Analysis Of Breath Samples Research Articles

Point-of-care breath sample analysis by semiconductor-based E-Nose technology discriminates non-infected subjects from SARS-CoV-2 pneumonia patients: a multi-analyst experiment.

Metal oxide sensor-based electronic nose (E-Nose) technology provides an easy to use method for breath analysis by detection of volatile organic compound (VOC)-induced changes of electrical conductivity. Resulting signal patterns are then analyzed by machine learning (ML) algorithms. This study aimed to establish breath analysis by E-Nose technology as a diagnostic tool for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pneumonia within a multi-analyst experiment. Breath samples of 126 subjects with (n=63) or withoutSARS-CoV-2 pneumonia (n=63) were collected using the ReCIVA® Breath Sampler, enriched and stored on Tenax sorption tubes, and analyzed using an E-Nose unit with 10 sensors. ML approaches were applied by three independent data analyst teams and included a wide range of classifiers, hyperparameters, training modes, and subsets of training data. Within the multi-analyst experiment, all teams successfully classified individuals as infected or uninfected with an averaged area under the curve (AUC) larger than 90% and misclassification error lower than 19%, and identified the same sensor as most relevant to classification success. This new method using VOC enrichment and E-Nose analysis combined with ML can yield results similar to polymerase chain reaction (PCR) detection and superior to point-of-care (POC) antigen testing. Reducing the sensor set to the most relevant sensor may prove interesting for developing targeted POC testing.

Neonatal Exhaled Breath Sampling for Infrared Spectroscopy: Biomarker Analysis.

Monitoring health conditions in neonates for early therapeutic intervention in case deviations from physiological conditions is crucial for their long-term development. Due to their immaturity preterm born neonates are dependent on particularly careful physical and neurological diagnostic methods. Ideally, these should be noninvasive, noncontact, and radiation free. Infrared spectroscopy was used to analyze exhaled breath from 71 neonates with a special emphasis on preterm infants, as a noninvasive, noncontact, and radiation-free diagnostic tool. Passive sample collection was performed by skilled clinicians. Depending on the mode of respiratory support of infants, four different sampling procedures were adapted to collect exhaled breath. With the aid of appropriate reference samples, infrared spectroscopy has successfully demonstrated its effectiveness in the analysis of breath samples of neonates. The discernible increase in concentrations of carbon dioxide, carbon monoxide, and methane in collected samples compared to reference samples served as compelling evidence of the presence of exhaled breath. With regard to technical hurdles and sample analysis, samples collected from neonates without respiratory support proved to be more advantageous compared to those obtained from intubated infants and those with CPAP (continuous positive airway pressure). The main obstacle lies in the significant dilution of exhaled breath in the case of neonates receiving respiratory support. Metabolic analysis of breath samples holds promise for the development of noninvasive biomarker-based diagnostics for both preterm and sick neonates provided an adequate amount of breath is collected.

Detection of COVID-19 through breath sample analysis with an electronic nose

Detection of COVID-19 through breath sample analysis with an electronic nose

HS-GC–MS analysis of volatile organic compounds after hyperoxia-induced oxidative stress: a validation study

BackgroundExhaled volatile organic compounds (VOCs), particularly hydrocarbons from oxidative stress-induced lipid peroxidation, are associated with hyperoxia exposure. However, important heterogeneity amongst identified VOCs and concerns about their precise pathophysiological origins warrant translational studies assessing their validity as a marker of hyperoxia-induced oxidative stress. Therefore, this study sought to examine changes in VOCs previously associated with the oxidative stress response in hyperoxia-exposed lung epithelial cells.MethodsA549 alveolar epithelial cells were exposed to hyperoxia for 24 h, or to room air as normoxia controls, or hydrogen peroxide as oxidative-stress positive controls. VOCs were sampled from the headspace, analysed by gas chromatography coupled with mass spectrometry and compared by targeted and untargeted analyses. A secondary analysis of breath samples from a large cohort of critically ill adult patients assessed the association of identified VOCs with clinical oxygen exposure.ResultsFollowing cellular hyperoxia exposure, none of the targeted VOCs, previously proposed as breath markers of oxidative stress, were increased, and decane was significantly decreased. Untargeted analysis did not reveal novel identifiable hyperoxia-associated VOCs. Within the clinical cohort, three previously proposed breath markers of oxidative stress, hexane, octane, and decane had no real diagnostic value in discriminating patients exposed to hyperoxia.ConclusionsHyperoxia exposure of alveolar epithelial cells did not result in an increase in identifiable VOCs, whilst VOCs previously linked to oxidative stress were not associated with oxygen exposure in a cohort of critically ill patients. These findings suggest that the pathophysiological origin of previously proposed breath markers of oxidative stress is more complex than just oxidative stress from hyperoxia at the lung epithelial cellular level.

An analytical approach for on-site analysis of breath samples for Δ9-tetrahydrocannabinol (THC).

Increased acceptance of cannabis containing the psychoactive component, Δ9-tetrahydrocannabinol (THC), raises concerns about the potential for impaired drivers and increased highway accidents. In contrast to the "breathalyzer" test, which is generally accepted for determining the alcohol level in a driver, there is no currently accepted roadside test for THC in a motorist. There is a need for an easily collectible biological sample from a potentially impaired driver coupled with an accurate on-site test to measure the presence and quantity of THC in a driver. A novel breath collection device is described, which includes three separate sample collectors for collecting identical A, B, and C breath samples from a subject. A simple one-step ethanol extraction of the "A" breath collector sample can be analyzed by UHPLC/selected ion monitoring (SIM) liquid chromatography/mass spectrometry (LC/MS) to provide qualitative and quantitative determination of THC in breath sample in less than 4 min for samples collected up to 6 h after smoking a cannabis cigarette. SIM LC/MS bioanalyses employed d3-THC as the stable isotope internal standard fortified in negative control breath samples for quantitation including replicates of six calibrator standards and three quality control (QC) samples. Subsequent confirmation of the same breath sample in the B collectors was then confirmed by a reference lab by LC/MS/MS analysis. Fit-for-purpose bioanalytical validation consistent with pharmaceutical regulated bioanalyses produced pharmacokinetic (PK) curves for the two volunteer cannabis smokers. These results produced PK curves, which showed a rapid increase of THC in the breath of the subjects in the first hour followed by reduced THC levels in the later time points. A simpler single-point calibration curve procedure with calibrators and QC prepared in ethanol provided similar results. Limitations to this approach include the higher cost and operator skill sets for the instrumentation employed and the inability to actually determine driver impairment.

Preservation of exhaled breath samples for analysis by off-line SESI-HRMS: proof-of-concept study

Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) is an established technique in the field of breath analysis characterized by its short analysis time, as well as high levels of sensitivity and selectivity. Traditionally, SESI-HRMS has been used for real-time breath analysis, which requires subjects to be at the location of the analytical platform. Therefore, it limits the possibilities for an introduction of this methodology in day-to-day clinical practice. However, recent methodological developments have shown feasibility on the remote sampling of exhaled breath in Nalophan® bags prior to measurement using SESI-HRMS. To further explore the range of applications of this method, we conducted a proof-of-concept study to assess the impact of the storage time of exhaled breath in Nalophan® bags at different temperatures (room temperature and dry ice) on the relative intensities of the compounds. In addition, we performed a detailed study of the storage effect of 27 aldehydes related to oxidative stress. After 2 h of storage, the mean of intensity of all m/z signals relative to the samples analyzed without prior storage remained above 80% at both room temperature and dry ice. For the 27 aldehydes, the mean relative intensity losses were lower than 20% at 24 h of storage, remaining practically stable since the first hour of storage following sample collection. Furthermore, the mean relative intensity of most aldehydes in samples stored at room temperature was higher than those stored in dry ice, which could be related to water vapor condensation issues. These findings indicate that the exhaled breath samples could be preserved for hours with a low percentage of mean relative intensity loss, thereby allowing more flexibility in the logistics of off-line SESI-HRMS studies.

The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis

Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.

A novel breath molecule sensing system based on deep neural network employing multiple-line direct absorption spectroscopy

A novel ppb-level biomedical sensor is developed to analyze breath samples for continuous monitoring of diseases. The setup is very compact, consisting of a distributed feedback quantum cascade laser (DFB-QCL) and a single-pass absorption cell. To make the sensor more compact and functional, a deep neural network (DNN) model is utilized for predicting gas concentrations. In order to evaluate the performance of the sensor, N2O is used as the target molecule. A minimum detection limit of 500 ppb is achieved in a single-pass absorption cell configuration. The model is trained on multiple N2O/CO2 absorption lines (instead of an isolated line) with concentrations between 0 to 500 ppm generated using the HITRAN database. The trained model is tested on measured spectra and compared to a non-linear least squares fitting algorithm. The coefficients of determination (R2) were found to be 0.997 and 0.981 for the predictions of N2O concentrations in the N2O/N2 gas mixture and the breath air, respectively. The accuracies of 2.5% and 2.9% were achieved by the sensor for both cases.

Breath Analysis in Children with Ketogenic Glycogen Storage Diseases

(1) Background: The treatment goal of ketogenic glycogen storage diseases (GSDs) is appropriate control of hypoglycemia and other disturbances such as dyslipidemia. Monitoring and treatment of ketosis are known to improve outcomes. We used breath analysis to identify volatile organic compounds (VOCs) that correlate with serum ketones in order to provide a non-invasive method of monitoring ketosis. (2) Methods: Consecutive children with ketogenic GSDs were recruited from a single center during routine admission to monitor serum glucose and ketone levels. Five breath samples were collected from every patient at the same time of blood draws. SIFT-mass spectrometry was used to analyze breath samples. Univariate linear mixed-effects regression models for 22 known VOCs and either serum ketones or glucose were performed. (3) Results: Our cohort included 20 patients aged 5–15 years with a mean BMI of 20 kg/m2 (72% tile). Most patients had GSD type 0 (35%), while 25% had type IX. VOCs that showed a significant correlation with serum ketone levels included acetone (p < 0.0001), trimethylamine (p < 0.0001), pentane (p = 0.0001), 3-methylhexane (p = 0.0047), and carbon disulfide (p = 0.0499). No correlation was found between serum glucose and any VOC. (4) Conclusions: Breath analysis is a promising noninvasive tool that can be used to predict ketone serum levels in patients with GSD.

High-resolution mass spectrometry exhalome profiling with a modified direct analysis in real time ion source.

Exhaled breath contains many substances that are closely related to human metabolism. Analysis of its composition is important for human health, but it is difficult. Since the volatile molecules in breath samples are exhaled instantaneously, easily diffused and modified, and at low level of presence, they are difficult to identify and quantify. A modified direct analysis in real time ion source was used for high-resolution mass spectrometry measurement of human metabolites in exhaled breath through online monitoring and offline analysis, in both positive and negative ion modes. The improved system enabled the breath volatiles as well as condensates to be directly sampled, rapidly transmitted and efficiently ionized in a confined region, and then detected using an Orbitrap mass analyzer. The molecular features with online and offline analysis of exhaled breath were demonstrated with obvious differences. A total ofabout 65 metabolites in positive ion mode and about 55 metabolites in negative ion mode were identified based on accurate m/z values. Exhalome profile and the composition proportion of different classes of compounds were obtained. The relative contents of metabolites from breath varied during different time periods throughout a day. A more complete picture of the human breath metabolome was provided combining the results obtained from both online and offline analysis. The developed method allows analysis of breath samples with different status rapidly and directly, and it features simple operation and metabolite identification, requiring little or no sample preparation.

A compact breath gas sensor system based on terahertz/millimeter-wave gas spectroscopy

Abstract We demonstrate a full-cycle breath gas sensor system based on terahertz/millimeter-wave gas spectroscopy. The sensor consists of a transmitter and receiver working around 250 GHz based on SiGe BiCMOS technology. Typical detection thresholds are in the ppm range depending on the respective molecule. The data analysis provides partial pressures of the investigated molecules by fitting of spectra which are measured by wavelength modulation. Beside the spectroscopic measurement and the data analysis, a full cycle of breath analysis includes the sampling and the conditioning of the sample tubes. The full cycle takes about 35 min per sample in average. As the system is compact and easy to operate, it allows for on-site analysis of breath samples in medical laboratories or hospitals.

Millimeter-wave gas spectroscopy for breath analysis of COPD patients in comparison to GC-MS

The analysis of human breath is a very active area of research, driven by the vision of a fast, easy, and non-invasive tool for medical diagnoses at the point of care. Millimeter-wave gas spectroscopy (MMWGS) is a novel, well-suited technique for this application as it provides high sensitivity, specificity and selectivity. Most of all, it offers the perspective of compact low-cost systems to be used in doctors’ offices or hospitals. In this work, we demonstrate the analysis of breath samples acquired in a medical environment using MMWGS and evaluate validity, reliability, as well as limitations and perspectives of the method. To this end, we investigated 28 duplicate samples from chronic obstructive lung disease patients and compared the results to gas chromatography-mass spectrometry (GC-MS). The quantification of the data was conducted using a calibration-free fit model, which describes the data precisely and delivers absolute quantities. For ethanol, acetone, and acetonitrile, the results agree well with the GC-MS measurements and are as reliable as GC-MS. The duplicate samples deviate from the mean values by only 6% to 18%. Detection limits of MMWGS depend strongly on the molecular species. For example, acetonitrile can be traced down to 1.8 × 10−12 mol by the MMWGS system, which is comparable to the GC-MS system. We observed correlations of abundances between formaldehyde and acetaldehyde as well as between acetonitrile and acetaldehyde, which demonstrates the potential of MMWGS for breath research.

Role of Breath Biopsy in COVID-19.

BackgroundCOVID-19 is a highly contagious respiratory disease that can be transmitted through human exhaled breath. It has caused immense loss and has challenged the healthcare sector. It has affected the economy of countries and thereby affected numerous sectors. Analysis of human breath samples is an attractive strategy for rapid diagnosis of COVID-19 by monitoring breath biomarkers.ContentBreath collection is a noninvasive process. Various technologies are employed for detection of breath biomarkers like mass spectrometry, biosensors, artificial learning, and machine learning. These tools have low turnaround time, robustness, and provide onsite results. Also, MS-based approaches are promising tools with high speed, specificity, sensitivity, reproducibility, and broader coverage, as well as its coupling with various chromatographic separation techniques providing better clinical and biochemical understanding of COVID-19 using breath samples.SummaryHerein, we have tried to review the MS-based approaches as well as other techniques used for the analysis of breath samples for COVID-19 diagnosis. We have also highlighted the different breath analyzers being developed for COVID-19 detection.

Indeterminacy of cannabis impairment and ∆9-tetrahydrocannabinol (∆9-THC) levels in blood and breath

Previous investigators have found no clear relationship between specific blood concentrations of ∆9-tetrahydrocannabinol (∆9-THC) and impairment, and thus no scientific justification for use of legal “per se” ∆9-THC blood concentration limits. Analyzing blood from 30 subjects showed ∆9-THC concentrations that exceeded 5 ng/mL in 16 of the 30 subjects following a 12-h period of abstinence in the absence of any impairment. In blood and exhaled breath samples collected from a group of 34 subjects at baseline prior to smoking, increasing breath ∆9-THC levels were correlated with increasing blood levels (P < 0.0001) in the absence of impairment, suggesting that single measurements of ∆9-THC in breath, as in blood, are not related to impairment. When post-smoking duration of impairment was compared to baseline ∆9-THC blood concentrations, subjects with the highest baseline ∆9-THC levels tended to have the shortest duration of impairment. It was further shown that subjects with the shortest duration of impairment also had the lowest incidence of horizontal gaze nystagmus at 3 h post-smoking compared to subjects with the longest duration of impairment (P < 0.05). Finally, analysis of breath samples from a group of 44 subjects revealed the presence of transient cannabinoids such as cannabigerol, cannabichromene, and ∆9-tetrahydrocannabivarin during the peak impairment window, suggesting that these compounds may be key indicators of recent cannabis use through inhalation. In conclusion, these results provide further evidence that single measurements of ∆9-THC in blood, and now in exhaled breath, do not correlate with impairment following inhalation, and that other cannabinoids may be key indicators of recent cannabis inhalation.

Pulmonary Oxygen Toxicity Through Exhaled Breath Markers After Hyperbaric Oxygen Treatment Table 6.

Introduction: The hyperbaric oxygen treatment table 6 (TT6) is widely used to manage dysbaric illnesses in divers and iatrogenic gas emboli in patients after surgery and other interventional procedures. These treatment tables can have adverse effects, such as pulmonary oxygen toxicity (POT). It is caused by reactive oxygen species’ damaging effect in lung tissue and is often experienced after multiple days of therapy. The subclinical pulmonary effects have not been determined. The primary aim of this study was to measure volatile organic compounds (VOCs) in breath, indicative of subclinical POT after a TT6. Since the exposure would be limited, the secondary aim of this study was to determine whether these VOCs decreased to baseline levels within a few hours. Methods: Fourteen healthy, non-smoking volunteers from the Royal Netherlands Navy underwent a TT6 at the Amsterdam University Medical Center—location AMC. Breath samples for GC-MS analysis were collected before the TT6 and 30 min, 2 and 4 h after finishing. The concentrations of ions before and after exposure were compared by Wilcoxon signed-rank tests. The VOCs were identified by comparing the chromatograms with the NIST library. Compound intensities over time were tested using Friedman tests, with Wilcoxon signed-rank tests and Bonferroni corrections used for post hoc analyses. Results: Univariate analyses identified 11 compounds. Five compounds, isoprene, decane, nonane, nonanal and dodecane, showed significant changes after the Friedman test. Isoprene demonstrated a significant increase at 30 min after exposure and a subsequent decrease at 2 h. Other compounds remained constant, but declined significantly 4 h after exposure. Discussion and Conclusion: The identified VOCs consisted mainly of (methyl) alkanes, which may be generated by peroxidation of cell membranes. Other compounds may be linked to inflammatory processes, oxidative stress responses or cellular metabolism. The hypothesis, that exhaled VOCs would increase after hyperbaric exposure as an indicator of subclinical POT, was not fulfilled, except for isoprene. Hence, no evident signs of POT or subclinical pulmonary damage were detected after a TT6. Further studies on individuals recently exposed to pulmonary irritants, such as divers and individuals exposed to other hyperbaric treatment regimens, are needed.

The Utility of Breath Analysis in the Diagnosis and Staging of Parkinson's Disease.

The analysis of volatile organic compounds (VOCs) collected in breath samples has the potential to be a rapid, non-invasive test to aid in the clinical diagnosis and tracking of chronic conditions such as Parkinson's disease (PD). To assess the feasibility and utility of breath sample analysis done, both at point of collection in clinic and when sent away to be analyzed remotely, to diagnose, stratify and monitor disease course in a moderately large cohort of patients with PD. Breath samples were collected from 177 people with PD and 37 healthy matched control individuals followed over time. Standard clinical data (MDS-UPDRS & cognitive assessments) from the PD patients were collected at the same time as the breath sample was taken, these measures were then correlated with the breath test analysis of exhaled VOCs. The breath test was able to distinguish patients with PD from healthy control participants and correlated with disease stage. The off-line system (remote analysis) gave good results with overall classification accuracies across a range of clinical measures of between 73.6% to 95.6%. The on-line (in clinic) system showed comparable results but with lower levels of correlation, varying between 33.5% to 82.4%. Chemical analysis identified 29 potential molecules that were different and which may relate to pathogenic pathways in PD. Breath analysis shows potential for PD diagnostics and monitoring. Both off-line and on-line sensor systems were easy to do and provided comparable results which will enable this technique to be easily adopted in clinic if larger studies confirm our findings.

Breath collection protocol for SARS-CoV-2 testing in an ambulatory setting

Background. The SARS-CoV-2 pandemic changed the way the society functioned. The race to develop a rapid, non-invasive, widely available test resulted in multiple studies examining the potential of breath to be that ‘game changing test’. Breath sampling is a non-invasive point of care test, but SAR-CoV-2 has introduced a level of danger into collection and analysis that requires a change in workflow to keep staff and participants safe. We developed a SARS-CoV 2 breath test work flow for collection and processing of breath samples in an ambulatory care setting and prospectively evaluated the protocol. Protocol development included testing the effect of respiratory filters on the integrity and reproducibility of breath samples. Methods. Prospective, observational study conducted at community COVID-19 testing sites, collecting breath samples from patients presenting for RT-PCR testing. Breath was collected via Tedlar®, and/or BioVOC-2™ as well as an environmental sample for all participants. Samples were transferred to Tenex tubes, dry purged and analyzed using a Centri automated sample introduction machine, GC, and a Bench-ToF-HD. Results. We successfully collected and processed 528 breath samples from 393 participants at community-based ambulatory COVID-19 test sites. The majority of samples were collected before vaccines were available and throughout the emergence of the Delta Variant. No staff member was infected. Conclusion. We demonstrated a safe workflow for the collection, handling, transport, storage, and analysis of breath samples during the pandemic collecting highly infectious SARS-CoV-2 positive breath samples. This was done without filters as they added complexity to the breath matrix, jeopardizing the sample integrity.

Delayed Analysis of Hydrogen-Methane Breath Samples.

PurposeHydrogen-methane breath tests are used to diagnose carbohydrate malabsorption and small intestinal bacterial overgrowth. The COVID-19 pandemic has driven the modification of procedures as breath tests are potentially aerosol-generating procedures. We assessed the effect of delayed analysis of breath samples, facilitating the at-home performance of breath testing.MethodsChildren provided two breath samples at every step of the lactose breath test. The samples were brought back to the clinic, and one set of samples was analyzed immediately. The second set was stored at room temperature and analyzed 1-4 days later.ResultsOut of the 73 “double” lactose breath tests performed at home, 33 (45.8%) were positive. The second samples were analyzed 20 to 117 hours after the first samples (41.7±24.3 hours). There was no significant difference in the hydrogen concentration between the first and second sets (Z=0.49, p=0.62). This was not the case for methane, which had a significantly higher concentration in the second breath samples (Z=7.6).ConclusionExpired hydrogen levels remain stable in plastic syringes if preserved at room temperature for several days. On the other hand, the delayed analysis of methane appeared to be less reliable. Further research is needed to examine the impact of delayed analysis on methane and hydrogen concentrations.

Combination of Exhaled Breath Analysis with Parallel Lung Function and FeNO Measurements in Infants.

Breath analysis by secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) offers the possibility to measure comprehensive metabolic profiles. The technology is currently being deployed in several clinical settings in Switzerland and China. However, patients are required to exhale directly into the device located in a dedicated room. Consequently, clinical implementation in patients incapable of performing necessary exhalation maneuvers (e.g., infants) or immobile (e.g., too weak, elderly, or in intensive care) remains a challenge. The aim of this study was to develop a method to extend such breath analysis capabilities to this subpopulation of patients by collecting breath samples remotely (offline) and promptly (within 10 min) transfer them to SESI-HRMS for chemical analysis. We initially assessed the method in adults by comparing breath mass spectra collected offline with Nalophan bags against spectra of breath samples collected in real time. In total, 13 adults provided 176 pairs of real-time and offline measurements. Lin's concordance correlation coefficient (CCC) was used to estimate the agreement between offline and real-time analyses. Here, 1249 mass spectral features (55% of total detected) exhibited Lin's CCC > 0.6. Subsequently, the method was successfully deployed to analyze breath samples from infants (n = 16), obtaining as a result SESI-HRMS breath profiles. To demonstrate the clinical feasibility of the method, we measured in parallel other clinical variables: (i) lung function, which characterizes the breathing patterns, and (ii) nitric oxide, which is a surrogate marker of airway inflammation. As a showcase, we focused our analysis on the exhaled oxidative stress marker 4-hydroxynonenal and its association with nitric oxide and minute ventilation.

Lung pharmacokinetics of inhaled and systemic drugs: A clinical evaluation.

Human pharmacokinetic studies of lung-targeted drugs are typically limited to measurements of systemic plasma concentrations, which provide no direct information on lung target-site concentrations. We aimed to evaluate lung pharmacokinetics of commonly prescribed drugs by sampling different lung compartments after inhalation and oral administration. Healthy volunteers received single, sequential doses of either inhaled salbutamol, salmeterol and fluticasone propionate (n = 12), or oral salbutamol and propranolol (n = 6). Each participant underwent bronchoscopies and gave breath samples for analysis of particles in exhaled air at two points after drug administration (1 and 6, 2 and 9, 3 and 12, or 4 and 18 h). Lung samples were taken via bronchosorption, bronchial brush, mucosal biopsy and bronchoalveolar lavage during each bronchoscopy. Blood samples were taken during the 24 h after administration. Pharmacokinetic profiles were generated by combining data from multiple individuals, covering all sample timings. Pharmacokinetic profiles were obtained for each drug in lung epithelial lining fluid, lung tissue and plasma. Inhalation of salbutamol resulted in approximately 100-fold higher concentrations in lung than in plasma. Salmeterol and fluticasone concentration ratios in lung versus plasma were higher still. Bronchosorption- and bronchoalveolar-lavage-generated profiles of inhaled drugs in epithelial lining fluid were comparable. For orally administered drugs, epithelial-lining-fluid concentrations were overestimated in bronchoalveolar-lavage-generated profiles. Combining pharmacokinetic data derived from several individuals and techniques sampling different lung compartments enabled generation of pharmacokinetic profiles for evaluation of lung targeting after inhaled and oral drug delivery.