Apparatus and method for analyzing gas biomarkers

Abstract

The invention relates to a detection device (10) adapted to analyze the ambient air of a room, comprising a plurality of sensors, and wherein the detection parameters are controlled independently for each sensor. The invention also relates to a system for analyzing data collected by such a device and to a method for detecting and analyzing such data.

Description

Technical Field

[0001] This invention relates to devices and systems for detecting and analyzing gaseous biomarkers. The target devices of this invention particularly allow for the detection of the presence of one or more gaseous biomarkers and the creation of profiles for the detected gaseous biomarkers, as well as the tracking of the evolution of such profiles over time. The invention also relates to a diagnostic method that allows for the non-invasive identification of pathological conditions based on identified biomarkers. This method also allows for the tracking of the evolution of pathological conditions based on identified biomarkers and the corresponding adaptation of treatment. Background Technology

[0002] Various devices allow for the timed measurement of biomarkers emitted by a patient's breath and the determination of their presence at given time intervals. However, these devices require physical contact with the patient, who must typically exhale into a collector for analysis. Furthermore, the biomarkers sought are not detectable uniformly with each exhalation. Their concentrations may even vary significantly over time and may not necessarily be correlated with the patient's physiological state. Timed analysis is therefore susceptible to interpretation errors or requires frequent, potentially mandatory, repetitive measurements.

[0003] Targeted biomarkers can, for example, allow the determination of a patient’s blood glucose levels, as described in document WO2022233771.

[0004] Devices like those described in document EP4244617 allow for continuous monitoring of enclosed spaces, such as offices or classrooms, to identify the presence of potential contaminants. Even when used in hospitals, such devices do not allow for accurate diagnosis and are limited to detecting specific biomarkers.

[0005] Document US2023127176 describes a device including a fan and a gaseous biomarker sensor coupled to a mass spectrometer, allowing the identification of potential contaminants or pathogens that could easily spread epidemics. Monitoring a site does not imply diagnosis or follow-up treatment of patients. The individual identification of gaseous biomarkers does not necessarily allow for an accurate and reliable diagnosis.

[0006] To date, the analysis of gaseous biomarkers has not been fully integrated into the diagnostic and treatment process. There is greater potential for developing gaseous biomarkers for diagnostic, treatment follow-up, and research purposes. Summary of the Invention

[0007] The object of this invention is to provide an improved device and / or system that particularly allows for the continuous tracking of a patient's gaseous biomarker profile over time, preferably without physical contact with the patient. Another object of this invention is to provide a device and / or system that allows for the tracking of the health status of a treated patient and, from there, the determination of the appropriateness of treatment.

[0008] Another object of the present invention is to provide a method for establishing a diagnosis by continuously tracking a patient's gaseous biomarker profile over time, preferably without physical contact with the patient. Another object of the present invention is to provide a method for evaluating a patient's treatment, particularly to avoid inappropriate treatment and to facilitate the most appropriate treatment.

[0009] Another object of the present invention is to provide a system and / or method that allows for easy and remote tracking of the health status of treated patients and assessment of the appropriateness of their treatment. Remote tracking, in particular, allows for more efficient and less expensive outpatient care of patients.

[0010] Another object of the present invention is to provide a system and / or method that allows for limiting the harmful effects of treatments, particularly antibiotics. The aim is to limit bacterial tolerance.

[0011] Another object of the present invention is to provide a system and / or method that allows for the identification of pathological conditions and the selection and / or simulation of diagnostic and treatment methods.

[0012] Another object of the present invention is to provide a target, system and / or method that allows for earlier and / or more accurate detection of pathological conditions compared to currently used methods.

[0013] According to the invention, these objectives are achieved, in particular, by means of devices, systems, and methods that are the subject of the independent claims and detailed in the dependent claims.

[0014] This approach offers several advantages over existing technologies, particularly in the following ways: earlier detection of pathological conditions; and the ability to provide faster, more effective, and more comfortable diagnostic and treatment options. It also allows for minimizing analytical costs for diagnostic purposes. Attached Figure Description

[0015] Examples of implementing the invention are shown in the description illustrated in the following figures: • Figure 1 : A schematic representation of the detection element of a detection device according to an embodiment of the present invention. • Figure 2 : A schematic representation of a detection device according to an embodiment of the present invention. • Figure 3 : A schematic representation of an analysis system according to an embodiment of the present invention. • Figure 4 : A schematic cross-sectional representation of a device according to an embodiment of the present invention. • Figure 5a Measurement of early biomarkers and representation of Escherichia coli growth. • Figure 5b Measurement of early biomarkers and representation of Klebsiella pneumoniae growth. • Figure 5c Measurement of early biomarkers and representation of Pseudomonas aeruginosa growth. • Figure 6 : A representation of the biomarker profiles for Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa according to the present invention. Detailed Implementation

[0016] This invention relates to a detection device 10 for volatile compounds, particularly volatile organic compounds (also known as VOCs). The detection device 10 allows the detection of a wide variety of volatile compounds present in the atmosphere in which it is placed. The detection device 10 can be calibrated to more accurately detect specific volatile compounds. In particular, the detection device 10 can be specifically designed to detect volatile products present indoors (such as residences, hospital rooms, private or public buildings, or any enclosed area). This detection device 10 is particularly adapted to detect volatile products emitted by biological systems within a room (in this case, one or more patients). For this purpose, the detection device 10 is placed near the monitored person and analyzes one or more air samples that may contain organic products emitted by the person present in the room. Typically, the analytical device 10 is in the shape of a housing, with openings on at least one of its sides to allow ambient air to enter the detection element arranged within the housing. In this case, the detection device is not intended to accurately and exclusively collect air exhaled by the patient. Therefore, it lacks the mask or collector typically positioned above the patient's mouth to collect exhaled breath. As a result, the detection device 10 according to the invention collects all volatile compounds present in the room, regardless of their source. This air sample corresponds to an equal aliquot of the atmosphere.

[0017] According to another embodiment, the air sample represents a volume of air exhaled by the patient, extracted from the patient's face, and delivered to the detection device 10. This arrangement can be useful for emergency testing, such as in a pharmacy or when a patient enters a hospital for rapid diagnosis. This arrangement does not preclude the possibility of subsequently establishing monitoring without contact with the patient using the detection device described herein. The same detection device 10 can therefore be used in different configurations.

[0018] According to another embodiment, the detection device 10 described herein can be integrated into a laboratory analytical instrument. For example, cell culture samples can be contained within a dish, and the air in the dish can be sampled and / or analyzed using the detection device 10 described herein. Depending on a specific arrangement, the same detection device 10 can be dedicated to monitoring or analyzing multiple different dishes.

[0019] Furthermore, as long as air can reach the internal detection element, this detection device 10 may not be equipped with a fan to direct air toward the internal detection element. However, specific applications may require such a fan or an equivalent element that allows airflow to be directed toward the internal detection element.

[0020] According to an embodiment, the detection device 10 can be positioned at a predetermined height, such as 80 cm to 1.5 m above a patient's bed. This arrangement is particularly suitable for monitoring bedridden patients, whether in a hospital or at home. Alternatively, the detection device 10 can be placed on furniture in a room at a height adapted for optimal collection of volatile organic compounds. In this case, an intermediate height between the floor and ceiling is preferred to best capture all volatile elements in the room. Such an arrangement is advantageously adapted for monitoring mobile individuals, even if they remain in a given room for an extended period.

[0021] Specifically, volatile organic compounds or gaseous biomarkers can be emitted by any type of living organism and can be detected in a variety of secretory products from patients, including urine, sweat, blood, breath, and any other bodily fluids. Therefore, the detection device described herein can be specifically used for the more particular analysis of any of these secretions.

[0022] According to an embodiment, the detection device 10 can be calibrated to detect only volatile organic compounds emitted by humans and that can be interpreted as biomarkers. Alternatively, it can allow the detection of other volatile or suspended compounds that may be present in the monitored space, such as pollen, chemical or biological contaminants. Detection of volatile or suspended compounds other than potential biomarkers can be subject to specific processing. For example, although they are physically detected or detectable by the detection device 10, the collected data may mask or ignore their presence. Alternatively, data related to volatile or suspended compounds and contaminants can be analyzed jointly or separately with data related to potential biomarkers to provide more accurate analysis.

[0023] According to an embodiment, the detection device 10 allows for the establishment of a profile of volatile compounds present in one or more air samples, whether involving ambient air or air collected from a specific source (such as a cell culture vessel) or a patient's face. The detection device 10 includes at least one, preferably multiple, sensors 10a, 10b, 10c, 10n, which are capable of generating a digital response upon contact with one or more volatile compounds. Depending on the nature of the volatile compounds, the response of a given sensor may vary, particularly in terms of response intensity. The intensity of a sensor's response therefore may not necessarily reflect the quantity or concentration of volatile compounds in the air. Furthermore, the nature of the volatile compounds may not be determined by a given sensor.

[0024] The detection device 10 may therefore not be perfectly suited for directly identifying volatile compounds present in an air sample. In particular, the sensor may not be specific to a given volatile compound. Importantly, in response to the detection of a volatile compound, one or more sensors generate a profile representing the volatile compounds present in the air sample.

[0025] According to an embodiment, the responses of one or more of the sensors 10a, 10b, 10c, 10n of the detection device 10 can be determined by calibrating them with varying concentrations of known volatile compounds and / or under controlled conditions. Alternatively or additionally, known mixtures of the identified volatile compounds can be used to calibrate one or more sensors 10a, 10b, 10c, 10n. The obtained responses produce a profile representing the analyzed mixture.

[0026] Here, the profile specifies, for example, the electrical response from one or more sensors 10a, 10b, 10c, 10n. This can be embodied by measurements of electrical strength, conductance, frequency, magnetic field, wavelength of light, or any suitable physical value. Alternatively, the profile can be embodied or supplemented by variations in one or more of these physical values. Such variations may occur particularly when detection conditions change, whether controlled and intentional or originating from uncontrolled external factors. Typically, temperature or humidity conditions may cause variations in the response of one or more sensors of the detection device 10.

[0027] According to a specific arrangement Figure 1The illustrated detection device 10 according to the invention includes a detection element within its housing. Such a detection element comprises at least one, preferably multiple, different compartments 11a, 11b, 11c, 11n. All compartments are in contact with an air sample. However, they may not be interconnected, such that air passing through a given compartment is not analyzed by other compartments. Alternatively, the compartments or portions of the compartments may be arranged in series, such that a given airflow can pass through multiple compartments. The number of compartments is not limited. Preferably, the detection device 10 comprises two or more compartments, particularly four or multiples of four.

[0028] Each of the compartments 11a, 11b, 11c, and 11n is equipped with at least one sensor 10a, 10b, 10c, or 10n, which is capable of reacting upon contact with at least one volatile organic compound. In other words, the sensor generates a measurable electrical signal upon contact with such a volatile compound. Such a sensor may include, for example, a metal oxide or a metal oxide-type sensor, such as the sensor indicated by the abbreviation MOS (Metal Oxide sensor). Other types of sensors may be used as needed. In this case, a colorimetric sensor may be used instead of or to supplement the MOS-type sensor.

[0029] According to an embodiment, a given compartment includes more than one sensor. The sensors in a given compartment can therefore be identical to produce more reliable measurements. In this case, the responses of the sensors in the compartment can be combined or averaged. Alternatively, the sensors in a given compartment can be of different types, or if they are of the same type (such as MOS or colorimetric), they can be calibrated to produce different responses when contacted with a given volatile compound or a mixture of given components. Thus, within the same compartment, a volatile compound or mixture of volatile compounds can be identified differently by multiple sensors, allowing for more accurate responses, especially with respect to the air components being analyzed.

[0030] Alternatively or additionally, the various compartments 11a, 11b, 11c, 11n of the detection device 10 may be equipped with means for controlling at least one measurement parameter. Measurement parameters include, in particular, temperature, humidity, or pressure. Thus, the value of one or more of these parameters can be determined, allowing the response of one or more corresponding sensors to be modulated accordingly. For example, the sensor's response to a particular volatile compound may vary depending on the value of the measurement parameter. Therefore, it is appropriate to combine, correct, or weight the data obtained by the sensors with the values ​​of the measurement parameters, or some of them.

[0031] Furthermore, controlling the measurement parameters may involve actively and in a controlled manner modifying the values ​​of one or more of the measurement parameters within a given compartment 11a, 11b, 11c, 11n. According to an embodiment, one or more compartments of the detection device include regulating devices for at least one of the measurement parameters. Typically, one or more compartments may include thermal regulating devices 12a, 12b, 12c, 12n, which allow for controlled temperature variations within the corresponding compartments.

[0032] The term "compartment" can refer to a physically separated space within the detection device 10. Alternatively, the compartment can be limited to the detection area equipped with the corresponding sensor. In this case, the measurement parameters can be controlled directly at or near the sensors 10a, 10b, 10c, 10n. For example, one or more of the sensors can be combined with a temperature regulator device so that gases present in the air are detected independently by each sensor at a predetermined temperature.

[0033] According to an embodiment, a set of compartments 11a, 11b, 11c, and 11n form a detection unit U. The detection device 10 may include multiple detection units U1, U2, U3, and Un, each detection unit U1, U2, U3, and Un including multiple compartments, as described above (comparing the compartments). Figure 2 The temperature of each compartment in the detection unit U can be controlled individually.

[0034] According to an embodiment, the detection device 10 includes at least one detection unit U, preferably two or more detection units, which are adapted for static measurements in which the measured parameters do not change. For example, the detection device 10 may include a first detection unit U1, which includes four compartments 11a, 11b, 11c, and 11n, each with a temperature of Ta1, Tb1, Tc1, and Tn1. The temperature values ​​may be fixed and determined between a minimum value Tm1 and a maximum value TM1. The minimum value may be on the order of 80°C or 100°C. The maximum value may be on the order of 200°C, 300°C, 400°C, or higher, as needed. The temperature difference between the compartments of the detection unit U may be an absolute value on the order of tens of degrees (e.g., 15°C, 20°C, 25°C, 30°C, or multiples or combinations of these values). Alternatively, the temperature difference between the compartments of the detection unit U may be determined in a relative manner (e.g., based on a percentage of the temperature of adjacent compartments). Temperature can be, for example, 5%, 10%, or 15% higher or lower than that of an adjacent compartment, or multiples of these values.

[0035] According to the example, the temperatures Ta1, Tb1, Tc1, and Tn1 of the compartments in the first detection unit U1 are 100 °C, 150 °C, 175 °C, and 200 °C, respectively. In this way, air is simultaneously analyzed through the compartments of the first detection unit U1 at different temperatures, and the gases contained therein are detected under different controlled conditions.

[0036] The detection device 10 may include a second measuring unit U2, which comprises four compartments 11a, 11b, 11c, and 11n, each with a temperature of Ta2, Tb2, Tc2, and Tn2, respectively. The temperature values ​​may be fixed and determined between a minimum value Tm2 and a maximum value TM2. The minimum temperature Tm1 and maximum temperature TM2 of the second measuring unit U2 may be the same as or different from the minimum temperature Tm1 and maximum temperature TM2 of the first measuring unit U1. The temperature difference between the compartments of the second measuring unit U2 may be determined in the same or different manner as that of the first measuring unit U1.

[0037] According to the embodiment, the temperature range of the second detection unit U2 is different from that of the first detection unit U1. For example, the minimum temperature Tm2 of the second detection unit U2 can be on the order of 200°C, 220°C, or 250°C. The maximum temperature TM2 of the second detection unit U2 can be on the order of 400°C or higher.

[0038] According to the example, the temperatures Ta2, Tb2, Tc2, and Tn2 of the compartment in the second detection unit U2 are 250°C, 300°C, 350°C, and 400°C, respectively. In this way, the gas is detected by passing through the compartment of the second detection unit U2 at different temperatures and within a temperature range different from that of the first detection unit.

[0039] The first detection unit U1 and the second detection unit U2, as described above, operate in a so-called static mode (i.e., with constant measurement parameters). They are adapted for high or relatively high concentrations of volatile organic compounds.

[0040] The measurement parameter here is limited to temperature. However, other measurement parameters may be considered.

[0041] According to an embodiment, one or more of the detection units U of the detection device 10 are adapted for dynamic measurement, wherein at least one of the measurement parameters changes during the measurement process. For example, the detection device 10 may include a third detection unit U3, which is composed of four compartments 11a, 11b, 11c, 11n, each having a temperature Ta3, Tb3, Tc3, and Tn3 that can vary independently between a minimum and a maximum value. The minimum and maximum values ​​of the compartments in the detection unit U may be the same. In this case, the temperature changes of the individual compartments are performed according to different progressions. Alternatively or further, at least one of the minimum and maximum values ​​differs from one compartment to another within the detection unit.

[0042] According to an embodiment, the temperature change within the compartment can be linear and flat. Alternatively, it can be based on an exponential change. Alternatively, it can be based on jumps with steps of defined duration. The conditions of the temperature change can be adapted as needed. The temperature change is preferably negative. However, it can be positive.

[0043] According to the example, the temperatures of compartments 11a, 11b, 11c and 11n in the third detection unit U3 change from 400°C to 100°C, from 400°C to 150°C, from 400°C to 200°C and from 400°C to 250°C, respectively.

[0044] Dynamic detection mode is advantageous for detecting low concentrations of volatile compounds. Furthermore, it provides better selectivity. The measured conductance relaxes with temperature changes, especially when using MOS-type sensors, for each of the sensors 10a, 10b, 10c, and 10n in the considered compartment.

[0045] Preferably, the temperature change is rapid in order to improve sensitivity. Typically, the temperature change occurs within intervals on the order of one second or a few hundredths of a second.

[0046] According to an embodiment, multiple temperature cycles are repeated for each compartment in the detection unit U. The minimum and maximum values, as well as the temperature change conditions, are reproduced as is for each cycle. Alternatively, the change and one or the other of the minimum and maximum values ​​can be altered from one thermal cycle to another.

[0047] Here, the variable measurement parameter is temperature. However, it is not excluded that other measurement parameters may be considered as alternatives to or supplements to temperature within the framework of dynamic measurement.

[0048] According to an embodiment, the detection unit U of the detection device 10 is used for standard detection of volatile compounds. The purpose of standard detection is to generate a general signal corresponding to volatile compounds present in the atmosphere. Such a general signal on its own is not sufficient to establish a profile of the detected biomarker, but it can be used as a reference in the processing of the collected data.

[0049] Standard tests can be performed under controlled conditions. Alternatively, the measurement conditions correspond to the ambient conditions and there is no need to control the measurement parameters. Under these conditions, air is analyzed at the ambient temperature. Other measurement parameters, such as humidity or pressure, can also be environmental parameters. This arrangement does not preclude determining one or more of the measurement parameters, especially the ambient temperature, at the corresponding detection unit. According to this arrangement, all compartments of the detection unit U have the same measurement parameters. The properties of the sensors 10a, 10b, 10c, and 10n in these compartments can advantageously differ from one compartment to another or be calibrated differently.

[0050] According to an embodiment, the detection device 10 is adapted to detect volatile compounds simultaneously in static and dynamic modes. According to an embodiment, the detection device 10 is adapted to detect volatile compounds simultaneously in static, dynamic, and standard modes. According to an embodiment, the detection device 10 is adapted to detect volatile compounds simultaneously in static and standard modes. According to an embodiment, the detection device 10 is adapted to detect volatile compounds simultaneously in dynamic and standard modes. The combination of modes mentioned herein represents a mixed mode.

[0051] For example, the first detection unit U1, the second detection unit U2, and the third detection unit U3 can be used in dynamic mode, according to which the temperature of each compartment within the detection unit independently changes from a maximum temperature towards a minimum temperature or from a minimum temperature towards a maximum temperature. The temperature range and / or variation conditions can vary from one detection unit to another. The fourth detection unit U4 can be dedicated to the standard measurement of volatile compounds.

[0052] According to another example, the first detection unit U1, the second detection unit U2, and the third detection unit U3 can be used in a dynamic mode, in which the temperature of all compartments in the detection units simultaneously changes from a maximum temperature to a minimum temperature or from a minimum temperature to a maximum temperature. The temperature range and / or the changing conditions can vary from one detection unit to another. The fourth detection unit U4 can be dedicated to the standard measurement of volatile compounds.

[0053] According to another example, the first detection unit U1 and the second detection unit U2 can be used in dynamic mode, in which the temperature of all compartments in the detection units simultaneously changes from a maximum temperature to a minimum temperature or from a minimum temperature to a maximum temperature. The third detection unit U3 is used in static mode as described above. The fourth detection unit U4 can be dedicated to the standard measurement of volatile compounds.

[0054] According to a specific embodiment, an automatic adaptation mode is implemented based on measurement conditions. For example, a static mode can be initiated by default for at least one measurement unit U. If the signal from one or more compartments in the corresponding measurement unit is less than a predetermined value, the detection unit can be manipulated according to a dynamic mode. A dynamic mode can be selected by default, wherein, for example, the temperature of all compartments in one or more detection units changes simultaneously from a maximum temperature to a minimum temperature or from a minimum temperature to a maximum temperature.

[0055] According to the embodiment, the first detection unit U1, the second detection unit U2, and the third detection unit U3 are in static mode by default, and the fourth detection unit U4 is in standard mode. If the signal from one or more of the corresponding compartments is less than the threshold, each of the first detection unit U1, the second detection unit U2, and the third detection unit U3 can independently and automatically switch to dynamic mode.

[0056] The variety of static, dynamic, and hybrid modes (not limited to those actually described herein) allows for great flexibility and measurement accuracy.

[0057] The static mode, dynamic mode, standard mode, and mixed mode are described herein in conjunction with MOS type sensors. This is not intended to limit their application to this type of sensor. According to embodiments, the inhomogeneities of one or more compartments or some of them in the detection unit U may include sensors other than MOS type sensors. For example, colorimetric sensors or other types of sensors may constitute the detection unit. In this case, the measurement conditions can be adapted in a manner similar to that described above.

[0058] Each of sensors 10a, 10b, 10c, and 10n generates a response signal under controlled measurement conditions. The response signals are processed by a compartment and a detection unit to establish a profile representing the air composition in terms of volatile compounds.

[0059] For this purpose, the detection device 10 includes a data processing unit 13 for processing the collected data to create such a profile. Alternatively, the data processing unit 13 can be connected to the detection device 10 for remote data processing.

[0060] The testing device 10 also includes a control unit 14 for each testing unit U1, U2, U3, Un, which in particular allows the testing and / or control of measurement parameters (especially temperature) and the selection of one or more testing modes of the testing unit from static mode, dynamic mode, standard mode, and mixed mode. The control parameters of the control unit 14 can be programmed therein or input therein.

[0061] The detection device according to the invention typically takes the shape of a rigid housing, which includes at least one opening allowing airflow to the detection element. One or more openings may be equipped with dust filters. It may include one or more human-machine interfaces, such as a device for turning the device on and off, a system for inputting or selecting data or preset programs, a display device for displaying at least specific data (such as measurement cycle position or one or more detection parameters), a connection device capable of transmitting data (such as Wi-Fi, Bluetooth, wired, Internet, or any equivalent connection), a power supply system, and / or a battery.

[0062] According to an embodiment, the device includes means for guiding the air to be analyzed toward at least one of the sensors. For example, the detection unit U may include one or more channels 30 adapted to guide one or more airflows F to be analyzed. Figure 4 The channel 30 is connected to at least one detection compartment 11a, 11b, 11c, 11d via passages 31, 31a that allow the sensors 10a, 10b, 10c, 10d in each compartment to contact the air passing through the channel 30. Passages 31, 31a can be dimensionally calibrated to deflect a specific portion of the air flowing through the channel 30. The detection compartments can be shaped like cavities 32, 32a in which sensors 10a are arranged, and the cavities are in fluid communication with the channel 30 via corresponding passages 31. The deflected portion of the airflow F thus contacts the sensors, allowing possible markers contained in the airflow F to be detected. The volume of cavity 32 can also be calibrated to correlate the response of sensor 10a with the volume of cavity 32, 32a. Furthermore, the airflow F in the channel 30 can be precisely controlled, for example, by means of a fan (not shown). The airflow rate directed into the channel 30 is therefore known and can be adjusted as needed.

[0063] According to an embodiment, the responses of sensors 10a, 10b, 10c, and 10d are correlated with the flow rate of airflow F and / or the volume of the compartment cavity to assess or measure the concentration of a marker identified by the sensors. The airflow can be constant and regulated to remain stable. For better measurement, the flow rate of airflow F can be varied, and the values ​​obtained by the sensors can be correlated with these different airflow flow rates. The airflow flow rate can be between 1 L / h and above 10 L / h, typically approximately 2 to 6 or 8 L / h.

[0064] Depending on the possible arrangement, channel 30 can contact multiple detection compartments 11, 11a, 11b, 11c, 11d. The airflow is therefore uniform across a set of detection compartments. Figure 4 The illustration shows such an arrangement. A detector can be positioned on a first surface 40, the temperature of which can be adjusted. A distribution structure 42 can be positioned on or combined with the first surface 40, allowing the definition of a passageway 31 containing cavities and detection compartments in which sensors 10, 10a, 10b, 10c, and 10d are arranged. The distribution structure thus defines the walls of the respective detection compartments within the passageway 30. A second surface 41, arranged opposite the distribution structure 42, defines the dimensions of the passageway 30. The second surface 41 can be positioned at a distance H30 from the distribution structure 42. This distance H30 is typically a few millimeters, for example, between 1 mm and 10 mm, or on the order of 1.5 to 5 mm, or even on the order of 2 to 4 mm or 3 mm. The width of the passageway 30 can be determined to correspond to the width of the compartments. The cross-section of the passageway 30 can therefore be square or rectangular. However, other shapes are conceivable.

[0065] The channel 30 may include an inlet 30a and an outlet 30b that define the path of airflow within the detection unit U, wherein the detection compartment is arranged on the path between the inlet 30a and the outlet 30b.

[0066] According to an embodiment, in addition to or alternative to the outlet 30b of the channel, multiple individual outlets can be provided at each detection compartment. In this way, air passing through each compartment does not return to the airflow or get analyzed by other detection compartments. Overpressure can also be generated, particularly by providing an inlet 30a larger than outlet 30b or larger than any possible individual outlet at the detection compartment. Such overpressure can be beneficial for controlling the concentration of volatile products at the detection compartment.

[0067] According to an embodiment, the channel 30 may include an flared shape at the inlet 30a to concentrate the airflow F at the detection compartment.

[0068] According to another embodiment (not shown), channel 30 can be divided into multiple independent channels, each channel for one or more detection compartments. Therefore, the flow rate in each of the independent channels can be adjusted individually as needed.

[0069] The architecture of the device described above has the advantage of lowering the detection threshold for volatile products. Furthermore, the airflow F is controlled. This arrangement allows for the reliable and reproducible measurement of small amounts of volatile products. The measurement of small amounts of volatile products advantageously allows for early identification of pathological conditions. Therefore, appropriate measures can be taken in advance, allowing for better treatment or adjustments to ongoing treatment.

[0070] The present invention also covers an analysis system 1, which includes one or more detection devices 10 as described herein. Figure 3 The analysis system 1 includes a data analysis unit 20 for analyzing data collected by one or more detection devices 10. The data analysis unit 20 may include an artificial intelligence module 21 or a deep learning module, or any program capable of autonomous learning. The artificial intelligence module, in particular, allows the determination of the presence of at least one gaseous biomarker (preferably multiple gaseous biomarkers emitted by the monitored person) from the profiles received by one or more detection devices 10. It also allows the determination of changes in the concentration of the identified one or more biomarkers over time. Changes in concentration can be determined in an absolute or relative manner with reference to various detected volatile compounds. Changes include decreases, increases, cyclical changes, and relative concentrations of multiple biomarkers.

[0071] The identification of one or more gaseous biomarkers can be obtained, for example, by comparison with one or more pre-established databases that include profiles of gaseous biomarkers and mixtures of such gaseous biomarkers.

[0072] The artificial intelligence module 21 is capable of extracting collected data related to potential contaminants detected by the detection device 10. The contaminant profile can be compared, for example, with profiles in a database. Deconvolution methods or any other methods adapted to identify a specific profile within a stack of profiles can be used.

[0073] According to an embodiment, the artificial intelligence module 21 can identify possible pollutants and, if necessary, changes in their concentration.

[0074] The analysis unit 20 can also be connected to one or more types of environmental sensors C1, C2, Cn, which are different from or integrated into the detection device 10. Such environmental sensors include: ambient temperature sensors; hygrometers; barometers; visible light, UV, or infrared radiation sensors; sound sensors, such as microphones; and presence and / or motion sensors. Non-environmental sensors—especially physiological sensors, such as body temperature sensors, blood pressure sensors, oxygenation sensors, and blood glucose sensors—can also be connected to the data processing unit 20.

[0075] The data processing unit 20 is capable of correcting, weighting, and modifying profiles issued by one or more detection devices 10 based on data collected by environmental sensors and / or non-environmental sensors.

[0076] Alternatively or additionally, the data processing unit 20 includes means for accessing third-party databases D1, D2, and Dn, which include, for example: meteorological data, including forecast data and pollen maps; and air quality or pollution data, including, for example, concentrations of particulate matter, nanoparticles, ozone, carbon dioxide, carbon monoxide, and other gases or elements suspended in the air.

[0077] According to an embodiment, the data processing unit is capable of correcting, weighting, or modifying the profile issued by the detection device 10 based on data collected from one or more of these third-party databases D1, D2, Dn.

[0078] According to an embodiment, the data processing unit 20 is capable of distinguishing volatile compounds originating from pathogens or markers of pathological conditions from volatile compounds not originating from pathogens. In practice, it is possible that healthy individuals may naturally emit specific volatile compounds. In this case, a specific profile associated with a particular volatile compound can allow for differentiation between healthy and pathological states. The nature of the pathogen can also be identified based on the profile of the detected volatile compound.

[0079] According to an embodiment, the data processing unit 20 allows identification of one or more gaseous biomarkers that represent a patient's pathological condition or health status.

[0080] According to an embodiment, the data processing unit 20 allows identification of one or more gaseous biomarkers that represent side effects of treatments in relation to pathological conditions.

[0081] According to an embodiment, the data processing unit 20 is capable of modeling the evolution of a pathological condition or its possible complications based on data collected by one or more detection devices 10.

[0082] The data processing unit 20 includes a processor, memory, and software suitable for processing data according to the methods described below. The data processing unit 20 allows, when necessary, the generation of analysis results R1, R2, Rn automatically or on request, based on profiles received from one or more detection devices 10 and data received from environmental sensors, non-environmental sensors C1, C2, Cn, and third-party databases D1, D2, Dn. The data processing unit 20 includes appropriate algorithms for generating such analysis results.

[0083] The analytical results R1, R2, and Rn include the identification of the pathogen responsible for volatile compounds detected in the environment of one or more patients. The pathogen can be identified at an early stage of infection or pathological condition. Preferably, the pathogen is a respiratory pathogen for which sample extraction for laboratory analysis is difficult or even impossible. However, pathogens of other natures can be detected, such as non-respiratory infection pathogens or pathogens causing organ dysfunction. The identification of such pathogens can be correlated with the monitored person's body temperature, possible cough sounds, and other physiological parameters. For example, a distinction can be made between bacterial and viral pathogens. Such analytical reports can recommend appropriate treatment based on the pathogen identification. Typically, in the case of viral pathogens, antibiotics may not be recommended. For bacterial pathogens, the analytical results may be able to recommend appropriate antibiotics to avoid ineffective use of ineffective antibiotics. Where necessary, the analytical results may include the known tolerance of the pathogen to a particular treatment.

[0084] Alternatively or additionally, analytical reports may allow the identification of volatile compounds that best represent a pathological condition, which must then be monitored most closely. The relevant volatile compounds, or their profiles, are analyzed to allow them to be designated as gaseous biomarkers. Not all detected volatile compounds represent a pathological condition. They may also be emitted in proportions that do not indicate a pathological condition. Therefore, in addition to the diagnostic and treatment follow-up applications described herein, the detection of volatile compounds according to the invention can also be used for research or investigation purposes.

[0085] The analysis results may include parameters that are beneficial or detrimental to the identified pathological condition, for example, based on environmental conditions such as humidity, temperature, or the presence of volatile pollutants.

[0086] The analysis results may include a pathological condition evolution model based on continuous measurements using detection device 10 and, where necessary, data collected by environmental and / or non-environmental sensors C1, C2, Cn and predictive or real-time data from third-party databases.

[0087] The analysis results can include the correlation between the collected and analyzed data and the treatments administered to the patient. The analyzed profiles allow for confirmation of remission of the pathological condition, for example, through a reduction in specific gaseous biomarkers.

[0088] The results of the analysis are not limited to those actually described herein. They can be in the form of written and / or digital reports. Analysis results can also be organized and distributed according to recipients. Analysis results may have multiple recipients, such as attending physicians, researchers, insurers, or the patient themselves. Therefore, some results of a given analysis may be sent only to a specific set of recipients. For example, in the case of home monitoring, analysis results regarding the effectiveness of treatment may be sent to the attending physician.

[0089] According to an embodiment, the analysis results include, for example, a graphical visualization of a summary of the detected volatile products in the form of feature markers. Figure 6 ).

[0090] The present invention also covers a method for detecting one or more volatile biomarkers using at least one detection device (such as detection device 10 described herein). The detection method includes the step of arranging at least one detection device in a room to analyze the air in the room. The room is preferably occupied by one or more people whose health is being monitored.

[0091] The detection method includes steps of autonomously and / or automatically analyzing one or more air samples to identify potential gaseous biomarkers. Analysis can be performed continuously or through successive analysis cycles. Analysis cycles include one or more of the static, dynamic, standard, and mixed modes described above. Analysis of the air samples may include controlling the airflow rate in at least one channel 30 that allows air to be directed toward the detector. Control of the airflow rate F entering channel 30 can be limited to maintaining the flow rate at a constant and reproducible value. Alternatively, the airflow rate F can be varied in a controlled manner, for example, continuously or in steps from a minimum to a maximum value. The sensor's response can therefore be correlated with the value of the airflow rate F to assess or measure the concentration of various volatile compounds in the sample.

[0092] The detection method may include the step of automatically selecting a mode when the obtained response is below a predetermined intensity threshold.

[0093] The detection method may include a step or cycle of cleaning the detection equipment, preferably automatically, when the obtained response is below a predetermined intensity threshold. The cleaning step or cycle may include heating one or more detection elements of the detection equipment to a temperature above 200°C or 300°C, or between 300°C and 400°C, or cyclically changing the temperature to destroy potential contaminants without damaging the detection elements. Cleaning may or may not be associated with an airflow that allows potential contaminants to dissipate. Alternatively or additionally, UV or infrared radiation from one or more detection elements may be envisioned. The cleaning step or cycle may be performed for a period deemed appropriate to restore the sensitivity and / or accuracy of the detection elements. For example, a thermal cycle of one minute or less may be envisioned.

[0094] The detection method includes the step of collecting response signals from the detection device to establish a profile of volatile compounds present in the room at the time of measurement. Signal collection is performed during the detection period and / or according to the detection mode. The detection operation can last for one minute or less. The profile of volatile compounds can be established by means of a data processing unit 13 associated with or integrated into the detection device. The detected profile can be temporarily stored in the memory of the detection device or sent to the analysis unit 20. Alternatively or additionally, the detected profile can be read by a device capable of collecting data stored in the detection device (such as a terminal, telecommunications instrument, or any equivalent).

[0095] The detection method may include multiple detection cycles that are repeated at predetermined intervals or initiated automatically.

[0096] The detection method may include the step of calibrating the detection device according to the volatile compound to be identified. Such calibration may be performed, for example, by measuring a known volatile compound at a certain concentration under controlled conditions and recording the response signal.

[0097] The present invention also covers a method for analyzing data emitted by one or more detection devices using a data analysis unit 20. The analysis method may include: correcting, weighting, and reprocessing the profiles emitted by one or more detection devices using appropriate algorithms with external data (such as data received by environmental or non-environmental sensors C1, C2, Cn or third-party databases D1, D2, Dn).

[0098] The analysis method also includes the step of sending analysis results R1, R2, Rn in response to a specific request or for automatically executed routine analysis. The analysis results can be divided into subgroups, and each subgroup is sent to a different receiver.

[0099] The analytical method described herein may involve multiple testing devices deployed, for example, in multiple rooms of a hospital or in the homes of multiple patients under home monitoring. The collected and then analyzed data may be sent to the attending physician or any other caregiver. The collected data may vary from one patient to another. This analytical method allows, for example, the comparison of data received sequentially by the analysis unit 20 and the determination of their evolution over time. The analysis can therefore allow the detection of patient remission or deterioration, possible synergistic factors influencing the evolution of their pathological condition, possible microbial tolerance, possible hospital-acquired infections, and possible epidemic hotspots. The analytical method allows for modeling the evolution of the pathological condition, the efficacy of treatment, and possible side effects of treatment.

[0100] This analytical method may also include steps for detecting and saving previously unidentified profiles for subsequent analysis.

[0101] For the purposes of this description, volatile organic compounds refer to any volatile compound present in the air in gaseous form. Gas biomarkers refer to volatile organic compounds of metabolic origin. Gas biomarkers may be of fungal, bacterial, or viral origin, or may originate from the cellular activity of a living organism (particularly a patient). Biomarkers are preferably indicators or characteristics of pathological conditions and preferably allow for the identification of pathological conditions. Gas biomarker profiles are preferably used to characterize pathological conditions. Here, pathological condition refers to any abnormal metabolic function that may be related to infection, contamination, inflammation, or dysfunction. Pathological condition may refer to respiratory diseases of viral, bacterial, or other origins. Respiratory diseases may, for example, be tuberculosis, bronchitis, pneumonia, pleurisy, or bronchopneumonia.

[0102] Example Perform in vitro tests to identify various bacteria (including Escherichia coli (ATCC BAA-2471)) isolated based on human respiratory pathology. Figure 5a Klebsiella pneumoniae (ATCC BAA-2472) Figure 5b ), Pseudomonas aeruginosa ( Figure 5c Characteristic markers were used. Bacteria were cultured in vitro in culture medium. Three samples were prepared according to the cultured strain. After inoculating the culture medium with bacteria at a concentration of 100 CFU / mL, continuous measurements of volatile products were performed above the culture medium.

[0103] Cell concentrations were determined through a series of dilutions and counts.

[0104] Experiments showed that volatile products could be detected before bacterial exponential growth. Characteristic profiles of bacteria serving as digital markers were also identified. Figure 6 The culture medium was used as a negative control.

[0105] The time for strain detection by measuring volatile products was: 6 hours for Escherichia coli; 7 hours for Klebsiella pneumoniae; and 11 hours for Pseudomonas aeruginosa.

[0106] Reference numbers used in each figure 1: Analysis system; 10: VOC detection equipment; 10a, 10b, 10c, 10n: Sensors; 11a, 11b, 11c, 11n: Compartments; 12a, 12b, 12c, 12n: Temperature regulators; 13: Data processing unit; 14: Control unit; 20: Data analysis unit; 21: Artificial intelligence module; 30: Channel; 30a: Channel inlet; 30b: Channel outlet; 31, 31a: Pathway; 32: Cavity; 40: The... Surface 1; 41: Second surface; 42: Distribution structure; H30: Distance between distribution structure and upper surface; C1, C2, Cn: Environmental sensor or physiological sensor; D1, D2, Dn: Third-party database; F: Airflow; R1, R2, Rn: Analysis results; U1, U2, U3, Un: Detection unit; Ta1, Tb1, Tc1, Tn1: Compartment temperature; Tm1, Tm2: Minimum temperature value; TM1, TM2: Maximum temperature value.

Claims

1. A detection device (10) adapted for analyzing one or more air samples, comprising: - Multiple sensors (10a, 10b, 10c, 10n) for volatile organic compounds. - A means for determining and / or controlling at least one detection parameter (12a, 12b, 12c, 12n), which is arranged near each of the sensors (10a, 10b, 10c, 10n) or at each of the sensors (10a, 10b, 10c, 10n), and adapted to independently determine or modify the detection conditions of the sensors. - Data processing unit (13), which is capable of collecting signals emitted by sensors in contact with one or more air samples, The device is characterized in that it includes means for guiding air to the sensor to create an airflow (F) and means for determining or controlling the flow rate of the airflow (F), wherein the signal emitted by the sensor is related to the flow rate of the airflow (F) and is processed by the data processing unit (13) to generate a profile of volatile organic compounds.

2. The device of claim 1, wherein the sensors (10a, 10b, 10c, 10n) are arranged in or form detection compartments (11a, 11b, 11c, 11n), each detection compartment comprising one or more sensors of the same or different natures.

3. The device of claim 2, wherein the detection compartments are grouped into one or more detection units (U1, U2, U3, Un), and each detection unit includes multiple detection compartments.

4. The detection device according to any one of claims 1 to 3, wherein the means for guiding air includes at least one channel (30), the at least one channel (30) including an inlet (30a) adapted to allow an airflow (F) to pass through, and the sensor is arranged on a first surface (40) and configured to contact the airflow (F).

5. The device as claimed in any one of claims 1 to 4, wherein the sensor is arranged within a cavity (32) having a defined volume and including a passage (31) in fluid communication with a means for guiding air.

6. The device as claimed in any one of claims 1 to 5, wherein the means for guiding air includes a flared shape adapted to concentrate air at the detector.

7. The device as claimed in any one of claims 1 to 6, wherein the detection parameter is selected from temperature, humidity and pressure, preferably temperature.

8. The device as claimed in any one of claims 1 to 8, wherein the sensor is selected from a MOS type sensor or a colorimetric type sensor.

9. An analytical system (1) for analyzing volatile organic compounds, comprising: - At least one detection device (10) as described in any one of claims 1 to 8. - One or more environmental sensors or non-environmental sensors (C1, C2, Cn). - A device for accessing one or more third-party databases (D1, D2, Dn), and - Analysis Unit (20) The analytical unit (20) is characterized in that it is connected to the at least one detection device, the sensors (C1, C2, Cn) and the third-party database (D1, D2, Dn) to enable the data received by the sensors (C1, C2, Cn) and the third-party database (D1, D2, Dn) to correct, modulate, weight and / or modify the profile of the organic compound sent by the at least one detection device (10).

10. The analysis system (1) of claim 9, wherein the analysis unit (20) includes an artificial intelligence module (21) capable of identifying at least one gaseous biomarker associated with a pathological condition.

11. A method for detecting volatile organic compounds in one or more air samples using a detection device as described in any one of claims 1 to 8, comprising the following steps: - Sensors (10a, 10b, 10c, 10n) used for volatile organic compounds come into contact with one or more air samples. The detection parameters at each sensor are independently determined and / or controlled, including one or more parameters among temperature, humidity, and pressure. - The sensor's response signal is acquired and processed by the data processing unit (13), and - A brief overview of sensor-based signal generation of volatile organic compounds. The feature is that one or more air samples are brought into contact with the sensor by means of an airflow (F) whose flow rate is determined and / or controlled.

12. The method of claim 11, wherein the sensors are grouped in a plurality of detection units (U1, U2, U3), and the acquisition of the sensor response signal is performed independently for each of the detection units according to one of a static mode, a dynamic mode, a standard mode, and a hybrid mode.

13. The method of claim 12, wherein the static mode is defined by constant detection parameters that are different for each sensor in a given detection unit, the dynamic mode is defined by detection parameters that are independently variable for each detector in a given detection unit, the standard mode is defined by detection parameters that correspond to the ambient conditions for all detectors in a given detection unit, and the hybrid mode combines multiple of the static mode, dynamic mode, and standard mode in multiple detection units.

14. The method of claim 13, wherein the detection parameter is temperature, the temperature being determined between a minimum temperature and a maximum temperature for each sensor of the detection unit in a static mode, the temperature varying independently between a minimum temperature and a maximum temperature for each sensor of the detection unit in a dynamic mode, and the temperature being the ambient temperature for all sensors of the detection unit in a standard mode.

15. The detection method according to any one of claims 11 to 14, further comprising the step of: automatically cleaning at least one of the sensors when the corresponding signal is less than a predetermined intensity threshold.

16. The method of one of claims 12 to 15, further comprising: When the response signal of one or more sensors in the detection unit is less than a predetermined intensity threshold, one of the detection modes is automatically selected.

17. An analytical method for analyzing volatile organic compounds using the analytical system as described in any one of claims 9 and 10, comprising: - The profiles of volatile organic compounds received by the analysis unit (20) are compared with profiles in a pre-established database, which includes profiles of gaseous biomarkers. - Gaseous biomarkers that identify substances present in volatile organic compounds. - Determine the concentration of at least one of the identified biomarkers, and - Analytical results (R1, R2, Rn) are generated based on the identified gaseous biomarkers.

18. The analytical method of claim 17, further comprising one or more of the following steps: - Characterizing pathological conditions based on identified gaseous biomarkers, - Compare gaseous biomarkers over time and determine their evolution. - Correlating the evolution of biomarkers with treatments administered as a means of treating pathological conditions and / or possible infections and / or possible environmental conditions. - Differentiate between viral and bacterial origins based on the identified pathological conditions. - Identify potential treatment-related side effects or possible tolerability. - Modeling the evolution of the identified pathological conditions, and - Key biomarkers that identify a given pathological condition.

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