Prediction of systemic free and total valproic acid by off-line analysis of exhaled breath in epileptic children and adolescents
Introduction:
This study explores breath analysis as a tool for therapeutic drug monitoring (TDM) in clinical settings, focusing on valproic acid (VPA) in epilepsy treatment. It contrasts real-time and off-line mass spectrometry methods for analyzing exhaled compounds associated with VPA. Real-time analysis involves direct exhalation into a mass spectrometer, while off-line analysis uses a gas collection device. The study proposes a hybrid approach, combining off-line sample collection with rapid, real-time mass spectrometric analysis. This method allows for flexible, non-invasive monitoring, suitable for a broader range of patients, including those who cannot perform controlled exhalation maneuvers.
The research included 40 epilepsy patients undergoing VPA treatment. The study spanned over 4.5 years, emphasizing safety and accuracy, with measurements aligned with ethical standards and analyzed using advanced statistical tools. The focus was on both the drug's impact and associated side effects.
Breath collected in bags provides a similar metabolic signature as its counterpart by real-time analysis |
(a) Signal intensities of all observed m/z ranging from April 2018 to September 2022. The color bar represents signal intensity (log 10 transformed). (b) Raw mass spectra from identified biomarkers of VPA, the upper half are real-time measurements, and the lower half are bag off-line measurements. Dotted lines represent +−1 ppm deviation. Dashed line represents theoretical mass. ‘x’ represents the centroid for each mass spectral feature. Each color represents a unique measurement (in pairs, real-line and off-line).
Results;
The study highlights the advantage of SESI-HRMS in real-time mapping of a wide range of metabolites. However, its limitation lies in requiring patients to access the mass spectrometer physically. To address this, an alternative method of collecting breath samples in bags for later analysis was evaluated. This approach successfully recovered about 55% of the mass spectral features from breath samples, suggesting its feasibility for clinical applications. The data, collected over four years, demonstrated consistent signal intensity, indicating the method's potential for long-term monitoring despite some signal loss, particularly in heavier compounds.
Systemic VPA prediction using breath collected in bags
The study successfully used a combination of 11 ions detected in exhaled breath to predict systemic concentrations of VPA. This involved focusing on ten ions detectable in positive ion mode, linked to VPA and its metabolites. The research showed good consistency between real-time and off-line analysis, with Lin's concordance correlation coefficient (CCC) indicating varying degrees of agreement among different ions. The study also applied regression models for predicting total and free VPA concentrations, finding the support vector machine algorithms to be most effective. This approach shows promise for remotely predicting VPA concentrations using off-line breath analysis.
Side-effects and drug response
The study investigated the preservation of endogenous compounds associated with side effects and drug response in off-line breath analysis. It focused on 23 ions previously identified as relevant to these clinical outcomes. The evaluation of agreement between off-line and real-time analysis using Lin’s concordance correlation coefficient (CCC) revealed a significant disparity in the quality of off-line readings. Only four out of fifteen ions linked to side effects showed a CCC higher than 0.6, while none of the drug response-related ions reached this threshold, indicating challenges in capturing these endogenous compounds using the off-line method.
Conclusion:
The study concludes that the remote sampling and rapid mass spectrometric analysis of exhaled breath can predict systemic concentrations of valproic acid (VPA) in a clinical setting. However, it highlights limitations in comparing different analytical techniques, urging cautious interpretation of predictive capabilities, especially beyond the therapeutic window. The method is effective for predicting VPA's free fraction and partially captures compounds related to drug response and side effects. Its non-invasive nature and ease of use make it suitable for a wide range of patients, including young children and those with intellectual impairments, suggesting potential for large-scale screening.
