= Emerging. More than 5 years before clinical availability. (24.37%, 2023)
= Expected to be clinically available in 1 to 4 years. (39.50%, 2023)
= Clinically available now. (36.13%, 2023)
MSACL 2023 : Heughebaert

MSACL 2023 Abstract

Self-Classified Topic Area(s): Tox / TDM / Endocrine > Various OTHER

Podium Presentation in Steinbeck 1 on Thursday at 15:15 (Chair: Michael Gelb / Gwen McMillin)

Evaluation and Application of Automated Non-contact Reflectance-based Hematocrit Prediction of Dried Blood Spots

Laura Boffel, Liesl Heughebaert, Sigrid Deprez and Christophe Stove
Laboratory of Toxicology, Ghent University, Ghent, Belgium

Liesl Heughebaert, Master in Pharmaceutical Care (Presenter)
Ghent University

Presenter Bio: After successfully completing my Master in Pharmaceutical Care, I graduated as pharmacist in 2020. Mainly due to the interesting research performed during my Master’s thesis in the laboratory of Toxicology of prof. Christophe Stove, I decided to further pursue a career in science and research and started my PhD a few months after graduating. Currently, my work is mainly focusing on automation of microsampling-based analysis, including hematocrit prediction of dried blood microsamples (conventional dried blood spots and samples collected via volumetric absorptive microsampling) and the development of automated microsampling-based LC-MS/MS methods for the analysis of vitamins. Apart from research, I have also been involved in the organization of the last two Young Scientist Symposia of the European Bioanalysis Forum (EBF). I am (co-)author of 6 peer-reviewed publications.


Introduction: Dried blood spot(s) (DBS) microsampling has increasingly attracted interest as a patient-centric alternative to a conventional blood draw. Due to the advances in liquid-chromatography tandem mass spectrometry (LC-MS/MS) equipment, shorter runtimes are being achieved in combination with increased sensitivity. This enables the quantification of lower drug concentrations in samples with limited amount of blood, as low as a few microliters (1). Despite the advances in the field and the many advantages associated with DBS sampling, its widespread use into clinical practice is still hampered, which is mainly caused by the hematocrit (Hct) effect. An important application of DBS lies in the field of therapeutic drug monitoring (TDM), where patient follow-up can be established trough home-sampling for drugs as immunosuppressants (e.g. tacrolimus, sirolimus, everolimus and cyclosporin A). It has previously been demonstrated that fully automated DBS analysis for immunosuppressant drug monitoring suffers from this Hct effect, mainly due to analysis of a partial DBS punch and extractability differences imposed by blood with different Hcts (2). Fortunately, different approaches to cope with this issue have been developed - amongst which the Hct prediction of DBS using ultraviolet-visible (UV-Vis) spectroscopy - which allow Hct correction based on the DBS-predicted Hct (3).

Objectives: Recently, a UV-Vis-based Hct prediction module has been incorporated into the automated CAMAG® DBS-MS 500 HCT system. However, besides a proof-of-principle, no formal in-depth evaluation of this module, or demonstration of its applicability, has been performed. Hence, the aim of this study was twofold. On the one hand, we performed an in-depth evaluation of this module to establish to what extent automated Hct prediction of DBS via this module can universally be applied and generates acceptable results (4). On the other hand, the validated methodology was used to predict the Hct of a relevant set of venous DBS obtained in the framework of TDM of immunosuppressants. More specifically, to demonstrate applicability, the resulting predicted Hct was used to correct for the Hct effect observed in the automated DBS analysis for these compounds and corrected DBS results were compared with paired whole blood concentrations (5).

Methods: Using calibrators (n = 95) and quality control samples (n = 42) generated from authentic patient samples we set up and validated a calibration model using the automated UV-Vis-based hematocrit predicton module. Additionally, we evaluated whether the validated calibration model could serve as a ‘generic’ model for different, independent Hct prediction modules as this would substantially increase user-friendliness and implementation potential. Finally, 48, 47, 58 and 48 paired venous whole blood and venous DBS patient samples were collected for tacrolimus, sirolimus, everolimus, and cyclosporin A quantification, respectively, and analyzed using an automated DBS-MS 500 HCT extraction unit coupled to an LC-MS/MS. Additionally, for all 201 samples the Hct of the DBS was predicted using the automated UV-Vis based Hct prediction module.

Results: A quadratic calibration curve with 1/x² weighting was established. The bias, intra-day and total precision for 8 different cohorts reflecting Hct sub-ranges from 0.157 to 0.537 L/L were below 0.025 L/L, 2.2% and 2.7%, respectively. A lab-lab comparison of the performance of the Hct module of two independently operated instruments demonstrated that the validated model can be used as a generic calibration model. For tacrolimus and cyclosporin A, UV-Vis-based Hct prediction allowed for adequate correction of the Hct effect. Also for sirolimus and everolimus the results greatly improved after Hct correction, although for both a Hct bias remained. Overall, clinical acceptance limits (i.e. ≥ 80% of the samples within 20% difference compared to whole blood) were met for all analytes, demonstrating the feasibility of fully automated DBS extraction (coupled to LC-MS/MS) in combination with UV-Vis-based Hct prediction from DBS for application in clinical practice.

Conclusion: Automated UV-Vis-based Hct prediction of DBS can universally and reliably generate acceptable results. Moreover, by combining Hct prediction with fully automated DBS extraction and LC-MS/MS analysis, we showed that immunosuppressant concentrations can be adequately corrected, yielding a good agreement with whole blood.

1. Deprez S, Heughebaert L, Verougstraete N, Stove V, Verstraete A, Stove C. Automation in microsampling: at your fingertips? In: Siple J, Ehrenfeld E, Lee M, Spooner N, editors. Patient Centric Blood Sampling and Quantitative Bioanalysis. In revision: John Wiley & Sons; 2022.
2. Deprez S, Stove C. Application of a Fully Automated Dried Blood Spot Method for Therapeutic Drug Monitoring of Immunosuppressants. Archives of pathology & laboratory medicine. 2022. DOI: 10.5858/arpa.2021-0533-OA.
3. Capiau S, Wilk LS, De Kesel PMM, Aalders MCG, Stove CP. Correction for the Hematocrit Bias in Dried Blood Spot Analysis Using a Nondestructive, Single-Wavelength Reflectance-Based Hematocrit Prediction Method. Analytical chemistry. 2018;90(3):1795-804.
4. Boffel L, Heughebaert L, Lambrecht S, Luginbuhl M, Stove CP. In-depth evaluation of automated non-contact reflectance-based hematocrit prediction of dried blood spots. The Analyst. 2022;147(23):5445-54.
5. Deprez S, Heughebaert L, Boffel L, Stove CP. Application of non-contact hematocrit prediction technologies to overcome hematocrit effects on immunosuppressants quantification from dried blood spots. Talanta. 2022. DOI: 10.1016/j.talanta.2022.124111.

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