‘I wouldn’t start from here!’ – Efficiently Creating an Enhanced Evidence Portfolio.

Muzeable Thinking No.24 posted by Tim Brooks 4th October 2017


This is a guest piece from Dr Tom Kenny of Dune Consulting. Muzeable has had the pleasure of working with Tom and find the mix of his expert, clinical perspective and our marketing/brand views has the potential to deliver genuinely fresh thinking. Thanks Tom.

Using finite resources and the available data to build a compelling story that creates and defends a value proposition or tries to deliver distinctive claims for a medicine (POM or OTC) is one of the most important – and difficult – tasks for anyone managing a healthcare business.

Yet, we are repeatedly shocked by the poor use of evidence companies make when it comes to constructing a value story for their healthcare brands.

Too frequently the company who are aiming to promote a medicine do not put enough energy into seeing the world from the perspective of a payer (and that includes people shopping for medicines) at the beginning of their clinical trial programme – the focus is single-mindedly on the regulator and the ‘hurdles’ they need to jump.

We understand the pressures that drive this, but as they say, “if wishes were horses, beggars would ride” and at the late stages of your positioning around pricing and reimbursement, or creation of a value proposition, or a setting of marketing or promotional messages it is a little churlish to be wishing that some deeper, or different, thinking had been done earlier. At this point the more appropriate saying often appears to be “beggars can’t be choosers”. It is was it is, we need to work with the evidence portfolio that we already have…

…or do we?

Our experience is that, unlike the old saying, you actually can ‘start from here’ i.e. with the data you have. An evidence portfolio/framework can actually be enhanced relatively simply, quickly and cost effectively. These thoughts come from a long experience of working with, often imperfect, data sets in order to design care pathways, choose between different medicines or make a reimbursement decision. All of this is equally applicable in the self-medication environment, even if the scale of the data and clinical investment might be smaller. In fact, it is particularly relevant to the competitive world of differentiating OTCs with evidence beyond marketing spin and in the absence of large clinical investment. But, firstly a couple of, perhaps, obvious things to remember about clinical studies and real-world research:

  1. It is rare that any single study provides ‘the answer’. Even when beautifully designed, bias, chance and simple errors can, and do, occur.
  2. There is no such thing as a perfect study design. A well-designed study will set out to answer a question and be specifically designed to do just that, this will mean it will have strengths and weaknesses. Pose a different question and these strengths and weaknesses will be different. The weaknesses, especially, become obvious and magnified when it starts to consider answering multiple questions.
  3. A study lives or dies on its methodology. We may or may not like the results, but whether we trust them or can use them depends entirely on the methodology used to get them. Research is often designed in such a way that it undermines its own results. For example; multiple outcome measures and designs that allow for a multitude of explanations of the data.

So, here are 5 things that you should consider when you are faced with a weak portfolio, generic data or when you want to build a data-set to differentiate or support your brand and you lack the money – or time – to run a large study program:

  1. Trawl & Steal. Systematically draw together the other work that has been done in the same field; the work that has asked similar or related questions. This is by far the most cost-effective way to get a large number of robust enhance insights and a clear data baseline.
  2. Polish. Prospectively re-analyse a study’s results; this can yield valuable insights without the cost of setting up and running a whole new trial. Get relevant associated/secondary data in the public domain [gray papers etc.] and use it!
  3. Strengthen. Run simple studies in parallel to provide a basis for comparison and defend against alternative explanations; this maximises the insights from the investments and supports the production of great claims. It’s like a puzzle and the creativity comes from how you fit the pieces [data] together.
  4. People first. Use simple studies of Patient Reported Outcomes Measures (PROMs) to uncover outcomes that are meaningful for patients and compelling for payers; data that enhances the proposition/claims. To date PROMs have been poorly understood and little used for OTC medicines.
  5. Build a context. Capture the natural history or epidemiology of the condition to provide comparisons data that are often otherwise lacking.

This is not a tick box exercise. This approach needs to be wedded to practical, expert input to pull together a roadmap to evolve and build stronger evidence in a finite resources environment. A hybrid commercial/clinical input model is at its heart. And start small. A few weeks of analysis could quickly confirm the potential and define the benefits/outcomes.

If you would like to talk to Tom and Tim about building an evidence portfolio to drive claims and growth please contact us.

Dr Tom Kenny started life as a GP, he then moved into NHS/Public Health Medicine. He is expert in clinical drug/data evaluation and building real-world data/studies to enhance patient/consumer experience & outcomes. As well as running his own consultancy, Dune, he leads the core team delivering clinical research programmes at Spoonful of Sugar the behavioural data consultancy at Imperial College, University of London.


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