Prosecution Insights
Last updated: April 19, 2026
Application No. 18/044,940

A method for analysing a breath sample for screening, diagnosis or monitoring of SARS-CoV-2 carriage or infection (COVID-19) on humans

Final Rejection §103§112
Filed
Mar 10, 2023
Examiner
ROBERTS, HERBERT K
Art Unit
2855
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Association Hopital Foch
OA Round
2 (Final)
68%
Grant Probability
Favorable
3-4
OA Rounds
2y 9m
To Grant
81%
With Interview

Examiner Intelligence

Grants 68% — above average
68%
Career Allow Rate
348 granted / 509 resolved
At TC average
Moderate +13% lift
Without
With
+12.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
35 currently pending
Career history
544
Total Applications
across all art units

Statute-Specific Performance

§101
1.7%
-38.3% vs TC avg
§103
51.6%
+11.6% vs TC avg
§102
20.1%
-19.9% vs TC avg
§112
21.2%
-18.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 509 resolved cases

Office Action

§103 §112
DETAILED ACTION The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Amendment / Arguments The response, filed 11/18/2025, has been entered. Claims 1-16, 20, and 37 are cancelled. Claims 17-19, 21-36 and 38-40 are pending. All previous objections and 112b rejections are withdrawn due to amendment. Applicant’s arguments have been fully considered and are unpersuasive. On pages 12-13 of the response, applicant argues that specific limitations are not taught by specific references (e.g., Steppert fails to teach mass-to-charge ratio, Trefz fails to teach the at least one range comprising 99.08, Trefz fails to teach identifying the results, etc.). In response, the examiner notes that each pairing (reference and teaching) argued by applicant was not relied on by the examiner (e.g., Trefz was relied on as teaching mass-to-charge ratio). Therefore the examiner finds the aforementioned arguments unpersuasive. It is unclear exactly which limitation applicant is arguing in the second full paragraph of page 12 of the response regarding Trefz. In case applicant is arguing that Trefz fails to teach “determining at least one value of a signal intensity and/or concentration of ions defined by a mass-to-charge ratio (m/z) given by the spectrometer”, the examiner notes that Trefz is explicitly using PTR-ToF-MS which is an acronym for “Proton Transfer Reaction - Time-of-Flight Mass Spectrometer” (or “spectrometry”), which is used for the real-time detection of trace volatile organic compounds (VOCs) in the air. It works by using a "proton transfer reaction" to ionize VOCs and a "time-of-flight" method to measure their mass-to-charge ratio. The examiner cited FIG. 2 of Trefz which explicitly shows (on the Y-axis) the “Masses [Th]”. “Th” is a unit (Thomson) occasionally used in the field of mass spectrometry for the mass-to-charge ratio (m/z). Therefore the examiner finds the aforementioned arguments unpersuasive. On pages 12-13 of the response, applicant argues that Trefz and Hack “predate the discovery of COVID-19 and SARS-CoV-2. For this reason, the skilled person would not have taken the teachings of these documents into account.” In response, the examiner notes that the primary reference Steppert teaches that VOC profiles may be used to diagnose COVID-19 (e.g., page 11 - second to last paragraph). As such, this would lead one of ordinary skill in the art to consider how to characterize VOC profiles. Trefz is directed to the measurement of VOC profiles in exhaled breath. Trefz explicitly recites (abstract) that “[a]nalysis of volatile organic compounds (VOCs) in breath holds great promise for noninvasive diagnostic applications”. Haick is also explicitly directed to diagnosing diseases using breath VOC profiles. As such, it is clear that “the skilled person”, upon considering the disclosure of Steppert, would take previous pre-COVID teaching into account as they relate to diagnosing disease states using breath VOC profiles. Therefore the examiner finds the aforementioned arguments unpersuasive. On pages 13-14 of the response, applicant argues that the particular value of m/z (99.08) recited in claim 17 is of critical importance and that “[o]nly applicant provides this value”. In response, the examiner notes that the limitation in question is “wherein the at least one range comprises m/z = 99.08”. As such, this may be read upon by a reference which teaches a far larger range that has 99.08 within it. Still further, such a value (or even the specific range recited in claim 22) is merely used as an indication of the VOC nonanal using a specific mass spectrometer under a specific set of conditions. Each range recited by applicant appears to be a detection range for a specific VOC using specific equipment under specific conditions. As an example, the specific m/z values (and their associated ranges) of 135.09, 143.15, 99.08 and 111.12 are asserted by applicant as the detection of 1-chloroheptane, nonanal, methylpent-2-enal, and 2,4-octadiene. See the first full paragraph of page 21 of the originally filed specification. Most importantly, the specific m/z of a given VOC (e.g., nonanal) depends on the specific mass spectrometer used since it uses ionization for detection -- does it add a proton? knock off an electron? break the molecule into pieces? Further, using the same ionization source, there is also an impact on the m/z based on the mass analyzer. Still further, a plethora of other factors affect the m/z data obtained (humidity, reagent ion selection, drift tube energy, isotopes, dimer formation, etc.). Applicant selects such a narrow range (e.g., claim 22 where m/z is between 99.04 and 99.14) that the specific m/z of the VOC detected is dependent on all the aforementioned factors. This lends further evidence to the examiner’s assertion that the specific ranges used and claimed by applicant are merely data mining of spectroscopy data to determine specific markers or VOC profiles that differentiate between a particular group and a control / negative group. This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. This, as set forth in the previous and instant claim 17 rejection, is taught by at least Steppert and Haick. Therefore the examiner finds the aforementioned arguments unpersuasive. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(d): (d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers. The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph: Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers. Claim 31 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 31 depends on claim 20 which is cancelled. Applicant may cancel the claim, amend the claim to place the claim in proper dependent form, rewrite the claim in independent form, or present a sufficient showing that the dependent claim complies with the statutory requirements. For the purposes of examination, this claim is interpreted as being dependent upon claim 19. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 17-19, 21-22, 24-36, and 38-40 are rejected under 35 U.S.C. 103 as being unpatentable over Steppert et al. (“Rapid detection of SARS-CoV-2 infection by multicapillary column coupled ion mobilityspectrometry (MCC-IMS) of breath. A proof of concept study”, prior art of record) in view of Trefz et al. (“Continuous Real Time Breath Gas Monitoring in the Clinical Environment by Proton-Transfer-Reaction-Time-of-Flight-Mass Spectrometry”, prior art of record) and Haick et al. (US 20120326092 A1, prior art of record).Regarding claim 17:Steppert teaches a method for analysis, comprising: exposing a sample comprising elements coming from breath exhaled from a person to a spectrometer (title; page 10, paragraphs 3-5); for identifying at least one of the following results: a person carries or is infected by SARS-CoV-2, with or without clinical symptoms, a person does not carry or is not infected by SARS-CoV-2, a person suffers from COVID-19, and/or a person does not suffer from COVID-19 (detecting VOCs / scent fingerprint in a person’s breath using the spectrometer and using that data to determine if a person has SARS-CoV-2; see, e.g., title; first two paragraphs under “Data analysis” on page 5; page 10, paragraphs 3-5; first two paragraphs of page 11; Figure 2)Steppert fails to teach: determining at least one value of a signal intensity and/or concentration of ions defined by a mass-to-charge ratio (m/z) given by the spectrometer in at least one range, the at least one range being defined by a median, a lower limit, and an upper limit, wherein the at least one range comprises m/z = 99.08; applying at least one test to the at least one value, the at least one range and the at least one test being configured for identifying the results; and communicating the at least one result of the at least one test as a messageTrefz teaches: determining at least one value of a signal intensity and/or concentration of ions defined by a mass-to-charge ratio (m/z) given by the spectrometer in at least one range, the at least one range being defined by a median, a lower limit, and an upper limit; applying at least one test to the at least one value, the at least one range and the at least one test being configured for identifying the results (paragraph spanning pages 10322 and 10323; Figure 2; Page 10326; conclusion) Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the PTR MS of Trefz in the method of Steppert as it is an art-recognized equivalent method of breath VOC / VOC “fingerprint” detection. The examiner notes that both Steppert and Trefz essentially teach the use data mining of spectroscopy data to determine specific markers that differentiate between a particular group and a control / negative group. The examiner also relies on Haick teaching such data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see Steppert - first paragraph of page 11. Regarding the limitation of “wherein the at least one range comprises m/z = 99.08”: this is rendered obvious by the above citations and rationale. As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding the claim limitation of “communicating the at least one result of the at least one test as a message”: the examiner takes official notice that it is common and well-known to communicate results via a message. Regarding claim 18:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.As combined in the claim 17 rejection above, Trefz teaches: wherein the spectrometer is a mass spectrometer (paragraph spanning pages 10322 and 10323; Figure 2; Page 10326; conclusion) Regarding claim 19:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the step of determining comprises determining only one value of signal intensity and/or concentration of ions defined by its mass-to-charge ratio (m/z) given by the spectrometer in only one range As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Regarding claim 21:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the step of determining comprises determining values of signal intensities and/or concentrations of ions defined by their mass-to-charge ratios (m/z) given by the spectrometer in a group of ranges As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 22:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the range is m/z median = 99.08; m/z lower limit = 99.04; and m/z upper limit = 99.14 As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 24:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.Steppert fails to teach: wherein the person is undergoing invasive mechanical ventilationTrefz teaches: wherein the person is undergoing invasive mechanical ventilation (e.g., abstract) Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to perform the method on a person undergoing invasive mechanical ventilation to rapidly determine if they have COVID. Further, it is very easy to get regular breath samples from someone who is being mechanically ventilated. Lastly, a person undergoing invasive mechanical ventilation, in the context of respiratory diseases, is already in a critical state. Thus, they should be continuously monitored for progression of the disease. Regarding claim 25:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.Steppert also teaches: wherein the sample is a sample of exhaled breath (e.g., title) Regarding claim 26:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.Steppert also teaches: obtaining the sample via a transfer line in communication with the person (e.g., third line of page 4; also see Trefz - right side of page 10322) Regarding claim 27:Steppert teaches a device for diagnosis, screening or monitoring of SARS-CoV-2 and/or COVID-19, comprising: means for applying at least one test to the at least one value, the at least one range and the at least one test being configured for identifying that: a person carries and/or is infected with SARS-CoV-2, a person does not carry and/or is not infected with SARS-CoV-2, a person suffers from COVID-19, and/or a person does not suffer from COVID-19(detecting VOCs / scent fingerprint in a person’s breath using the spectrometer and using that data to determine if a person has SARS-CoV-2; see, e.g., title; first two paragraphs under “Data analysis” on page 5; page 10, paragraphs 3-5; first two paragraphs of page 11; Figure 2) Steppert fails to teach: means for determining at least one value of a signal intensity and/or concentration of ions defined by a mass-to-charge ratio (m/z) given by a spectrometer in at least one range, the at least one range being defined by a median and limits of the range, and wherein the at least one range comprises m/z = 99.08;Trefz teaches: means for determining at least one value of a signal intensity and/or concentration of ions defined by a mass-to-charge ratio (m/z) given by a spectrometer in at least one range, the at least one range being defined by a median and limits of the range (paragraph spanning pages 10322 and 10323; Figure 2; Page 10326; conclusion) Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the PTR MS of Trefz in the method of Steppert as it is an art-recognized equivalent method of breath VOC / VOC “fingerprint” detection. The examiner notes that both Steppert and Trefz essentially teach the use data mining of spectroscopy data to determine specific markers that differentiate between a particular group and a control / negative group. The examiner also relies on Haick teaching such data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see Steppert - first paragraph of page 11. Regarding the limitation of “wherein the at least one range comprises m/z = 99.08”: this is rendered obvious by the above citations and rationale. As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. Regarding claim 28:Steppert, Trefz, and Haick render obvious all the limitations of claim 27, as mentioned above.Steppert also teaches: a spectrometer (e.g., title; first two paragraphs under “Data analysis” on page 5; page 10, paragraphs 3-5; first two paragraphs of page 11)(also see Trefz - paragraph spanning pages 10322 and 10323; Figure 2; Page 10326; conclusion) Regarding claim 29:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.Steppert, Trefz, and Haick render obvious: a non-transitory computer-readable storage medium having instructions thereon that, when executed by a processor, cause the processor to execute operation for analyzing a sample according to claim 17 Steppert, Trefz, and Haick already teach the method of claim 17. Mere automation of a method is prima facie obvious. E.g., see MPEP 2144.04 III. Regarding claim 30, as best understood (see 112d rejection above):Steppert, Trefz, and Haick render obvious all the limitations of claim 19, as mentioned above.As combined in the claim 17 rejection above, Trefz teaches: wherein the spectrometer is a proton transfer reaction mass spectrometer (paragraph spanning pages 10322 and 10323; Figure 2; Page 10326; conclusion) Regarding claim 31:Steppert, Trefz, and Haick render obvious all the limitations of claim 20, as mentioned above.Steppert also teaches: wherein the method comprises identifying that a person is carrying or is infected by SARS-CoV-2 or that a person is not carrying or is not infected by SARS-CoV-2 (e.g., title; first two paragraphs under “Data analysis” on page 5; page 10, paragraphs 3-5; first two paragraphs of page 11; Figure 2) Regarding claim 32:Steppert, Trefz, and Haick render obvious all the limitations of claim 21, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the group comprises the following ranges: (see list of instant claim 32) As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 33:Steppert, Trefz, and Haick render obvious all the limitations of claim 21, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the group consists of the following ranges: (see list of instant claim 33) As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 34:Steppert, Trefz, and Haick render obvious all the limitations of claim 21, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the group comprises the following ranges: (see list in instant claim 34) As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 35:Steppert, Trefz, and Haick render obvious all the limitations of claim 21, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the group consists of the following ranges: (see list in instant claim 35) As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 36:Steppert, Trefz, and Haick render obvious all the limitations of claim 21, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the group comprises all of the ranges of the following table: (see table in instant claim 36) As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 38:Steppert, Trefz, and Haick render obvious all the limitations of claim 36, as mentioned above.As combined in the claim 17 rejection above, Steppert, Trefz, and Haick render obvious: wherein the group consists of the ranges of the table As set forth in the claim 17 rejection above, Steppert teaches detecting COVID-19 / SARS-CoV-2 by determining a specific spectrometer data “fingerprint” (page 11, first paragraph). Trefz teaches the use of the specific mass spectrometer and using m/z ratios for “VOC profiles” (e.g., FIG. 2). Haick teaches data mining in [0015]-[0019] (as it relates to relying on some specific range or ranges). This is merely taking data from a group known to have a disease/condition, taking data from a group without the disease/condition, and finding what data / VOCs / MS peaks / etc. may be used to differentiate them. Also see last bullet point in the response to arguments section above. As such, the selection of a specific m/z or m/z range is merely the result of the aforementioned data mining and is routine optimization within the conditions of the prior art. Regarding claim 39:Steppert, Trefz, and Haick render obvious all the limitations of claim 24, as mentioned above.Steppert also teaches: obtaining the sample via a transfer line in direct communication with the person (e.g., third line of page 4; also see Trefz - right side of page 10322)Steppert fails to teach: wherein the transfer line is connected to an end of an endotracheal tube installed on the personTrefz teaches: wherein the transfer line is connected to an end of an endotracheal tube installed on the person (e.g., abstract, right side of page 10322. Mechanically ventilated patients, as taught by Trefz, have an endotracheal tube. To sample breath, as set forth in Trefz, the transfer line must be connected to an end of said tube) Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to perform the method on a person undergoing invasive mechanical ventilation (i.e., connecting the transfer line to an endotracheal tube) to rapidly determine if they have COVID. Further, it is very easy to get regular breath samples from someone who is being mechanically ventilated. Lastly, a person undergoing invasive mechanical ventilation, in the context of respiratory diseases, is already in a critical state. Thus they should be continuously monitored for progression of the disease. Regarding claim 40:Steppert, Trefz, and Haick render obvious all the limitations of claim 39, as mentioned above.Steppert fails to teach: heating the transfer lineTrefz teaches: heating the transfer line (last full paragraph of page 10322) Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to heat the transfer tube, as taught by Trefz, in the method of Steppert, to increase accuracy by ensuring all measurements are taken at the same temperature. Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Steppert et al. (“Rapid detection of SARS-CoV-2 infection by multicapillary column coupled ion mobilityspectrometry (MCC-IMS) of breath. A proof of concept study”, prior art of record) in view of Trefz et al. (“Continuous Real Time Breath Gas Monitoring in the Clinical Environment by Proton-Transfer-Reaction-Time-of-Flight-Mass Spectrometry”, prior art of record) and Haick et al. (US 20120326092 A1, prior art of record) and further in view of Trefz et al. (“Effects of elevated oxygen levels on VOC analysis by means of PTR-ToF-MS” - hereafter Trefz2, prior art of record)Regarding claim 23:Steppert, Trefz, and Haick render obvious all the limitations of claim 17, as mentioned above.Steppert fails to teach: comprising taking into account at least one of the following elements: a symptom score, whether the person had a corticosteroid therapy before sampling, and whether the person had oxygenotherapyTrefz2 teaches: comprising taking into account at least one of the following elements: a symptom score, whether the person had a corticosteroid therapy before sampling, and whether the person had oxygenotherapy (e.g., abstract, paragraph spanning pages 1-2) Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take into account whether the person had oxygenotherapy, as taught by Trefz2, in the method of Steppert, Trefz, and Haick, to increase accuracy and/or prevent erroneous results. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Herbert Keith Roberts whose telephone number is (571)270-0428. The examiner can normally be reached 10a - 6p MT. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter Macchiarolo can be reached at (571) 272-2375. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /HERBERT K ROBERTS/Primary Examiner, Art Unit 2855
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Prosecution Timeline

Mar 10, 2023
Application Filed
Aug 15, 2025
Non-Final Rejection — §103, §112
Nov 18, 2025
Response Filed
Nov 25, 2025
Final Rejection — §103, §112
Dec 04, 2025
Applicant Interview (Telephonic)
Dec 04, 2025
Examiner Interview Summary

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
68%
Grant Probability
81%
With Interview (+12.9%)
2y 9m
Median Time to Grant
Moderate
PTA Risk
Based on 509 resolved cases by this examiner. Grant probability derived from career allow rate.

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