Use of prior knowledge and extrapolation in paediatric drug development: A case study with deferasirox.

The characterisation of pharmacokinetics, pharmacodynamics and dose-exposure-response relationships requires data arising from well-designed study protocols and a relatively large sample from the target patient population. Such a prerequisite is unrealistic for paediatric rare diseases, where the patient population is often vulnerable and very small. In such cases, different sources of data and knowledge need to be considered to ensure trial designs are truly informative and oncoming data can be analysed efficiently. Here, we use clinical trial simulations to assess the contribution of historical data for (1) the analysis of sparse samples from a limited number of children and (2) the optimization of study design when an increase in number of subjects is not feasible. The evaluation of the pharmacokinetics of deferasirox in paediatric patients affected by haemoglobinopathies was used as case study. Our investigation shows that the incorporation of prior knowledge increases parameter precision and probability of successful convergence from only 12% with no priors to 56% and 75% for weakly and highly informative priors, respectively. In addition, we show that even when only one sample is collected per subject, as implemented in the original trial and in many other examples in clinical research, there is a 60% probability of biased parameter estimates (> 25%). In conjunction with adult prior information and optimization techniques, the probability of bias could be limited to <20% by increasing the number of samples/subject from 1 to 3. The methodology described here can be easily applied to other studies in small populations.