Background. Unique challenges posed by emerging infectious diseases often expose inadequacies in the conventional phased investigational therapeutic development paradigm. The recent Ebola outbreak in West Africa presents a critical case-study highlighting barriers to faster development. During the outbreak, clinical trials were implemented with unprecedented speed. Yet, in most cases, this fast-tracked approach proved too slow for the rapidly evolving epidemic. Controversy abounded as to the most appropriate study designs to yield safety and efficacy data, potentially causing delays in pivotal studies. Preparation for research during future outbreaks may require acceptance of a paradigm that circumvents, accelerates, or reorders traditional phases, without losing sight of the traditional benchmarks by which drug candidates must be assessed for activity, safety and efficacy. Methods. We present the design of an adaptive, parent protocol, ongoing in West Africa until January 2016. The exigent circumstances of the outbreak and limited prior clinical experience with experimental treatments, led to more direct bridging from preclinical studies to human trials than the conventional paradigm would typically have sanctioned, and required considerable design flexibility. Results. Preliminary evaluation of the "barely Bayesian" design was provided through computer simulation studies. The understanding and public discussion of the study design will help its future implementation.
|Original language||English (US)|
|Number of pages||8|
|Journal||Journal of Infectious Diseases|
|State||Published - Jun 15 2016|
Bibliographical noteFunding Information:
This work was partially funded by the Division of Clinical Research, National Institute of Allergy and Infectious Diseases. This project has been funded in part with federal funds from the National Cancer Institute, National Institutes of Health (contract HHSN261200800001E)
© 2016 Published by Oxford University Press for the Infectious Diseases Society of America.
- Adaptive design
- Bayesian design
- Clinical trials
- Ebola virus disease
- Emerging infectious diseases