title: Bridging the gap
title: using extrapolation to reduce the experimental burden in children
titleType: Subtitle
Creators: name: Wadsworth, Ian
Publisher: name: Lancaster University
Year: 2018
Subjects: Extrapolation
Paediatric
Clinical trials
Bayesian

description: When developing a new drug product for children, it is important to
      provide safe and effective medicines whilst minimising the experimental
      burden where possible. Extrapolating data from clinical trials in adults
      or other relevant populations has the potential to reduce the number or
      size of clinical trials required to obtain a licence for a new drug in the
      paediatric population. The ethical and practical benefits extrapolation
      can provide, such as speeding up access to medicines, reducing drug
      development costs and avoiding replication of existing information, have
      to be balanced against potential risks i.e. if extrapolation from adults
      is incorrectly deemed to be appropriate, children could be exposed to a
      harmful or ineffective treatment. Extrapolation is therefore a challenging
      but important aspect for future paediatric medicine development.
      
      The work presented in this thesis is broadly interested in approaches for
      reducing the experimental burden in the paediatric population by
      leveraging external information, such as existing adult data or the
      opinion of clinical experts. The concept of extrapolation, especially in
      the context of paediatric clinical trials, is explored over the thesis,
      beginning with a literature review of extrapolation methodology in Chapter
      3, particularly aiming to identify potentially relevant methods for
      performing extrapolations to children.
      
      Extrapolation can be a potentially controversial approach to take in drug
      development, so the opinion of experts within a target clinical setting is
      incredibly valuable. Chapters 4 and 5 describe the process and outcome of
      seeking the opinion of clinical experts regarding extrapolation in
      epilepsy drug development. Based on this expert opinion, an outline for a
      new drug development paradigm is presented allowing for simultaneous
      recruitment of adults and paediatric patients aged 2 years and older, from
      Phase II onwards.
      
      In order for the extrapolation of efficacy data from adult trials to the
      paediatric population to be plausible and appropriate, strong assumptions
      regarding similarity between these populations are required. One important
      assumption is whether adults and children can be said to have similar
      pharmacokinetic-pharmacodynamic (PK-PD) relationships. In Chapter 6, an
      approach is developed to use data from existing studies of adults and
      adolescents, along with expert opinion, to quantify prior uncertainty
      regarding the similarity of PK-PD relationships in adults and younger
      children. A bias-adjusted meta-analysis of existing adult and adolescent
      data allows the derivation of prior distributions quantifying our
      uncertainty about the extrapolation assumption and calculation of the
      prior probability that the extrapolation assumption holds. This approach
      could be extended to quantifying prior uncertainty in other contexts; here
      we consider PK-PD relationships in adults and younger children to provide
      a clear focus.
      
      Within the paediatric population itself, there may exist distinct age
      groups with different PK-PD relationships requiring separate dosing rules
      to account for pharmacological differences. Chapter 7 considers
      model-based approaches to quantify how parameters of PK-PD models differ
      over age. Based on this, an approach for deriving optimal dosing rules
      accounting for differences between age groups is developed.