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Updated: Nov 18, 2025
11:28
Dried Blood Spots - Preparing and Processing for Use in Immunoassays and in Molecular Techniques
Published on: March 13, 2015
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Mind the Quality Gap When Banking on Dry Blood Spots
David Carpentieri1, Amber Colvard2, Jackie Petersen2
1Department of Pathology and Laboratory Medicine, Clinical Genomics, Phoenix Children's Hospital, Phoenix, Arizona, USA.
Biopreservation and Biobanking
|February 10, 2021
Summary
Dry blood spots (DBS) offer efficient blood sample collection and storage, particularly for pediatric patients. This review explores key indicators for designing effective DBS biobanks for omics platforms and pediatric research.
Area of Science:
- Biotechnology
- Biobanking
- Genomics
Background:
- Dry blood spots (DBS) offer advantages in blood sample collection, processing, storage, and shipment compared to traditional methods.
- The small sample size of DBS makes it ideal for pediatric collections.
- Current Centers for Disease Control and Prevention (CDC) preanalytical standards for DBS are established for inborn errors of metabolism screening but may not cover all analytes or protocols.
Purpose of the Study:
- To review literature for indicators crucial in designing prospective, fit-for-purpose DBS biobanks.
- To provide insights for biobanks focusing on pediatric samples and omics platforms.
Main Methods:
- Literature review of existing studies and guidelines on Dry Blood Spot (DBS) biobanking.
- Analysis of preanalytical standards and their applicability beyond established screening programs.
Main Results:
- DBS offers significant benefits for sample handling and pediatric collections.
- Existing DBS guidelines may require adaptation for novel analytes and research areas.
- Leftover samples and new research interests are driving advancements in DBS biobanking.
Conclusions:
- Designing effective DBS biobanks requires careful consideration of specific analytical needs and sample types.
- Future DBS biobanks, especially for pediatric and omics research, should incorporate tailored indicators for optimal sample integrity and data quality.
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