The European Medicines Agency (EMA) on Friday released an updated draft reflection paper for public consultation detailing the agency's framework for pediatric extrapolation in drug development.
EMA defines extrapolation as extending information and conclusions from studies of a particular subgroup (source population), condition or drug to make inferences for another subgroup (target population), condition or drug. By extrapolating data from adult or other pediatric populations, EMA says drugmakers can reduce the amount of, or need for, additional studies in children.
"A more targeted generation of evidence should help to ensure that children only participate in clinical trials with specific objectives that further the scientific understanding of a medicinal products for use in children and address the requirements for regulatory decision-making," EMA writes.
The revised reflection paper comes a year and a half after the previous version and reflects input gathered at a public workshop on pediatric extrapolation held in May 2016 and recognizes the ongoing revision of the International Council for Harmonization's (ICH) E11 guideline on pediatric investigations which discusses the use of extrapolation. ICH indicated that it will take up pediatric extrapolation as a topic for a new guideline.
Despite numerous changes throughout the document, the overarching framework for pediatric extrapolation detailed in a table at the end of both versions of the paper remains unchanged.
The framework proposed by EMA centers on three elements: the extrapolation concept, extrapolation plan, and strategy for mitigating uncertainty and risk. EMA also strongly encourages drugmakers to discuss their strategy for pediatric extrapolation early on.
"It is important to seek regulatory agreement on an extrapolation concept and proposed extrapolation plan before studies are conducted, and again for important changes to the concept or plan as data in the target population emerge," EMA writes.
To develop a concept for extrapolation, EMA says that drugmakers should quantify information about the disease, drug and the populations being looked at. Then, differences between the source and target populations should be used to identify assumptions and uncertainties about dose, exposure, pharmacodynamic response and clinical efficacy.
Using that information, drugmakers can look to create a model for predicting clinical efficacy based on drug exposure (pharmacokinetics), the relationship between pharmacokinetic and pharmacodynamic response, or based on some other pharmacological or clinical justification.
EMA says sponsors should then develop a plan for the tests and trials needed to validate the extrapolation concept.
"This validation confirms whether regulatory decisions can rely on the initial, or revised, predictions for the expected effects of treatment in the target population or if more data needs to be generated," EMA writes.
The regulator says that there may still be residual uncertainties at the time of marketing authorization and that it may be necessary to gather additional data post-authorization.
However, the reflection paper does not make recommendations for preferred approaches or quantitative methods for pediatric extrapolation, and instead seeks to encourage sponsors to explore and justify potentially suitable methods.
EMA also cautions that pediatric extrapolation will not always be justifiable, especially for diseases that are "completely different" in adults and children or where not enough is known about a drug's pharmacology.
But in other situations where the understanding of a drug and disease is well established, EMA says it may be unethical not to extrapolate data as not doing so would expose more children to unnecessary studies.
Additionally, EMA notes that the objectives of extrapolation studies may be different than those of clinical studies.
"Pivotal evidence in an extrapolation plan might be based on matching exposure between the source and target population or precisely quantifying an exposure response relationship," EMA writes, noting that "less common statistical and pharmacometric methods may be used."