Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation
Recognizing an increasing need for biomarkers that predict clinical outcomes in type 1 diabetes (T1D), JDRF, a major funding organization for T1D research, recently instituted the Core for Assay Validation (CAV) to accelerate the translation of promising assays from discovery to clinical implementat...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2015-01-01
|
| Series: | Biomarker Insights |
| Online Access: | https://doi.org/10.4137/BMI.S29697 |
| _version_ | 1818863062416883712 |
|---|---|
| author | Cate Speake Jared M. Odegard |
| author_facet | Cate Speake Jared M. Odegard |
| author_sort | Cate Speake |
| collection | DOAJ |
| description | Recognizing an increasing need for biomarkers that predict clinical outcomes in type 1 diabetes (T1D), JDRF, a major funding organization for T1D research, recently instituted the Core for Assay Validation (CAV) to accelerate the translation of promising assays from discovery to clinical implementation via a process of coordinated evaluation of biomarkers. In this model, the CAV facilitates the validation of candidate assay methods as well as qualification of proposed biomarkers for a specific clinical use in well-characterized patients. We describe here a CAV-driven pilot project aimed at identifying biomarkers that predict the rate of decline in beta cell function after diagnosis. In a formalized pipeline, candidate assays are first assessed for general rationale, technical precision, and biological associations in a cross-sectional cohort. Those with the most favorable characteristics are then applied to placebo arm subjects of T1D intervention trials to assess their predictive correlation with beta cell function. We outline a go/no-go process for advancing candidate assays in a defined qualification pipeline that also allows for the discovery of novel predictive biomarker combinations. This strategy could be a model for other collaborative biomarker development efforts in and beyond T1D. |
| first_indexed | 2024-12-19T10:09:47Z |
| format | Article |
| id | doaj.art-ae049fcf1cef4d389b77cde79f2bbe3a |
| institution | Directory Open Access Journal |
| issn | 1177-2719 |
| language | English |
| last_indexed | 2024-12-19T10:09:47Z |
| publishDate | 2015-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Biomarker Insights |
| spelling | doaj.art-ae049fcf1cef4d389b77cde79f2bbe3a2022-12-21T20:26:24ZengSAGE PublishingBiomarker Insights1177-27192015-01-0110s410.4137/BMI.S29697Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay ValidationCate Speake0Jared M. Odegard1Diabetes Clinical Research Program, Benaroya Research Institute, Seattle, WA, USA.Diabetes Clinical Research Program, Benaroya Research Institute, Seattle, WA, USA.Recognizing an increasing need for biomarkers that predict clinical outcomes in type 1 diabetes (T1D), JDRF, a major funding organization for T1D research, recently instituted the Core for Assay Validation (CAV) to accelerate the translation of promising assays from discovery to clinical implementation via a process of coordinated evaluation of biomarkers. In this model, the CAV facilitates the validation of candidate assay methods as well as qualification of proposed biomarkers for a specific clinical use in well-characterized patients. We describe here a CAV-driven pilot project aimed at identifying biomarkers that predict the rate of decline in beta cell function after diagnosis. In a formalized pipeline, candidate assays are first assessed for general rationale, technical precision, and biological associations in a cross-sectional cohort. Those with the most favorable characteristics are then applied to placebo arm subjects of T1D intervention trials to assess their predictive correlation with beta cell function. We outline a go/no-go process for advancing candidate assays in a defined qualification pipeline that also allows for the discovery of novel predictive biomarker combinations. This strategy could be a model for other collaborative biomarker development efforts in and beyond T1D.https://doi.org/10.4137/BMI.S29697 |
| spellingShingle | Cate Speake Jared M. Odegard Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation Biomarker Insights |
| title | Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation |
| title_full | Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation |
| title_fullStr | Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation |
| title_full_unstemmed | Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation |
| title_short | Evaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation |
| title_sort | evaluation of candidate biomarkers of type 1 diabetes via the core for assay validation |
| url | https://doi.org/10.4137/BMI.S29697 |
| work_keys_str_mv | AT catespeake evaluationofcandidatebiomarkersoftype1diabetesviathecoreforassayvalidation AT jaredmodegard evaluationofcandidatebiomarkersoftype1diabetesviathecoreforassayvalidation |