  Among many efforts to facilitate timely access to safe and effective
medicines to children, increased attention has been given to extrapolation.
Loosely, it is the leveraging of conclusions or available data from adults or
older age groups to draw conclusions for the target pediatric population when
it can be assumed that the course of the disease and the expected response to a
medicinal product would be sufficiently similar in the pediatric and the
reference population. Extrapolation then can be characterized as a statistical
mapping of information from the reference (adults or older age groups) to the
target pediatric population. The translation, or loosely mapping of
information, can be through a composite likelihood approach where the
likelihood of the reference population is weighted by exponentiation and that
this exponent is related to the value of the mapped information in the target
population. The weight is bounded above and below recognizing the fact that
similarity (of the disease and the expected response) is still valid despite
variability of response between the cohorts. Maximum likelihood approaches are
then used for estimation of parameters and asymptotic theory is used to derive
distributions of estimates for use in inference. Hence, the estimation of
effects in the target population borrows information from reference population.
In addition, this manuscript also talks about how this method is related to the
Bayesian statistical paradigm.
