Generating Evidence for Genomic Diagnostic Test Development

2011 ◽  
2019 ◽  
Vol 134 (2_suppl) ◽  
pp. 53S-57S ◽  
Author(s):  
Marla Petway ◽  
Laura Anderson ◽  
Rosemary Humes ◽  
Stephanie Sincock ◽  
Wendi Kuhnert-Tallman ◽  
...  

This study describes the efforts and outcomes associated with the establishment of a clinical sample repository during the 2016 Zika virus epidemic. To overcome the challenge of limited access to clinical samples to support diagnostic test development, multiple US Department of Health and Human Services (HHS) agencies formed a partnership to create the HHS Zika Specimen Repository. In 2016-2017, the Biomedical Advanced Research and Development Authority and the Centers for Disease Control and Prevention collected patient specimens (4420 convalescent sera aliquots from 100 donors and 7171 plasma aliquots from 239 donors), confirmed Zika virus test results, assembled 1 panel for molecular testing (n = 25 sets) and 7 panels for serologic testing (n = 92), and distributed the panels to test developers. We manufactured 8 test panels and distributed 74 sets of panels to 32 commercial companies, public health partners, and research institutions. Manufacturers used these panels to generate data that supported 14 US Food and Drug Administration (FDA) emergency use authorizations and 1 FDA approval. To develop a repository that can respond immediately to future disease outbreaks, we recommend that organizations pre-position procedures, resources, and partnerships to optimize each partner’s contribution.


2016 ◽  
Vol 10 (2) ◽  
pp. e0004331 ◽  
Author(s):  
Edith Roset Bahmanyar ◽  
William Cairns Smith ◽  
Patrick Brennan ◽  
Ray Cummings ◽  
Malcolm Duthie ◽  
...  

2014 ◽  
Vol 52 (10) ◽  
pp. 3755-3762 ◽  
Author(s):  
C. R. Molins ◽  
C. Sexton ◽  
J. W. Young ◽  
L. V. Ashton ◽  
R. Pappert ◽  
...  

PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0208851 ◽  
Author(s):  
Aekkachai Tuekprakhon ◽  
Orapim Puiprom ◽  
Tadahiro Sasaki ◽  
Johan Michiels ◽  
Koen Bartholomeeusen ◽  
...  

2021 ◽  
Author(s):  
Roman Cerny ◽  
Jodie Ashford ◽  
João Reis-Cunha ◽  
Felipe Campelo

AbstractBackgroundThe development of peptide-based diagnostic tests requires the identification of epitopes that are at the same time highly immunogenic and, ideally, unique to the pathogen of interest, to minimise the chances of cross-reactivity. Existing computational pipelines for the prediction of linear B-cell epitopes tend to focus exclusively on the first objective, leaving considerations of cross-reactivity to later stages of test development.ResultsWe present a multi-objective approach to the prioritisation of candidate epitopes for experimental validation, in the context of diagnostic test development. The dual objectives of uniqueness (measured as dissimilarity from known epitope sequences from other pathogens) and predicted immunogenicity (measured as the probability score returned by the prediction model) are considered simultaneously. Validation was performed using data from three distinct pathogens (namely the nematode Onchocerca volvulus, the Epstein-Barr Virus and the Hepatitis C Virus), with predictions derived using an organism-specific prediction approach. The multi-objective rankings returned sets of non-dominated solutions as potential targets for the development of diagnostic tests with lower probability of false positives due to cross-reactivity.ConclusionsThe application of the proposed approach to three test pathogens led to the identification of 20 new potential epitopes, with both high probability and a high degree of exclusivity to the target organisms. The results indicate the potential of the proposed approach to provide enhanced filtering and ranking of potential candidates, highlighting potential cross-reactivities and including this information into the test development process right from the target identification and prioritisation step.


2021 ◽  
Vol 6 (2) ◽  
pp. 132-143
Author(s):  
Setia Rahmawan ◽  
Harry Firman ◽  
Wiwi Siswaningsih ◽  
Dea Santika Rahayu

This research aims to develop a Pictorial-based Two-Tier Multiple Choice Misconception Diagnostic Test on Buffer Solutions. This research uses the Development and Validation method. The development steps in this method consist of test development (design); validity and reliability test; development of determination key; use of tests, and analysis of results. Based on the content validity test using the Content Validity Ratio (CVR) method, there are 24 items meet the content validity criteria. Based on the reliability test obtained Cronbach's Alpha value of 0.827 which indicates that the developed test is included in the acceptable category. It can identify high school students' misconceptions about the buffer solutions because the presence of pictures can help students understand the problems about the buffer solutions, and can provide an overview of their mental representations so that misconceptions are revealed more deeply.


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