Statistical Approaches to Overcome Challenges in Rare Disease Development

February 28, 2019

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In honor of Rare Disease Day 2019 we share a new Cytel podcast featuring Cytel Strategic Consultant Ursula Garczarek discussing how innovative statistical approaches can overcome challenges in rare disease development. Below, you can access the podcast and a summary of some of Ursula's key insights from working in rare diseases and interacting with regulatory agencies for complex and innovative designs.

Regulatory agencies welcome innovative approaches
One of the very positive aspects of working in rare disease development is that the regulatory bodies are very supportive. There is a drive from both from the FDA and from the EMA to accelerate new medicines for rare diseases to market. Of course, they want to know that type one error control in confirmatory
development is demonstrated and proven. Beyond this, in my experience, they are very receptive to innovative approaches so rather than saying of a design ‘ We’ve never seen this before' they will say ‘ This looks complex, please tell us more.' Personally, I recently had a very positive experience with the EMA when helping a sponsor to successfully defend a design that was extremely complex with population enrichment, sample size re-estimation, and dose selection adaptations.

Innovative designs enable better decisions in rare disease development
In a rare disease, you have scarce patients and small sample sizes so you have to make your decisions extremely carefully. You also need to ensure you are deriving the maximum information out of any trial subject that you can. The main advantage of using an adaptive approach is that you are not 'stuck' too long with an incorrect decision based on any of the assumptions underlying your study design. If with a non-adaptive approach you were able to make correct decisions only, you would actually need fewer patients than using an adaptive trial. In reality, there are many uncertainties in rare disease development because you are starting with much less knowledge compared with non-rare diseases. For example, you may not know the best endpoints, the nature of the effect size in the endpoint, the level of variability and there may also be subgroups in the indication to account for.
So, using a non-adaptive approach, you might choose an endpoint, effect size, and variability around that effect size. All of these assumptions would carry high uncertainty and potentially invalidate all the “optimality” of your planning. By using a flexible design, you can start with a set of plausible assumptions, but allow the trial to adapt to the learning that you gain at interim points. In this way, you prevent taking the trial in the wrong direction for too long.

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When does it make sense to adapt?
Cytel's 10 steps to consider before choosing an adaptive design by Jim Bolognese and Ranganath Nayak are an excellent starting point when considering to go adaptive. And the very first question is whether there is sufficient time between the interim observation for adaptation and the enrollment of the last patient. If you have a very fast recruiting trial and you need a long time to observe the endpoint, then typically it wouldn't make much sense to adapt unless you have an early biomarker which you could use for interim decision making. Other than that, an adaptive approach is advantageous in general and beyond rare diseases in any situation where you have this uncertainty in important decisions for study design like the target population, the endpoint, the effect size and the variability in endpoints. When being reasonably uncertain on any of those it makes sense to do e.g. a blinded sample size re-estimation or another interim decision where you check your basic assumptions at an interim analysis before deciding to go one way or the other.

Advice for Rare Disease Developers
My advice for rare disease developers is not dissimilar to the advice that I would give to a developer in any area. It is to, first of all, look very closely at the data that you already have and ensure you are making the best use of that. Translate any pharmacometrics information that you have and your learning from pre-clinical studies into better decision making for your next studies. If you have decided that your development would be best supported with an adaptive trial, then get into discussions with the authorities as soon as possible to make sure that the design you have in mind is being supported by them.

Click the button below to play the podcast for more insights.
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 Cytel has supported many sponsors design and implement innovative trials to support their rare disease development programs. To arrange an informal discussion about your next project, click the button below.

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