Clinical trials in paediatric rare diseases present statistical challenges due to the small number of patients available to be enrolled in the trials. Bespoke statistical solutions have been suggested to improve the performance of clinical trials in rare diseases. These solutions include (i) Bayesian statistical methods that allow information from different sources to be formally integrated into the analysis, (ii) enhancing clinical trials through comparator arm data augmentation methods based on external or historical controls in regulatory submissions and (iii) using decision theoretic approaches that account for the population size. However, these methods have rarely, if ever, been applied to clinical trials in pediatrics and must be augmented to ensure their accuracy and applicability to these clinical trials. For example, for data augmentation methods, exchangeability may be challenging to validate, reducing the probability of successful regulatory decisions, and requiring novel methods development to quantify uncertainty in studies which integrate external data.
The IMPaCT lab works within the biostatistics & simulation modelling sub-platform of Rare-Kids-CAN to bring together experts in these novel statistical designs to improve the use of these methods for paediatric rare disease trials by (1) facilitating access to both biostatisticians and simulation specialists with expertise in novel CT designs for RD; (2) providing consultation services aimed at supporting the selection of appropriate designs in pediatric RD; (3) identifying and addressing key areas of methodological development required to address the challenges specific to pediatric RD; (4) developing standardized pathways to obtain key inputs for PRDCTs; and (5) creating an online resource hub for statistical and modelling simulations methods in PRDCTs, combining education modules and software.