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 .
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.
Status of Claims
Claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 are currently pending. Claims 3-4, 6-7, 10, 16, 21-22, 26 and 28 have been canceled. Claims 1, 2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 have been amended.
Response to Arguments
Applicant cites supports and various parts of the specification and drawings for support of the amended claims. Applicant cites on page 13 that results of a SQL queries inherently converts the retrieved data into a “normalized, vectorized eligibility representation.” Examiner disagrees. SQL queries do not inherently convert data into normalized, vectorized values. Normalization and vectorization are separate concepts with distinct purposes, typically associated with different types of database systems. SQL queries are a tool for interacting with data that is already stored in a specific format within a relational database. Therefore, it is not “inherent” as argued.
Next, Applicant cites on pages 13-15, paragraphs 84, 114 and 115 and Table 1 for support of steps B and C in the amended claims as below. After further review, there is no mention of the terms “patient eligibility index”, “digital eligibility criteria profile”, and “eligibility mask” in any of these paragraphs cited or others. These terms are not described, defined or found in the originally filed specification.
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Next, Applicant cites on page 15, paragraphs 136-143 and Table 4 for support of steps D and E in the amended claims. After further review, there is no mention of the term “longitudinal eligibility trajectory” in any of these paragraphs cited or others. This term is not described, defined or found in the originally filed specification.
Next, Applicant cites paragraphs 86-87 and steps #4 and#5 for support of step F in the amended claims as seen below. After further review, there is no mention of “storing the computed predicted enrollment metrics and corresponding probability values in the trajectory datastore in association with the corresponding site identifiers for automated provisioning to a clinical trial management system wherein the retrieval, vectorized similarity computation, and storage in the trajectory datastore are performed using data obtained from a plurality of clinical trial sites, and the stored predicted enrollment metrics are thereby usable to generate site-specific clinical trial enrollment predictions.” Paragraphs 86-87 and Figure 2, Steps 4 and 5 have nothing to do with storing data of any kind in a trajectory datastore. Rather these citations have more to do with making predications and sharing the results.
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Applicant argues on pages 16-17 that claims 19 and 24 have been amended to overcome 112(b) rejection. Examiner agrees, however a new 112(b) rejection as seen below will be presented for claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30.
Applicant argues on pages 17-18 that the amended claims overcome the 101 rejection because amended claims are “directed to a specific, technological process for generating site-specific predicted enrollment metrics for a clinical trial from distributed EMR/EHR data.” Examiner disagrees. The data structures recited are generic and conventional, serving as mere containers or organizational frameworks for data without imparting a technological improvement beyond the abstract idea. The processing steps, including data retrieval, generating, normalization, and probabilistic modeling, are well-known mathematical concepts applied on generic computer components. The claims do not recite any improvement to the functioning of the computer itself or any unconventional computer components, but instead use generic computer technology to implement the abstract idea. See MPEP 2106.05(f). Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983.
Applicant’s arguments on pages 18-20, with respect to 103 rejection have been fully considered and are persuasive. The 103 rejection of claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 has been withdrawn.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 29 and 30 recite trajectory datastore, eligibility data schema, patient eligibility index, digital eligibility criteria profile, eligibility mask, longitudinal eligibility trajectory, predicted enrollment metric and probabilistic modeling engine. These terms are not described, defined or found in the originally filed specification. In addition, the limitations seen below including the bolded terms as seen in claims 1, 29 and 30 have no support in the originally filed specification:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, a plurality of time- stamped clinical values for each respective patient in a plurality of patients associated with a first set of one or more clinical trial sites, wherein retrieval comprises:
(i) executing a set of structured query language (SQL) queries that apply an eligibility data schema to identify only those data fields corresponding to a set of eligibility criteria for the clinical trial,
(ii) converting the retrieved clinical values into a normalized, vectorized eligibility representation, and
(iii) storing the normalized, vectorized eligibility representation in a patient eligibility index
B) for each of a plurality of discrete epochs in a first time period, processing the patient eligibility index using a vectorized similarity computation between each patient's eligibility representation and a digital eligibility criteria profile to generate, for that epoch, a machine- readable eligibility mask identifying eligible patients, thereby generating a sequence of eligibility masks for the plurality of epochs;
C) generating a longitudinal eligibility trajectory by storing the sequence of eligibility masks for the plurality of epochs in a trajectory datastore indexed by site and patient identifier;
D) for each site in the first set, generating, from the longitudinal eligibility trajectory, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal eligibility trajectory:
E) for each site-specific enrollment dataset, processing the dataset, by a probabilistic modeling engine configured to combine the candidate enrollment counts with their corresponding probability values, to produce a site-specific predicted enrollment metric for the second time period; and
F) storing the computed predicted enrollment metrics and corresponding probability values in the trajectory datastore in association with the corresponding site identifiers for automated provisioning to a clinical trial management system wherein the retrieval, vectorized similarity computation, and storage in the trajectory datastore are performed using data obtained from a plurality of clinical trial sites, and the stored predicted enrollment metrics are thereby usable to generate site-specific clinical trial enrollment predictions.
Claim 15 recites longitudinal eligibility trajectory. This term is not described, defined or found in the originally filed specification.
Claims 12, 14, 15, 17, 19, 20, and 23-25 recite predicted enrollment metric. This term is not described, defined or found in the originally filed specification.
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.
Claims 11-13, 17-20, 23-24, and 25 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 11 recites “wherein the A) retrieving of claim 1 further comprises,…” It is unclear and ambiguous as to what is meant by wherein the A). For examining purposes, Examiner will assume it is step A) that is being referenced. Applicant it advised to amend claim to recite “wherein step A) of claim 1 further comprises…” Appropriate correction is required.
Claim 12 recites “applied in the retrieving A) of claim 1.” It is unclear and ambiguous as to what is meant by retrieving A). For examining purposes, Examiner will assume it is step A) that is being referenced. Applicant it advised to amend claim to recite “applied in step A) of claim 1.” Appropriate correction is required.
Claim 13 recites “applied in the retrieving A) of claim 1.” It is unclear and ambiguous as to what is meant by retrieving A). For examining purposes, Examiner will assume it is step A) that is being referenced. Applicant it advised to amend claim to recite “applied in step A) of claim 1.” Appropriate correction is required.
Claim 17 recites “corresponding enrollment count from D) as a measure…” It is unclear and ambiguous as to what is meant by enrollment count from D). For examining purposes, Examiner will assume it is step D) that is being referenced. Applicant it advised to amend claim to recite “corresponding enrollment count of step D) as a measure…” Appropriate correction is required.
Claims 19 and 24 recites “repeating through E) of claim 1” It is unclear and ambiguous as to what is meant by repeating through E). For examining purposes, Examiner will assume it is step E) that is being referenced. Applicant it advised to amend claim to recite “repeating step E) of claim 1…” or “repeating steps A) -E) of claim 1…” Appropriate correction is required.
Claims 18, 20, 23, and 25 rejected to as being dependent upon a rejected base claim.
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 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
In the instant case, claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, and 27 are directed to methods (i.e. processes), while claim 29 is directed to a system (i.e. a machine) and claim 30 is directed to a non-transitory computer-readable medium (i.e. a manufacture). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A- Prong 1
Independent claims 1, 29, and 30 recite steps that, under their broadest reasonable interpretations, cover Mental Processes, e.g. concepts performed in the human mind (including an observation, evaluation, judgement, opinion). Specifically, claim 1 recites:
A computer-implemented method for generating site-specific clinical trial enrollment predictions of a clinical trial, the method comprising:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, a plurality of time- stamped clinical values for each respective patient in a plurality of patients associated with a first set of one or more clinical trial sites, wherein retrieval comprises:
(i) executing a set of structured query language (SQL) queries that apply an eligibility data schema to identify only those data fields corresponding to a set of eligibility criteria for the clinical trial,
(ii) converting the retrieved clinical values into a normalized, vectorized eligibility representation, and
(iii) storing the normalized, vectorized eligibility representation in a patient eligibility index
B) for each of a plurality of discrete epochs in a first time period, processing the patient eligibility index using a vectorized similarity computation between each patient's eligibility representation and a digital eligibility criteria profile to generate, for that epoch, a machine- readable eligibility mask identifying eligible patients, thereby generating a sequence of eligibility masks for the plurality of epochs;
C) generating a longitudinal eligibility trajectory by storing the sequence of eligibility masks for the plurality of epochs in a trajectory datastore indexed by site and patient identifier;
D) for each site in the first set, generating, from the longitudinal eligibility trajectory, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal eligibility trajectory:
E) for each site-specific enrollment dataset, processing the dataset, by a probabilistic modeling engine configured to combine the candidate enrollment counts with their corresponding probability values, to produce a site-specific predicted enrollment metric for the second time period; and
F) storing the computed predicted enrollment metrics and corresponding probability values in the trajectory datastore in association with the corresponding site identifiers for automated provisioning to a clinical trial management system wherein the retrieval, vectorized similarity computation, and storage in the trajectory datastore are performed using data obtained from a plurality of clinical trial sites, and the stored predicted enrollment metrics are thereby usable to generate site-specific clinical trial enrollment predictions.
Similarly, claim 29 recites:
A computer system comprising:
one or more processors; and
a non-transitory computer-readable medium including computer-executable instructions that, when executed by the one or more processors, cause the processors to perform a method for generating site-specific clinical trial enrollment predications for a clinical trial, the method comprising:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, a plurality of time- stamped clinical values for each respective patient in a plurality of patients associated with a first set of one or more clinical trial sites, wherein retrieval comprises:
(i) executing a set of structured query language (SQL) queries that apply an eligibility data schema to identify only those data fields corresponding to a set of eligibility criteria for the clinical trial,
(ii) converting the retrieved clinical values into a normalized, vectorized eligibility representation, and
(iii) storing the normalized, vectorized eligibility representation in a patient eligibility index
B) for each of a plurality of discrete epochs in a first time period, processing the patient eligibility index using a vectorized similarity computation between each patient's eligibility representation and a digital eligibility criteria profile to generate, for that epoch, a machine- readable eligibility mask identifying eligible patients, thereby generating a sequence of eligibility masks for the plurality of epochs;
C) generating a longitudinal eligibility trajectory by storing the sequence of eligibility masks for the plurality of epochs in a trajectory datastore indexed by site and patient identifier;
D) for each site in the first set, generating, from the longitudinal eligibility trajectory, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal eligibility trajectory:
E) for each site-specific enrollment dataset, processing the dataset, by a probabilistic modeling engine configured to combine the candidate enrollment counts with their corresponding probability values, to produce a site-specific predicted enrollment metric for the second time period; and
F) storing the computed predicted enrollment metrics and corresponding probability values in the trajectory datastore in association with the corresponding site identifiers for automated provisioning to a clinical trial management system wherein the retrieval, vectorized similarity computation, and storage in the trajectory datastore are performed using data obtained from a plurality of clinical trial sites, and the stored predicted enrollment metrics are thereby usable to generate site-specific clinical trial enrollment predictions.
Similarly, claim 30 recites:
a non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to perform a method for generating site-specific clinical trial enrollment predications for a clinical trial, the method comprising:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, a plurality of time- stamped clinical values for each respective patient in a plurality of patients associated with a first set of one or more clinical trial sites, wherein retrieval comprises:
(i) executing a set of structured query language (SQL) queries that apply an eligibility data schema to identify only those data fields corresponding to a set of eligibility criteria for the clinical trial,
(ii) converting the retrieved clinical values into a normalized, vectorized eligibility representation, and
(iii) storing the normalized, vectorized eligibility representation in a patient eligibility index
B) for each of a plurality of discrete epochs in a first time period, processing the patient eligibility index using a vectorized similarity computation between each patient's eligibility representation and a digital eligibility criteria profile to generate, for that epoch, a machine- readable eligibility mask identifying eligible patients, thereby generating a sequence of eligibility masks for the plurality of epochs;
C) generating a longitudinal eligibility trajectory by storing the sequence of eligibility masks for the plurality of epochs in a trajectory datastore indexed by site and patient identifier;
D) for each site in the first set, generating, from the longitudinal eligibility trajectory, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal eligibility trajectory:
E) for each site-specific enrollment dataset, processing the dataset, by a probabilistic modeling engine configured to combine the candidate enrollment counts with their corresponding probability values, to produce a site-specific predicted enrollment metric for the second time period; and
F) storing the computed predicted enrollment metrics and corresponding probability values in the trajectory datastore in association with the corresponding site identifiers for automated provisioning to a clinical trial management system wherein the retrieval, vectorized similarity computation, and storage in the trajectory datastore are performed using data obtained from a plurality of clinical trial sites, and the stored predicted enrollment metrics are thereby usable to generate site-specific clinical trial enrollment predictions.
These above limitations, under their broadest reasonable interpretation, cover performance of the limitation as mental processes. The claim recites elements, italicized above, which covers performance of the limitation that can be concepts performed in the mind of a person, with pen and paper (e.g., a person with pen and paper can draw graphs and make determinations from it) or using a generic computer (see MPEP 2106.04(a)(2) Ill C) to perform a judicial exception has been shown to be abstract.
Dependent claims 2, 5, 8-9, 11-15, 17-20, 23-25, and 27 inherit the limitations that recite an abstract idea from their dependence on claims 1, 29, or 30, respectively, and thus these claims also recite an abstract idea under the Step 2A — Prong 1 analysis. In addition, claims 2, 5, 8-9, 11-15, 17-20, 23-25, and 27 recite additional limitations that further describe and limit the abstract idea identified in the independent claims. Examiner notes that claims 12, 13, 17 and 18 are also abstract as reciting a mathematical concept (mathematical relationships and/or calculations). See MPEP 2106.04(a)(2).
Claim 2 recites wherein determining the longitudinal trajectory comprises, for a respective patient in the first plurality of patient records: determining by natural language processing the corresponding plurality of time-stamped clinical values that is valid for a respective epoch in the plurality of discrete epochs for the respective patient from an EMR or an EHR of the respective patient, or determining by natural language processing at least one time-stamped clinical value in a corresponding plurality of clinical values that is valid for the respective epoch for the respective patient from unstructured data in the EMR or EHR of the respective patient.
Claim 5 recites wherein retrieval of the plurality of time-stamped clinical values further comprises: queries querying structured clinical data in the EMR or EHR for a respective patient in the plurality of patients with a string-matching algorithm to identify a time-stamped clinical value that is valid for an epoch in the plurality of discrete epochs for the respective patient, or applying a large language model to the EMR or EHR for a respective patient in the plurality of patients to identify a time-stamped clinical value that is valid for an epoch in the plurality of epochs for the respective patient.
Claim 8 recites wherein the set of eligibility criteria comprises at least one exclusion criterion.
Claim 9 recites wherein the clinical trial is for treatment of a cancer condition and the set of eligibility criteria comprises a diagnosis of the cancer condition, administration of one or more prior therapies for the cancer condition, absence or presence of one or more biomarkers, one or more demographic parameters, or any combination thereof.
Claim 11 recites wherein the A) retrieving of claim 1 further comprises, for a respective patient in the plurality of patients, clustering medical entries from a EMR or a EHR for the respective patient by date and assigning a corresponding earliest eligibility date for the clinical trial based on a date associated with a clustered medical entry that is an earliest indication that the respective patient met the set of eligibility criteria for the clinical trial.
Claims 12 recites wherein the plurality of time-stamped clinical values for the plurality of patients associated with the first set of one or more clinical trial sites spans the first time period, and a respective site-specific predictive enrollment metric for the first set of one or more clinical trial sites is calculated as a measure of central tendency for the number of patients identified, in each epoch of the first time period, as satisfying the set of eligibility criteria applied in the retrieving A) of claim 1.
Claim 13 recites wherein the measure of central tendency is a mean of the number of patients identified as satisfying the set of eligibility criteria applied in the retrieving A) of claim 1.
Claim 14 recites wherein the plurality of time-stamped clinical values for the plurality of patients associated with the first set of one or more clinical trial sites spans the first time period, and a respective site-specific predictive enrollment metric for the first set of one or more sites is determined as a trend in the number of patients identified at the first set of one or more sites over a subset of the first time period.
Claim 15 recites wherein a predicted enrollment metric for the first set of one or more clinical trial sites represents an expected number of patients, identified in the longitudinal eligibility trajectory as newly satisfying the clinical trial eligibility criteria relative to a preceding epoch, over the first time period.
Claim 17 recites wherein the predicted enrollment metric for the second time period is obtained by forming a statistical distribution of possible enrollment counts
Claim 18 recites wherein the statistical distribution is a Poisson distribution established using a factor of the corresponding predicted enrollment matric as the mean of the Poisson distribution.
Claim 19 recites further comprising repeating through E) of claim 1 for each respective additional set of one or more clinical trial sites in a plurality of additional sets of one or more clinical trial sites, thereby predicting a corresponding predicted enrollment for the first time period or the second time period for each respective additional set of one or more clinical trial sites.
Claim 20 recites further comprising: ranking the first set of one or more clinical trial sites and each respective additional set of one or more clinical trial sites in the plurality of additional sets of one or more clinical trial sites based on the corresponding predicted enrollment metric for the clinical trial at the corresponding clinical trial site, or selecting a group of clinical trial sites for the clinical trial based on a comparison between the predicted enrollment metric for the first set of one or more clinical trial sites and the corresponding predicted enrollment metric for each respective additional set of one or more clinical trial sites.
Claim 23 recites wherein the first set of one or more clinical trial sites is a single clinical trial site, and each respective additional set of one or more clinical trial sites in the plurality of additional sets of one or more clinical trial sites is a single respective clinical trial site.
Claim 24 recites further comprising: updating the set of eligibility criteria with one or more revised eligibility criteria for the clinical trial; and repeating, through E) of claim 1,thereby predicting a corresponding predicted enrollment metric for the first time period or the second time period for the updated set of eligibility criteria.
Claim 25 recites further comprising selecting an eligibility criterion for the clinical trial based on a comparison between the predicted enrollment metric for the eligibility criteria prior to the update and the corresponding predicted enrollment metric for each respective updated set of eligibility criteria.
Claim 27 recites further comprising opening recruitment for the clinical trial or administering a treatment in the clinical trial to a patient.
Step 2A- Prong 2
The judicial exception is not integrated into a practical application. In particular, independent claims 1, 29, and 30 do not include additional elements that integrate the abstract idea into a practical application. Claims 1, 29, and 30 each include the additional elements of computer system, processors, memory, electronic medical record (EMR) or electronic health record (EHR) database, trajectory datastore, probabilistic modeling engine, and non-transitory computer-readable medium. These additional elements, when considered in the context of each claim as a whole, merely serve to automate the gathering of data, analysis and making determinations. The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). See Applicant’s specification para. [77-78] regarding computer systems. The database and datastore are also recited at a high-level of generality (i.e., as generic data collections access by computers) such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1, 29, and 30 are directed to an abstract idea without a practical application.
The judicial exception recited in dependent claims 2, 5, 8-9, 11-15, 17-20, 23-25, and 27 is also not integrated into a practical application under a similar analysis as above because they are performed with the same additional elements identified in the independent claims in addition to natural language processing and large language model that appear to be software and are also recited at a high level of generality.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements processors, memory, and non-transitory computer-readable medium are generic in nature and recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). See Applicant’s specification para. [77-78] regarding computer systems. Analyzing these additional elements as an ordered combination adds nothing that is not already present when considering the elements individually; the overall effect of the various computing devices in combination is to automate the gathering of data, analysis and making determinations that could otherwise be achieved as a mental process. Thus, when considered as a whole and in combination, claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 directed to an abstract idea and thus not patent eligible.
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 SHAHID R MERCHANT whose telephone number is (571)270-1360. The examiner can normally be reached M-F 7:30-5.
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/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684