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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3 February 2026 has been entered.
Response to Arguments
Applicant's arguments filed 3 February 2026 have been fully considered but they are not persuasive.
Applicant argues that Family does not disclose “a predicted response for patient suitability for the service”. However, Family discloses that the methods therein “enable a practitioner to determine whether a subject is likely to benefit from a psychedelic treatment and act accordingly” (paragraph [0141]). Determining whether a subject is likely to benefit from a treatment (service) is equivalent to determining their suitability for the treatment (service). Additionally, Family specifically discloses language analysis is utilized to determine a patient response metric, such as an adverse response (paragraph [0091]). A patient with an adverse response to a service would be considered unsuitable for the service.
Applicant’s remaining arguments simply reiterate that the prior art does not teach “for patient suitability for”. For the same reasons as presented above, those arguments are unpersuasive.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 4-7, 10-12, 14 and 17-19 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Family et al. (U.S. Patent Application Pub. No. 2023/0162851, hereinafter “Family”).
In regard to claim 1, Family discloses a computer-implemented method for use in treating a health condition (in a treatment setting, paragraph [0063]), comprising:
obtaining an audio file that captures one or more interactions between one or more providers and a patient of a service (language analysis begins with the input of an audio sample comprising an audio file, paragraph [0093]; captured from conversations between a patient and a provider, paragraph [0071]);
generating a transcript of at least a portion of the one or more interactions captured in the audio file (a transcript is generated from the audio file, paragraph [0093]);
inferring, using machine learning, a plurality of analytics based, at least in part, upon content contained in the transcript (based on the language in the transcribed sample, characteristics of the language are derived, paragraphs [0094] and [0102]);
determining one or more biomarkers for the patient based, at least in part, upon the plurality of analytics (the language characteristics are correlated with biomarkers such as hypomania, psychosis, etc., paragraphs [0094-0095]);
generating a predicted response for patient suitability for the service to provide for display based, at least in part, upon the one or more biomarkers and the plurality of analytics (a patient response metric is determined according to the language characteristics and biomarkers, paragraphs [0103-0106]; the patient response metric indicating whether the patient has an adverse response to, and is therefore unsuitable for, the treatment, paragraph [0091]; and the patient response provided to a monitor for viewing, paragraphs [0036-0037]; allowing a practitioner to determine whether a subject is likely to benefit from psychedelic treatment, paragraph [0141]); and
administering psilocybin to the patient at least one of before, during, and after the one or more interactions as treatment for the health condition (patients are administered psilocybin for treatment, paragraph [0133]).
In regard to claim 4, Family discloses:
analyzing one or more utterances present in the transcript (words in the transcript are analyzed, paragraph [0076]);
generating one or more tags associated with the one or more utterances (clustering models group characteristics into categories, paragraph [0102]); and
inferring the plurality of analytics based, at least in part, upon the generated tags (clustered characteristics are additional characteristics used for further processing, paragraph [0102] and paragraphs [0094-0095]).
In regard to claim 5, Family discloses the one or more biomarkers are determined based, at least in part, upon at least one of: detected sentiment, a detected pitch, a detected frequency, determined words per minute, detected pauses, and a duration of pauses in the audio file (psychosis, hypomania, etc. is further determined based on pitch, paragraph [0097]; frequency (MFCC’s), paragraph [0098]; pauses and length of pauses, paragraph [0088]).
In regard to claim 6, Family discloses assigning one or more tags to the audio file based, at least in part, upon audio cues detected in the audio file (characteristics of the audio file including acoustic features are clustered to group the characteristics into categories, paragraphs [0097-0098] and [0102]).
In regard to claim 7, Family discloses a system for use in treating a health condition (in a treatment setting, paragraph [0063]), comprising:
at least one processor (paragraph [0110]); and
at least one memory (paragraph [0110]) storing instructions that, when executed by the at least one processor, cause the at least one processor to:
obtain a media file that captures one or more interactions between one or more providers and a patient of a service (language analysis begins with the input of an audio sample comprising an audio file, paragraph [0093]; captured from conversations between a patient and a provider, paragraph [0071]);
generate a transcript of at least a portion of the one or more interactions captured in the media file (a transcript is generated from the audio file, paragraph [0093]);
infer, using machine learning, a plurality of analytics based, at least in part, upon content contained in the transcript (based on the language in the transcribed sample, characteristics of the language are derived, paragraphs [0094] and [0102]);
determine one or more biomarkers for the patient based, at least in part, upon the plurality of analytics (the language characteristics are correlated with biomarkers such as hypomania, psychosis, etc., paragraphs [0094-0095]);
generate a predicted response for patient suitability for the service to provide for display based, at least in part, upon the one or more biomarkers and the plurality of analytics (a patient response metric is determined according to the language characteristics and biomarkers, paragraphs [0103-0106]; the patient response metric indicating whether the patient has an adverse response to, and is therefore unsuitable for, the treatment, paragraph [0091]; and the patient response provided to a monitor for viewing, paragraphs [0036-0037]; allowing a practitioner to determine whether a subject is likely to benefit from psychedelic treatment, paragraph [0141]); and
administer psilocybin to the patient at least one of before, during, and after the one or more interactions as treatment for the health condition (patients are administered psilocybin for treatment, paragraph [0133]).
In regard to claim 10, Family discloses the instructions that, when executed by the at least one processor, cause the at least one processor to further:
analyze one or more utterances present in the transcript (words in the transcript are analyzed, paragraph [0076]);
generate one or more tags associated with the one or more utterances (clustering models group characteristics into categories, paragraph [0102]); and
infer the plurality of analytics based, at least in part, upon the generated tags (clustered characteristics are additional characteristics used for further processing, paragraph [0102] and paragraphs [0094-0095]).
In regard to claim 11, Family discloses the one or more biomarkers are determined based, at least in part, upon at least one of: detected sentiment, a detected pitch, a detected frequency, determined words per minute, detected pauses, and a duration of pauses in the media file (psychosis, hypomania, etc. is further determined based on pitch, paragraph [0097]; frequency (MFCC’s), paragraph [0098]; pauses and length of pauses, paragraph [0088]).
In regard to claim 12, Family discloses the instructions that, when executed by the at least one processor, cause the at least one processor to further:
assign one or more labels to the media file based, at least in part, upon audio or visual cues detected in the audio file (characteristics of the audio file including acoustic features are clustered to group the characteristics into categories, paragraphs [0097-0098] and [0102]).
In regard to claim 14, Family discloses a non-transitory computer-readable medium (paragraph [0110]), storing instructions that, when executed by at least one processor, cause the at least one processor to:
obtain a media file that captures one or more interactions between one or more providers and a patient of a service (language analysis begins with the input of an audio sample comprising an audio file, paragraph [0093]; captured from conversations between a patient and a provider, paragraph [0071]);
generate a transcript of at least a portion of the one or more interactions captured in the media file (a transcript is generated from the audio file, paragraph [0093]);
infer, using machine learning, a plurality of analytics based, at least in part, upon content contained in the transcript (based on the language in the transcribed sample, characteristics of the language are derived, paragraphs [0094] and [0102]);
determine one or more biomarkers for the patient based, at least in part, upon the plurality of analytics (the language characteristics are correlated with biomarkers such as hypomania, psychosis, etc., paragraphs [0094-0095]);
generate a predicted response for patient suitability for the service to provide for display based, at least in part, upon the one or more biomarkers and the plurality of analytics (a patient response metric is determined according to the language characteristics and biomarkers, paragraphs [0103-0106]; the patient response metric indicating whether the patient has an adverse response to, and is therefore unsuitable for, the treatment, paragraph [0091]; and the patient response provided to a monitor for viewing, paragraphs [0036-0037]; allowing a practitioner to determine whether a subject is likely to benefit from psychedelic treatment, paragraph [0141]); and
administer psilocybin to the patient at least one of before, during, and after the one or more interactions as treatment for the health condition (patients are administered psilocybin for treatment, paragraph [0133]).
In regard to claim 17, Family discloses the instructions that, when executed by the at least one processor, cause the at least one processor to further:
analyze one or more utterances present in the transcript (words in the transcript are analyzed, paragraph [0076]);
generate one or more tags associated with the one or more utterances (clustering models group characteristics into categories, paragraph [0102]); and
infer the plurality of analytics based, at least in part, upon the generated tags (clustered characteristics are additional characteristics used for further processing, paragraph [0102] and paragraphs [0094-0095]).
In regard to claim 18, Family discloses the one or more biomarkers are determined based, at least in part, upon at least one of: detected sentiment, a detected pitch, a detected frequency, determined words per minute, detected pauses, and a duration of pauses in the media file (psychosis, hypomania, etc. is further determined based on pitch, paragraph [0097]; frequency (MFCC’s), paragraph [0098]; pauses and length of pauses, paragraph [0088]).
In regard to claim 19, Family discloses the instructions that, when executed by the at least one processor, cause the at least one processor to further:
assign one or more labels to the media file based, at least in part, upon audio or visual cues detected in the audio file (characteristics of the audio file including acoustic features are clustered to group the characteristics into categories, paragraphs [0097-0098] and [0102]).
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, 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.
Claim(s) 2-3, 8-9 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Family, in view of Peters et al. (U.S. Patent Application Pub. No. 2007/0299664, hereinafter “Peters”).
In regard to claim 2, Family does not expressly disclose the recording is transcribed using NLP.
Peters discloses a method of transcribing a recording wherein the recording is transcribed using Natural Language Processing (NLP) (speech is transcribed using automatic speech recognition and natural language processing, paragraph [0051]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use NLP when transcribing the recording, because, as is widely recognized in the art, NLP increases transcription accuracy by modeling most likely sequences of words.
In regard to claim 3, Family does not disclose correcting errors.
Peters discloses a method of transcribing a recording comprising:
detecting that the transcript contains an error (erroneous text is detected, paragraph [0051]);
providing an indication of the error (the user is provided an indication of the error, paragraph [0040]); and
suggesting one or more corrections to the error (rules to correct the error are suggested to the user, paragraph [0043]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect errors in the transcript and suggest one or more corrections, because it would indicate to the user how to eliminate those errors in future applications, as taught by Peters (paragraph [0043]).
In regard to claim 8, Family does not disclose correcting errors.
Peters discloses instructions that, when executed by the at least one processor, cause the at least one processor to further:
detect that the transcript contains an error (erroneous text is detected, paragraph [0051]);
provide an indication of the error (the user is provided an indication of the error, paragraph [0040]); and
suggest one or more corrections to the error (rules to correct the error are suggested to the user, paragraph [0043]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect errors in the transcript and suggest one or more corrections, because it would indicate to the user how to eliminate those errors in future applications, as taught by Peters (paragraph [0043]).
In regard to claim 9, Family does not expressly disclose the recording is transcribed using NLP.
Peters discloses a method of transcribing a recording wherein the recording is transcribed using Natural Language Processing (NLP) (speech is transcribed using automatic speech recognition and natural language processing, paragraph [0051]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use NLP when transcribing the recording, because, as is widely recognized in the art, NLP increases transcription accuracy by modeling most likely sequences of words.
In regard to claim 15, Family does not disclose correcting errors.
Peters discloses instructions that, when executed by the at least one processor, cause the at least one processor to further:
detect that the transcript contains an error (erroneous text is detected, paragraph [0051]);
provide an indication of the error (the user is provided an indication of the error, paragraph [0040]); and
suggest one or more corrections to the error (rules to correct the error are suggested to the user, paragraph [0043]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect errors in the transcript and suggest one or more corrections, because it would indicate to the user how to eliminate those errors in future applications, as taught by Peters (paragraph [0043]).
In regard to claim 16, Family does not expressly disclose the recording is transcribed using NLP.
Peters discloses a method of transcribing a recording wherein the recording is transcribed using Natural Language Processing (NLP) (speech is transcribed using automatic speech recognition and natural language processing, paragraph [0051]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use NLP when transcribing the recording, because, as is widely recognized in the art, NLP increases transcription accuracy by modeling most likely sequences of words.
Claim(s) 13 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Family, in view of Lucas et al. (U.S. Patent Application Pub. No. 2002/0143533, hereinafter “Lucas”).
In regard to claims 13 and 20, Family does not disclose the media file is pre-processed prior to transcription to filter out unwanted noise from the media file.
Lucas discloses a system for transcribing voice from a media file, wherein the media file is pre-processed prior to transcription to filter out unwanted noise from the media file (an audio file is processed to remove noise prior to transcription, paragraph [0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to pre-process the media file prior to transcription to filter out unwanted noise from the media file, because, as is widely recognized in the art, removing noise would increase the accuracy of the transcription.
Conclusion
All claims are identical to or patentably indistinct from, or have unity of invention with claims in the application prior to the entry of the submission under 37 CFR 1.114 (that is, restriction (including a lack of unity of invention) would not be proper) and all claims could have been finally rejected on the grounds and art of record in the next Office action if they had been entered in the application prior to entry under 37 CFR 1.114. Accordingly, THIS ACTION IS MADE FINAL even though it is a first action after the filing of a request for continued examination and the submission under 37 CFR 1.114. See MPEP § 706.07(b). 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 BRIAN LOUIS ALBERTALLI whose telephone number is (571)272-7616. The examiner can normally be reached M-F 8AM-3PM, 4PM-5PM.
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BLA 2/18/26
/BRIAN L ALBERTALLI/Primary Examiner, Art Unit 2656