the different options will help us determine not just possible options, but those which are more probable as well as those which have most potential.
Having said that, it must be remembered that even if the right opportunity is identified and we get the science of today and tomorrow right, we know that value can still be lost. A potential winner can be turned into an also-ran by poor decision making throughout the development and commercialisation process. Failing to collect the right clinical data, not considering all the true value drivers beyond the efficacy and safety profile of the molecule, ignoring the non-clinical stakeholders needs etc., can all impact on the chances of success.
This takes us into the area of Scenario Learning. Building on the right science and clinical understanding underpinning the therapy area, the next step is to look at current and future therapeutic options. ‘Current’ is relatively easy, although establishing when patents expire can sometimes be difficult to determine accurately. We know how well current molecules are used and how they perform relative to their competitive set. The clinical development pipelines of the competition are also visible. While the future performance of a particular New Chemical Entity (NCE) can be hard to predict, in my experience R&D teams can provide an insight on the likely performance of competitor molecules, even those in early stages of development, based on their modes of action.
All that remains is to consider other market drivers that may potentially change how healthcare is delivered over the development time horizon. Sounds simple doesn’t it? After all it is very easy to devise strategies based on such sequential thinking, extrapolating from where we are today, adding the likely changes in a stepwise fashion, and arriving at one option of how things could develop.
But the problem is that this does not take account of the disruptive changes that we see in real life – how do we deal with these? What is required is the willingness to think beyond the obvious. Companies need to try to identify the most important and unpredictable factors, those plausible, yet surprising drivers of change that will shape the future, no matter where they come from. The wider the net, the more variables you can include, but areas to concentrate on include differing clinical, scientific, economic, population management and health system perspectives. It is then a matter of looking at these in different permutations and combinations and evaluating the potential impact on the product development.
Only when you have done this is it possible to arrive at a number of potentially viable scenarios. This provides more than just a means of assessing existing potential opportunities, because each scenario is brought to life with a market map of feasible opportunities that we believe will exist within them. From this it is then possible to identify potential opportunities that could exist in future worlds from which product profiles can subsequently be developed, products which may not have initially been considered.
Of course no one can predict the future in its entirety, but adopting a flexible strategic process underpinned by scientific evidence combined with the art of Scenario Learning can help. It can minimise uncertainty, aid decision making, facilitate course correction and enhance the final product proposition. Having this in a timely and structured fashion will ensure that the necessary information is where you need it, when you need it, helping you adapt along the unpredictable road to clinical development success and maximising your chances of backing a winner.
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Closing thought: How effective is your current use of scenario planning?