DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claim 11 is objected to because of the following informality:
Claim 11, line 12: “a respiratory” should be replaced with –the respiratory–
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
No limitations were interpreted under 35 U.S.C. 112(f).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 13-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 13 recites “a pharmaceutically acceptable salt, solvate or hydrate thereof (PF-07304814)” in lines 58-59 and “a solvate or hydrate thereof (PF-07321332)” in line 61. First, it is unclear if the parentheticals are part of the claimed invention or not. Parentheticals are used for reference numerals (which are not part of the claimed invention) and in equations (which are part of the claimed invention). The parentheticals of claim 13 fall into neither of these categories such that it is not clear how the parentheticals should be interpreted. Additionally, it is unclear whether the drugs within the parentheticals are merely examples or further limit the claim. Claim 14-16 recite parentheticals which are unclear for similar reasons, so claims 14-16 are rejected on similar grounds. The Examiner suggests deleting the parentheticals.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-13 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-20 do not include additional elements that integrate the exception into a practical application of the exception or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, p. 50, January 7, 2019), and the 2024 Guidance Update on Patent Subject Matter Eligibility (Federal Register, Vol. 89, No. 137 p. 58128, July 17, 2024).
The analysis of claim 7 is as follows:
Step 1: Claim 7 is directed to a machine, which is a statutory category.
Step 2A - Prong 1: Claim 7 is directed to an abstract idea in the form of a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components.
In particular, claim 7 recites the following limitations:
[A1]: generating a baseline data value using the collected at least one audio sample;
[B1]: processing the second audio sample using the generated baseline data value;
[C1]: determining the human subject’s respiratory condition.
These elements [A1]-[C1] of claim 7 are directed to an abstract idea because they are processes that, under their broadest reasonable interpretation, are mere steps that are capable of being mentally performed with the aid of pen and paper. For example, a skilled artisan is capable of analyzing audio samples to determine a baseline data value, analyzing a second audio sample in relation to the baseline data value to obtain further data, and analyzing the audio data to determine a human subject’s respiratory condition.
Step 2A - Prong Two: Claim 7 does not recite additional elements that integrate the judicial exception into a practical application. Claim 1 recites the following additional elements:
[A2]: one or more processors;
[B2]: a computer memory having computer-executable instructions stored thereon for performing operations when executed by one or more processors;
[C2]: collecting at least one audio sample from the human subject;
[D2]: collecting a second audio sample from the human subject;
[E2]: constructing a machine learning classifier using the processed second audio sample; and
[F2]: using the constructed machine learning classifier.
The elements [A2]-[F2] do not integrate the exception into a practical application of the exception.
The elements [A2] and [B2] do not integrate the exception into a practical application of the exception because the elements amount to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f).
The elements [C2] and [D2] do not integrate the exception into a practical application of the exception because the elements amount to adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering at a higher level of generality in conjunction with the abstract idea that uses conventional, routine, and well known elements - see MPEP 2106.04(d); MPEP 2106.05(g).
The elements [E2] and [F2] do not integrate the exception into a practical application of the exception because the elements amount to (A) merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea - see MPEP 2106.04(d); MPEP § 2106.05(f); or (B) generally linking the use of a judicial exception to a particular technological environment or field of use - see MPEP 2106.04(d); MPEP § 2106.05(h).
Accordingly, each of the additional elements do not integrate the abstract into a practical application because they do not impose any meaningful limitations on practicing the abstract idea.
Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. Claim 1 recites the following additional elements:
[A2]: one or more processors;
[B2]: a computer memory having computer-executable instructions stored thereon for performing operations when executed by one or more processors;
[C2]: collecting at least one audio sample from the human subject;
[D2]: collecting a second audio sample from the human subject;
[E2]: constructing a machine learning classifier using the processed second audio sample; and
[F2]: using the constructed machine learning classifier.
The elements [A2]-[B2] do not amount to significantly more than the judicial exception itself.
Simply reciting the elements [A2]-[B2] do not qualify as significantly more because these elements are simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (See MPEP 2106.05(d)(II); Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (See MPEP 2106.05(d)(II); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93).
The elements [C2] and [D2] do not qualify as significantly more because these elements amount to adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering at a higher level of generality in conjunction with the abstract idea that uses conventional, routine, and well known elements - see MPEP 2106.05(g). Additionally, the elements are well-understood, routine, and conventional, as evidenced by US 5,757,939 A (Begeja) which indicates that conventional manner for recording an audio sample includes using a digital audio tape recorder (Col. 3, lines 41-65).
The elements [E2] and [F2] do not qualify as significantly more because the elements amount to (A) merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea - See MPEP § 2106.05(f); or (B) generally linking the use of a judicial exception to a particular technological environment or field of use - see MPEP § 2106.05(h). Additionally, the elements are well-understood, routine, and conventional, as evidenced by US 2023/0326598 A1 (Sommer) which discloses that algorithms based on artificial intelligence (AI) are well-known and promising candidates for automated support of medical imaging and diagnosis, and that such AI algorithms must first be trained using training data (¶ [0003]).
In view of the above, the additional elements individually do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Independent claims 1 and 11 recite mirrored method limitations and are not patent eligible for substantially similar reasons.
Independent claim 11 further recites “if the human is positive for a respiratory illness, administering a therapeutically effective amount of a compound or a pharmaceutically acceptable salt of said compound to treat the human respiratory illness”, but this limitation does not integrate the exception into a practical application of the exception or qualify as significantly more because the element amounts to (A) merely reciting the words “apply it” (or an equivalent) with the judicial exception - see MPEP 2106.04(d); MPEP 2106.05(f) or (B) generally linking the use of a judicial exception to a particular technological environment or field of use - see MPEP 2106.04(d); MPEP § 2106.05(h). Additionally, the treatment is not particular because it covers any and all treatments using a compound or a salt of said compound. See MPEP 2106.04(d)(2)(a). Also the limitation is conditional and so if the human is not positive then no treatment is being applied.
Claims 2-6 depend from claim 1, and they recite the same abstract idea as claim 1. Claims 8-10 depend from claim 7, and they recite the same abstract idea as claim 7. Claims 12-20 depend from claim 11, and they recite the same abstract idea as claim 11. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the mental process) and/or append abstract ideas (that is, the claims only recite limitations that add further mental processes) except for the following limitations.
Claim 2 recites “collecting at least three audio samples from the human subject”. However the above element does not integrate the exception into a practical application of the exception or qualify as significantly more because the element amount to merely adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering at a higher level of generality in conjunction with the abstract idea that uses conventional, routine, and well known elements - see MPEP 2106.04(d); MPEP 2106.05(g). Additionally, the element is well-understood, routine, and conventional, as is evidenced by US 5,757,939 A (Begeja) which indicates that conventional manner for recording an audio sample includes using a digital audio tape recorder (Col. 3, lines 41-65). Indicating that at least three audio samples are collected merely indicates that additional samples are acquired and used, which does not amount to a practical application or significantly more. Claims 8 and 17 recite similar elements that do not integrate the exception into a practical application of the exception or qualify as significantly more for similar reasons.
Claim 13 recites “compound is selected from a group consisting of…” However, the above element does not integrate the exception into a practical application of the exception or qualify as significantly more because the element amounts to because the element amounts to (A) merely reciting the words “apply it” (or an equivalent) with the judicial exception - see MPEP 2106.04(d); MPEP 2106.05(f) or (B) generally linking the use of a judicial exception to a particular technological environment or field of use - see MPEP 2106.04(d); MPEP § 2106.05(h). Additionally, the treatment is not particular because it covers many compounds for treating COVID-19, some of which have only a nominal or insignificant relationship to treating COVID-19. See MPEP 2106.04(d)(2)(a-c).
In view of the above, the additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claims 14-16 include the administration of particular compounds, salts, solvates, or hydrates that amount to a particular treatment or prophylaxis. Therefore, claims 14-16 are not rejected under 35 U.S.C. §101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 7-8, 11, 17, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over US 2022/0061694 A1 (Ayu) in view of US 2022/0223293 A1 (Steinberg-Koch).
With regards to claims 1 and 7, Ayu teaches a method of screening a human subject for a respiratory illness (¶¶ [0006]-[0008] discloses systems and a method executed by the system for determining if a patient is afflicted with a respiratory illness, disease, and/or condition), and a computerized system for monitoring a respiratory condition of a human subject (¶ [0007] discloses a computerized system), the system comprising one or more processors (¶ [0007] discloses one or more processors); and a computer memory having computer-executable instructions stored thereon for performing operations when executed by the one or more processors (¶ [0007] discloses computer-executable instructions stored in a memory), the operations and the method comprising: collecting at least one audio sample from the human subject (¶ [0038] depicts a microphone 206 collecting and recording one or more vocal utterances, breathing samples, audio events, and/or other utterances produced by the patient 202; ¶ [0040] discloses a collation of historical patient audio samples associated with the patient 202); generating a baseline data value using the collected at least one audio sample (¶¶ [0039]-[0040] discloses determining, from the audio data collected within the medical environment 208, one or more audio characteristics from the audio data; ¶ [0040] discloses utilizing the collation of historical patient audio characteristics to compare and/or match the audio characteristics of the audio sample with the patient audio samples of the collation of historical patient audio characteristics and historical data); collecting a second audio sample from the human subject (¶ [0040] discloses that the collation of historical patient audio samples includes a large number of historical audio samples and historical audio characteristics obtained from the patient 202, which necessarily includes at least one second audio sample); constructing a machine learning classifier (¶¶ [0052]-[0053] discloses a patient status component 226 which can determine a current health status of the patient 202 through comparative and matching analysis between the audio data and the previous audio data associated with the patient health statuses, wherein the patient status component 226 can be configured to utilize machine learning algorithms and/or neural network technique to form categories of audio characteristic values that are associated with various respiratory illnesses and/or respiratory conditions, which indicates that the machine learning classifier was trained on the historical data); and using the constructed machine learning classifier to determine the human subject's respiratory condition (¶ [0053] discloses determining the current health status using the machine learning algorithm).
Ayu is silent regarding processing the second audio sample using the generated baseline data value and constructing a machine learning classifier using the processed second audio sample.
In the same field of endeavor of generating models for diagnosing a patient, Steinberg-Koch teaches processing new subject data using a generated baseline data value (¶ [0163] discloses creating training vectors on historic data and correct diagnosis tagging; ¶ [0164] discloses entering new subject data and feature embedding which includes, converting a long vector of input features into a smaller embedding vector which result in training vectors in which patients with similar conditions have similar vectors; See Fig. 6 and ¶ [0176] with regards to how the new subject data is processed using the baseline data) and constructing a machine learning classifier using the processed new subject data (¶ [0165] discloses training the artificial intelligence model using the tagged training vectors). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ayu to incorporate, based on the teachings of Steinberg-Koch, processing the second audio sample using the generated baseline data value and constructing a machine learning classifier using the processed second audio sample. The motivation would have been to provide a more accurate encapsulation of the patient data (see ¶ [0042] of Steinberg-Koch), which would result in a more accurate machine learning classifier.
With regards to claims 2 and 8, the above combination teaches or suggests the step of collecting at least one audio sample comprises collecting at least three audio samples from the human subject (¶ [0040] of Ayu discloses the collation of historical patient audio samples may include a large number of historical audio samples and historical audio characteristics obtained from the patient).
With regards to claims 3 and 9, the above combination teaches or suggests the step of generating the baseline data value comprises generating at least one spectrogram for each of the three collected audio samples (¶ [0044] of Ayu discloses the audio data including a spectrograph).
With regards to claims 11, Ayu teaches a method for treating a respiratory illness in a human in need of such treatment (¶¶ [0006]-[0008] discloses systems and a method executed by the system for determining if a patient is afflicted with a respiratory illness, disease, and/or condition; ¶¶ [0022], [0049] discloses using the device to provide treatment for a respiratory illness) the method comprising: collecting at least one audio sample from the human subject (¶ [0038] depicts a microphone 206 collecting and recording one or more vocal utterances, breathing samples, audio events, and/or other utterances produced by the patient 202; ¶ [0040] discloses a collation of historical patient audio samples associated with the patient 202); generating a baseline data value using the collected at least one audio sample (¶¶ [0039]-[0040] discloses determining, from the audio data collected within the medical environment 208, one or more audio characteristics from the audio data; ¶ [0040] discloses utilizing the collation of historical patient audio characteristics to compare and/or match the audio characteristics of the audio sample with the patient audio samples of the collation of historical patient audio characteristics and historical data); collecting a second audio sample from the human subject (¶ [0040] discloses that the collation of historical patient audio samples includes a large number of historical audio samples and historical audio characteristics obtained from the patient 202, which necessarily includes at least one second audio sample); constructing a machine learning classifier (¶¶ [0052]-[0053] discloses a patient status component 226 which can determine a current health status of the patient 202 through comparative and matching analysis between the audio data and the previous audio data associated with the patient health statuses, wherein the patient status component 226 can be configured to utilize machine learning algorithms and/or neural network technique to form categories of audio characteristic values that are associated with various respiratory illnesses and/or respiratory conditions, which indicates that the machine learning classifier was trained on the historical data); using the constructed machine learning classifier to determine the human subject's respiratory condition (¶ [0053] discloses determining the current health status using the machine learning algorithm), and if the human is positive for a respiratory illness, administering a therapeutically effective amount of a compound or a pharmaceutically acceptable salt of said compound to treat the human respiratory illness (¶ [0022] discloses the medical device 106 being used to provide treatment for a respiratory illness, wherein the medical device includes a drug delivery device).
Ayu is silent regarding processing the second audio sample using the generated baseline data value and constructing a machine learning classifier using the processed second audio sample.
In the same field of endeavor of generating models for diagnosing a patient, Steinberg-Koch teaches processing new subject data using a generated baseline data value (¶ [0163] discloses creating training vectors on historic data and correct diagnosis tagging; ¶ [0164] discloses entering new subject data and feature embedding which includes, converting a long vector of input features into a smaller embedding vector which result in training vectors in which patients with similar conditions have similar vectors; See Fig. 6 and ¶ [0176] with regards to how the new subject data is processed using the baseline data) and constructing a machine learning classifier using the processed new subject data (¶ [0165] discloses training the artificial intelligence model using the tagged training vectors). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ayu to incorporate, based on the teachings of Steinberg-Koch, processing the second audio sample using the generated baseline data value and constructing a machine learning classifier using the processed second audio sample. The motivation would have been to provide a more accurate encapsulation of the patient data (see ¶ [0042] of Steinberg-Koch), which would result in a more accurate machine learning classifier.
With regards to claim 17, the above combination teaches or suggests the step of collecting at least one audio sample comprises collecting at least three audio samples from the human subject (¶ [0040] of Ayu discloses the collation of historical patient audio samples may include a large number of historical audio samples and historical audio characteristics obtained from the patient).
With regards to claim 18, the above combination teaches or suggests the step of generating the baseline data value comprises generating at least one spectrogram for each of the three collected audio samples (¶ [0044] of Ayu discloses the audio data including a spectrograph).
Claims 4-6, 9-10, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Ayu in view of Steinberg-Koch, as applied to respective claims 3, 8, and 18 above, and further in view of US 2024/0273361 A1 (Jacob Banville).
With regards to claims 4-5, 9-10, and 19-20, the above combination is silent regarding whether the step of generating the baseline data value comprises determining covariance values of each of the three collected audio samples.
In a system relevant to the problem of constructing a machine learning classifier using audio signals, Jacob Banville teaches acquiring audio signals (¶¶ [0203], [0208] discloses receiving audio-signal data and analyzing the data) and determining covariance values of data of a channel (¶ [0297] discloses generating a covariance matrix of the data in the process of generating the training data) and projecting the covariance values from a Riemannian space to a Tangent space (¶ [0297] discloses projecting the covariance matrices into their Riemannian tangent space). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the step of generating the baseline data value and constructing the machine learning classifier of the above combination to incorporate, based on the teachings of Jacob Banville, determining covariance values of each of the three collected audio samples and projecting the covariance values from a Riemannian space to a Tangent space. The motivation would have been to improve the accuracy of the machine learning classifier. Additionally or alternatively, because both the methods of manipulating the features of Ayu in view of Steinberg-Koch and Jacob Banville are suitable for being used in the generation of a classifier, it would have been the simple substitution of one known equivalent element for another to obtain predictable results.
With regards to claim 6, the above combination is silent regarding whether the step of generating the baseline data value comprises generating an average value of the covariance values of the three collected audio samples projected in the Tangent space.
In a system relevant to the problem of constructing a machine learning classifier using audio signals, Jacob Banville teaches generating an average value of the covariance values (¶ [0182] discloses averaging covariance matrices). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the generation of the baseline data value of the above combination to incorporate, based on the teachings of Jacob Banville, generating an average value of the covariance values of the three collected audio samples projected in the Tangent space. The motivation would have been to improve the classification approach (¶ [0182] of Jacob Banville).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Ayu in view of Steinberg-Koch, as applied to claim 11 above, and further in view of US 2020/0380957 A1 (Edwards).
With regards to claim 12, the above combination is silent with regards to whether the respiratory illness comprises coronavirus disease 2019 (COVID-19).
In the same field of endeavor of machine learning systems for determining voice attributes, Edwards teaches a voice attributes machine learning system for determining a medical condition including a respiratory illness comprising coronavirus disease 2019 (COVID-19) (¶ [0036] discloses detecting a wide variety of attributes based on vocal analysis, including medical conditions such as respiratory illnesses (e.g., COVID-19). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the above combination to incorporate that coronavirus disease 2019 (COVID-19) is detected as taught by Edwards. The motivation would have been to improve the diagnostic capabilities of the system.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Ayu in view of Steinberg-Koch and Edwards, as applied to claim 12 above, and further in view of US 2021/0308224 A1 (Shevy).
With regards to claim 13, the above combination is silent regarding whether the compound is selected from a group consisting of: a PLpro inhibitor, Apilomod, EIDD-2801, Ribavirin, Valganciclovir, p-Thymidine, Aspartame, Oxprenolol, Doxycycline, Acetophenazine, lopromide, Riboflavin,Reproterol, 2,2'-Cyclocytidine, Chloramphenicol, Chlorphenesin carbamate, Levodropropizine, Cefamandole, Floxuridine, Tigecycline, Pemetrexed, L(+)-Ascorbic acid, Glutathione, Hesperetin, Ademetionine, Masoprocol, Isotretinoin, Dantrolene, Sulfasalazine Anti-bacterial, Silybin, Nicardipine, Sildenafil, Platycodin, Chrysin, Neohesperidin, Baicalin, Sugetriol-3,9-diacetate, (-)-Epigallocatechin gallate, Phaitanthrin D, 2-(3,4-Dihydroxyphenyl)-2-[[2-(3,4-dihydroxyphenyl)-3,4-dihydro-5,7- dihydroxy-2H-1-benzopyran-3-yl]oxy]-3,4-dihydro-2H-1-benzopyran-3,4,5,7-tetrol, 2,2- di(3-indolyl)-3-indolone, (S)-(1 S,2R,4aS,5R,8aS)-1-Formamido-1,4a-dimethyl-6- methylene-5-((E)-2-(2-oxo-2,5-dihydrofuran-3-yl)ethenyl)decahydronaphthalen-2-yl-2- amino-3-phenylpropanoate, Piceatannol, Rosmarinic acid, and Magnolol; a 3CLpro inhibitor, Lymecycline, Chlorhexidine, Alfuzosin, Cilastatin, Famotidine, Almitrine, Progabide, Nepafenac, Carvedilol, Amprenavir, Tigecycline, Montelukast, Carminic acid, Mimosine, Flavin, Lutein, Cefpiramide, Phenethicillin, Candoxatril, Nicardipine, Estradiol valerate, Pioglitazone, Conivaptan, Telmisartan, Doxycycline, Oxytetracycline, (1 S,2R,4aS,5R,8aS)-1-Formamido-1,4a-dimethyl-6-methylene-5-((E)-2-(2-oxo-2,5- dihydrofuran-3-yl)ethenyl)decahydronaphthalen-2-yl5-((R)-1,2-dithiolan-3-yl) pentanoate, Betulonal, Chrysin-7-0-p-glucuronide, Andrographiside, (1 S,2R,4aS,5R,8aS)-1-Formamido-1,4a-dimethyl-6-methylene-5-((E)-2-(2-oxo-2,5- dihydrofuran-3-yl)ethenyl)decahydronaphthalen-2-yl 2-nitrobenzoate, 23-Hydroxy-3,4- seco-friedelolactone-27-oic acid (S)-(1 S,2R,4aS,5R,8aS)-1-Formamido-1,4a-dimethyl-6- methylene-5-((E)-2-(2-oxo-2,5-dihydrofuran-3-yl)ethenyl) decahydronaphthalen-2-yl-2- amino-3-phenylpropanoate, Isodecortinol, Cerevisterol, Hesperidin, Neohesperidin, Andrograpanin, 2-((1 R,5R,6R,8aS)-6-Hydroxy-5-(hydroxymethyl)-5,8a-dimethyl-2- methylenedecahydronaphthalen-1-yl)ethyl benzoate, Cosmosiin, Cleistocaltone A, 2,2- Di(3-indolyl)-3-indolone, Biorobin, Gnidicin, Phyllaemblinol, Theaflavin 3,3'-di-O-gallate, Rosmarinic acid, Kouitchenside I, Oleanolic acid, Stigmast-5-en-3-ol, Deacetylcentapicrin, and Berchemol; an RdRp inhibitor, Valganciclovir, Chlorhexidine, Ceftibuten, Fenoterol, Fludarabine, Itraconazole, Cefuroxime, Atovaquone, Chenodeoxycholic acid, Cromolyn, Pancuronium bromide, Cortisone, Tibolone, Novobiocin, Silybin, Idarubicin Bromocriptine, Diphenoxylate, Benzylpenicilloyl G, Dabigatran etexilate, Betulonal, Gnidicin, 2p,30s-Dihydroxy-3,4-seco-friedelolactone-27- lactone, 14-Deoxy-11,12-didehydroandrographolide, Gniditrin, Theaflavin 3,3'-di-0- gallate, (R)-((1R,5aS,6R,9aS)-1,5a-Dimethyl-7-methylene-3-oxo-6-((E)-2-(2-oxo-2,5- dihydrofuran-3-yl)ethenyl)decahydro-1 H-benzo[c]azepin-1-yl)methyl2-amino-3- phenylpropanoate, 2p-Hydroxy-3,4-seco-friedelolactone-27-oic acid, 2-(3,4- Dihydroxyphenyl)-2-[[2-(3,4-dihydroxyphenyl)-3,4-dihydro-5,7-dihydroxy-2H-1- benzopyran-3-yl]oxy]-3,4-dihydro-2H-1-benzopyran-3,4,5,7-tetrol, Phyllaemblicin B, 14- hydroxycyperotundone, Andrographiside, 2-((1 R,5R,6R,8aS)-6-Hydroxy-5- (hydroxymethyl)-5,8a-dimethyl-2-methylenedecahydro naphthalen-1-yl)ethyl benzoate, Andrographolide, Sugetriol-3,9-diacetate, Baicalin, (1S,2R,4aS,5R,8aS)-1-Formamido- 1,4a-dimethyl-6-methylene-5-((E)-2-(2-oxo-2,5-dihydrofuran-3- yl)ethenyl)decahydronaphthalen-2-yl 5-((R)-1,2-dithiolan-3-yl)pentanoate, 1,7- Dihydroxy-3-methoxyxanthone, 1,2,6-Trimethoxy-8-[(6-0-3-D-xylopyranosyl-p-D- glucopyranosyl)oxy]-9H-xanthen-9-one, and/or 1,8-Dihydroxy-6-methoxy-2-[(6-0-3-D- xylopyranosyl-p-D-glucopyranosyl)oxy]-9H-xanthen-9-one, 8-(p-D-Glucopyranosyloxy)- 1,3,5-trihydroxy-9H-xanthen-9-one; Diosmin, Hesperidin, MK-3207, Venetoclax, Dihydroergocristine, Bolazine, R428, Ditercalinium, Etoposide, Teniposide, UK-432097, Irinotecan, Lumacaftor, Velpatasvir, Eluxadoline, Ledipasvir, a combination of Lopinavir/Ritonavir and Ribavirin, Alferon, and prednisone; dexamethasone, azithromycin, remdesivir, boceprevir, umifenovir and favipiravir; an a-ketoamides compound; an RIG 1 pathway activator; a protease inhibitor; and remdesivir, galidesivir, favilavir/avifavir, molnupiravir (MK-4482/EIDD 2801), AT-527, AT-301, BLD-2660, favipiravir, camostat, SLV213 emtrictabine/tenofivir, clevudine, dalcetrapib, boceprevir, ABX464, (3S)-3-({N-[(4-methoxy-1 H-indol-2-yl)carbonyl]-L-leucyl}amino)-2-oxo-4-[(3S)- 2-oxopyrrolidin-3-yl]butyl dihydrogen phosphate; and a pharmaceutically acceptable salt, solvate or hydrate thereof (PF-07304814), (1 R,2S,5S)-N-{(1 S)-1-Cyano-2-[(3S)-2- oxopyrrolidin-3-yl]ethyl}-6,6-dimethyl-3-[3-methyl-N-(trifluoroacetyl)-L-valyl]-3- azabicyclo[3.1.0]hexane-2-carboxamide or a solvate or hydrate thereof (PF-07321332), S-217622, glucocorticoids, convalescent plasma, a recombinant human plasma, monoclonal antibody, ravulizumab, VIR-7831/VIR-7832, BRII-196/BRIl-198, COVI- AMG/COVI DROPS (STI-2020), bamlanivimab (LY-CoV555), mavrilimab, leronlimab (PRO140), AZD7442, lenzilumab, infliximab, adalimumab, JS 016, STI-1499 (COVIGUARD), Ianadelumab (Takhzyro), canakinumab (Ilaris), gimsilumab, otilimab, antibody cocktail, recombinant fusion protein, anticoagulant, IL-6 receptor agonist, PIKfyve inhibitor, RIPK1 inhibitor, VIP receptor agonist, SGLT2 inhibitor, TYK inhibitor, kinase inhibitor, bemcentinib, acalabrutinib, losmapimod, baricitinib, tofacitinib, H2 blocker, anthelmintic, and a furin inhibitor.
In a system relevant to the problem of treating COVID-19, Shevy teaches treating COVID-19 with ribavirin (¶ [0049] discloses treating COVID-19 using anti-Hepatic C (Ribavirin)). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the compound of the above combination to incorporate that it is ribavirin, as taught by Shevy. The motivation would have been to substitute one known equivalent element for treating the respiratory illness with another to obtain predictable results.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Ayu in view of Steinberg-Koch and Edwards, as applied to claim 12 above, and further in view of US 2021/0322351 A1 (Groppel).
With regards to claim 14, the above combination is silent regarding whether the compound is (3S)-3-({N-[(4-methoxy-1 H-indol-2-yl)carbonyl]-L-leucyl}amino)-2-oxo-4-[(3S)- 2-oxopyrrolidin-3-yl]butyl dihydrogen phosphate, or a pharmaceutically acceptable salt, solvate, or hydrate thereof (PF-07304814).
In a system relevant to the problem of treating COVID-19, Groppel teaches administering PF-037304814 (¶ [0118] discloses a compound including PF-07304814). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the above compound of the above combination to incorporate the drug including PF-07304814 as taught by Groppel. The motivation would have been to provide a more effective treatment of the respiratory illness.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Ayu in view of Steinberg-Koch and Edwards, as applied to claim 12 above, and further in view of US 2022/0323396 A1 (Chawla).
With regards to claim 15, the above combination is silent regarding whether the compound is (1R,2S,5S)-N-{(1S)-1-Cyano-2-[(3S)-2-oxopyrrolidin-3-yl]ethyl}-6,6-dimethyl-3-[3-methyl-N-(trifluoroacetyl)-L-valyl]-3-azabicyclo[3.1.0]hexane-2-carboxamide or a solvate or hydrate thereof (PF-07321332, Nirmatrelvir).
In a system relevant to the problem of treating COVID-19, Chawla teaches administering Nirmatrelvir (¶ [0023] discloses an antiviral agent including nirmatrelvir). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the above compound of the above combination to incorporate the drug including Nirmatrelvir as taught by Chawla. The motivation would have been to provide a more effective treatment of the respiratory illness.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Ayu in view of Steinberg-Koch and Edwards, as applied to claim 12 above, and further in view of 2022/0177469 A1 (Klopp).
With regards to claim 16, the above combination is silent regarding whether the compound is nirmatrelvir or a pharmaceutically acceptable salt, solvate or hydrate thereof and ritonavir or a pharmaceutically acceptable salt, solvate or hydrate thereof (PaxlovidTM)
In a system relevant to the problem of treating COVID-19, Klopp teaches administering compound of nirmatrelvir or a pharmaceutically acceptable salt, solvate or hydrate thereof and ritonavir or a pharmaceutically acceptable salt, solvate or hydrate thereof (PaxlovidTM) (¶ [0003] discloses the antiviral drug Paxlovid (Nirmatrelvir plus ritonavir)). It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the above compound of the above combination to incorporate Paxlovid as taught by Klopp. The motivation would have been to provide a more effective treatment of the respiratory illness.
Conclusion
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/S.C.K./Examiner, Art Unit 3791
/JACQUELINE CHENG/Supervisory Patent Examiner, Art Unit 3791
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