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Updated: Jun 14, 2025

Microsampling in Targeted Mass Spectrometry-Based Protein Analysis of Low-Abundance Proteins
Published on: January 13, 2023
Evaluation of low volume sampling devices for a pharmacodynamic biomarker analysis: Challenges and solutions
Xiaoyun Yang1, Evelin Logis1, Kathi Williams1
1BioAnalytical Sciences, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
Abstract:
Low volume sampling technologies have gained popularity as they are minimally invasive, reduce patient burden, enhance population diversity, and have the potential to facilitate decentralized clinical trials. Herein, we validated a Gyrolab assay to measure soluble Mucosal Addressin Cell Adhesion Molecule 1 (sMAdCAM-1) in dried blood samples collected using two low volume sampling devices, Mitra and Tasso-M20. This validated assay was implemented in a proof-of-concept study to compare three low volume sampling devices (Mitra, Tasso-M20 and TassoOne Plus) with serum collected via venipuncture from healthy volunteers receiving etrolizumab. We observed significantly higher concentration of sMAdCAM-1 in dried blood samples collected using Mitra and Tasso-M20 compared to serum in some paired samples, which was attributed to interference from the dried blood extraction buffer. To mitigate this interference, samples required substantial dilution into the appropriate buffer, which negatively impacted the detectability of sMAdCAM-1 with the Gyrolab assay. By employing the Quanterix single molecule array (Simoa), known for its superior assay sensitivity, the interference was minimized in the diluted samples. Both liquid blood collected in TassoOne Plus and dried blood collected using Mitra and Tasso-M20 demonstrated great concordance with serum for sMAdCAM-1 measurement. However, a bias was observed in Mitra dried blood samples, presumably due to the different sample collection sites in comparison with venipuncture and Tasso devices. Our study highlights the potential of low volume sampling technologies for biomarker analysis, and underscores the importance of understanding the challenges and limitations of these technologies before integrating them into clinical studies.
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