Recent advances in methodology for clinical trials in small populations: the InSPiRe project

Tim Friede,
Martin Posch,
Sarah Zohar,
Corinne Alberti,
Norbert Benda,
Emmanuelle Comets,
Simon Day,
Alex Dmitrienko,
Alexandra Graf,
Burak Kürsad Günhan,
Siew Wan Hee,
Frederike Lentz,
Jason Madan,
Frank Miller,
Thomas Ondra,
Michael Pearce,
Christian Röver,
Artemis Toumazi,
Steffen Unkel,
Moreno Ursino,
Gernot Wassmer and
Nigel StallardEmail author View ORCID ID profile

Orphanet Journal of Rare Diseases201813:186

https://doi.org/10.1186/s13023-018-0919-y

Received: 20 December 2017
Accepted: 24 September 2018
Published: 25 October 2018

Abstract

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017.

The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods.