Improving chances for successful clinical outcomes with better preclinical models. Issue 49 (14th December 2017)

• Record Type: Journal Article
• Authors: Wenzel, Heather; Kaminski, Robert W.; Clarkson, Kristen A.; Maciel, Milton; Smith, Mark A.; Zhang, Weiping; Oaks, Edwin V.
• Is Part Of: Vaccine. Volume 35:Issue 49(2017)Part A
• Page Start: 6798
• Page End: 6802
• Publication Date: 2017-12-14
• Subjects: Preclinical -- Shigella -- ETEC -- Enterotoxigenic Escherichia coli -- Challenge model -- Animal models; Vaccines -- Periodicals; 615.372
• DOI: 10.1016/j.vaccine.2017.08.030
• Languages: English
• ISSNs: 0264-410X

Abstract

Highlights: Animal models for ETEC and Shigella may be key in avoiding clinical failures. These models' strengths and weaknesses should be considered in weighing results. To improve reliability of results, standardized reagents and methods are needed. Preclinical correlates of protection should be a focus of future research. Abstract: In order to avoid expensive clinical failures, better and more predictive animal models of vaccine efficacy are needed to screen Shigella and ETEC vaccine candidates for protective efficacy. The 2016 Vaccines Against Shigella and ETEC (VASE) Conference included a workshop focused on the strengths and weaknesses of current models, particularly in terms of the correlation to vaccine efficacy in human clinical trials. Workshop presenters shared information on existing preclinical animal models for assessing the immunogenicity and protective efficacy of Shigella and ETEC vaccines. The presentations were followed by a discussion about how to best utilize these models, how the models can be improved, and best practices for Shigella and ETEC vaccine developers. The workshop concluded with three major recommendations for the field: (1) develop better and more consistent reagents for animal studies and make them widely available, (2) prioritize harmonization of animal models and immunology assays, and (3) develop preclinical correlates of protection, which will be key in selecting the best vaccine candidates for further clinical development.