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 .
Status of the Claims
The status of the claims as of the response filed 10/24/2025 is as follows: Claims 1, 17, and 19-20 are currently amended. Claims 2-16 and 18 are original. Claims 1-20 are currently pending in the application and have been considered below.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 119(e) and 120 as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The limitation modifying the cloud computing environment in response to the user resource usage has been removed from claims 1, 19, and 20, such that these claims now appear to be fully supported by the disclosure of parent applications 18/167,812 and 16/732,168. Note that corresponding provisional patent application 62/786,739 makes no mention of a cloud environment or notebooks comprising templates with fillable cells, such that the effective filing date afforded to claims 1, 19, and 20 is the filing date of the ‘168 application: 12/31/2019. Claims 8-18 depending therefrom are also afforded the same effective filing date of 12/31/2019.
The disclosures of the prior-filed applications, Application No. 16/732,168 and 62/786,739, fail to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. For example, the above applications do not provide adequate support for the following limitations of the following claims:
claim 2: wherein at least a portion of the dataset is inaccessible to the user selecting the features defining the dataset;
claim 4: wherein the user cannot perform queries against the at least a portion of the dataset outside of the cloud computing environment;
claim 5: wherein the cloud computing environment prohibits egress of data from the cloud computing environment;
claim 6: limiting egress of data from the cloud computing environment to defined resources within the interactive user portal; and
claim 7: wherein the cloud computing environment is accessible by a plurality of users including an owner of the defined dataset and one or more other users, and wherein the owner of the defined dataset has greater functional control over the defined dataset within the cloud computing environment than the one or more other users.
Neither of the ‘168 and ‘739 applications make any mention of dataset inaccessibility, inability to perform queries against at least a portion of a dataset outside the cloud environment, prohibiting or limiting egress of data from the cloud computing environment, nor relative functional control implications of data ownership. Claims 2 (as well as claims 3-7 depending therefrom), 4, 5, 6, and 7 are therefore not entitled to the priority dates of the previously filed ‘168 and ‘739 applications. The effective filing date of claims 2-7 is considered to be the filing date of parent application 18167812: 2/10/2023.
Response to Amendment
Rejection Under 35 USC 112(b)
Claim 17 has been amended to sufficiently clarify the indefinite limitation such that the corresponding 35 USC 112(b) rejection is withdrawn.
Rejection Under 35 USC 103
The amendments made to independent claims 1, 19, and 20 alter the scope of the claims, resulting in an older effective filing date that disqualifies the Lefkofsky reference as prior art. Accordingly, the corresponding 35 USC 103 rejections are withdrawn. However, Examiner will consider the amended claims in light of an updated prior art search and address their patentability with respect to prior art below.
Claim Rejections - 35 USC § 103
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.
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 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.
Claims 1-13, 15-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Crafts, JR. et al. (US 20170124263 A1) in view of Kain et al. (US 20200210405 A1).
Claims 1, 19, and 20
Crafts teaches a method, comprising:
provisioning a cloud computing environment having access to a plurality of databases and a plurality of pre-defined notebooks (Crafts Figs. 6 & 8, [0086]-[0087], [0097], noting a cloud-based clinical analytics system that includes a storage/data layer and an analytics layer (i.e. a cloud computing environment having access to a plurality of storage databases and a plurality of pre-defined analytical tools and/or workflows)), each of the pre-defined notebooks comprising a template configured to be displayed in an interactive portal as one or more cells, each cell fillable with one of a plurality of preconfigured elements selected from analytics, models, visualizations, or reportings for implementing a specific type of disease progression analysis, wherein the cloud computing environment is accessible via an interactive user portal (Crafts Figs. 8 & 16, [0106]-[0108], noting the analytical tools and/or workflows (i.e. notebooks) include corresponding visualization templates for displaying data representative of analytics or modeling workflows in fillable fields (i.e. cells) on an interactive user interface (e.g. as shown in Figs. 12A-15B); the analytics/modeling results can represent a specific type of predictive disease risk model as noted in [0045] & [0089], considered equivalent to a specific type of disease progression analysis);
receiving, via the interactive portal displayed on a display device operatively coupled to a computer, a user selection of features defining a dataset (Crafts Fig. 16, [0092], [0112]-[0113], noting a user selects features such as disease/condition and a corresponding information set (i.e. as derived from and stored in the plurality of databases/data sources noted in [0005] & [0086]) such as genomic markers to apply to a specific analytical workflow), wherein each subject in the cohort of subjects has been diagnosed with one or more cancers, and wherein the dataset comprises clinical information relating to each of the subjects and biomarker information relating to a tumor specimen of each of the subjects (Crafts [0043], [0067]-[0068], noting the system can perform analyses by aggregating datasets representing cohorts of similar patients with similar medical conditions (which can include cancer as contemplated in [0089]), similar clinical information, and similar genetic or other biomarkers from biological specimens (considered to encompass biomarker information relating to a tumor specimen of each subject));
identifying a subset of notebooks of the plurality of pre-defined notebooks based on the user selection (Crafts [0098], [0106]-[0108], noting the system selects appropriate workflows and visualization templates (i.e. notebooks) based on the user selection/query),
generating, within the cloud computing environment a notebook interface comprising a plurality of user interface elements, each user interface elements configured to launch a corresponding notebook from among the subset of notebooks (Crafts Figs. 12A-15B, [0112], [0124], noting generation of interface displays with interactive elements which may launch corresponding workflow and visualization templates (i.e. notebooks) responsive to user selection); and
In summary, Crafts teaches a method for facilitating user queries regarding various patient features (e.g. disease and other clinical features) that result in the selection and launching of various pre-defined workflow analyses and corresponding visualization templates at an interactive user interface. Crafts further notes that various analyses may be based on patient data aggregated into cohorts based on features like condition, clinical data, and genetic/biomarker data. Though Crafts both (1) allows for a user to make a query related to a single given patient’s features so that workflow analyses and visualization templates are provided and (2) contemplates defining user cohorts, it fails to explicitly disclose that the user query for the purpose of workflow analyses and visualization templates as in Fig. 16 & [0106]-[0115] specifically represents a cohort of patients with the selected features. That is, Crafts appears to contemplate cohort grouping as part of the analytical model process, but not as part of the patient feature selection/querying function as related to selecting data for a given workflow analysis. Further, though Crafts contemplates performance of the method in a cloud computing environment, it fails to explicitly disclose monitoring user resource usage within the cloud computing environment.
However, Kain teaches an analogous method of performing clinical analytics on patient data that allows a user to select patient features to define a cohort of patient data that is then extracted and loaded into a cloud environment to be further analyzed for various purposes (Kain [0060], [0108], [0179], [0243]-[0247], noting a third-party user may query a clinical analytics system for subsets of information representing a cohort of patients associated with the selected patient features for desired analytics in a secure cloud sandbox environment). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the query/selection for analytics related to a single given patient’s features as in Crafts such that the query/selection for analytics may define a cohort of a plurality of patients with the desired features in a cloud sandbox as in Kain in order to permit the predefined analytic workflows and visualization to be applied to cohorts of similar patients in a secure and private sandbox environment, thereby improving the research capabilities and statistical power of the analyses by providing a powerful use case for determining clinical correlations across a patient population (as suggested by Kain [0243]-[0244] & [0246]) while still ensuring data privacy and security for the underlying patient data (as suggested by Kain [0060]).
Kain further teaches monitoring user resource usage within the cloud computing environment (Kain [0220], noting the number of uses of specific data (i.e. resources) may be tracked so that duration or time-based restrictions on data usage may be enforced). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the cloud computing environment of the combination to further include the ability to monitor user resource usage within the cloud computing environment as in Kain in order to permit enforcement of duration or time-based restrictions on the usage of specific data resources (as suggested by Kain [0220]).
Regarding claim 19, Crafts in view of Kain teaches a system, comprising: a computer including a processing device, the processing device configured to (Crafts [0100], [0125]) perform steps substantially similar to those of claim 1, as explained above.
Regarding claim 20, Crafts in view of Kain teaches a non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to (Crafts [0100], [0105], [0125]) perform steps substantially similar to those of claim 1, as explained above.
Claim 2
Crafts in view of Kain teaches the method of claim 1, but the present combination fails to explicitly disclose wherein at least a portion of the dataset is inaccessible to the user selecting the features defining the dataset. However, Kain further teaches at least a portion of a dataset being inaccessible to the user selecting the features defining the dataset (Kain [0060], [0129], [0221], noting users defining member data for retrieval such as third-parties or administrative entities may not have access to the members’ personal information). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the cohort selection method of the combination such that at least a portion of the requested dataset is inaccessible to the user selecting the dataset as in Kain in order to facilitate increased control and ownership of the data such that patient privacy, security, and autonomy are enhanced (as suggested by Kain [0050], [0060], & [0221]).
Claim 3
Crafts in view of Kain teaches the method of claim 2, and the combination further teaches wherein, after receiving the user selection of features, the defined dataset is loaded into the cloud computing environment (Kain [0060], [0126], [0179]-[0180], noting a requested cohort dataset may be loaded into a secure, controlled virtual “sandbox” of a cloud computing environment for analysis).
Claim 4
Crafts in view of Kain teaches the method of claim 3, and the combination further teaches wherein the user cannot perform queries against the at least a portion of the dataset outside of the cloud computing environment (Kain [0060], [0129], [0221], noting users such as third-parties or administrative entities may not have access to the members’ personal information which is stored in separate secured databases, considered equivalent to the user not being able to perform queries against a portion of the dataset outside of the dataset that has been loaded into the cloud computing environment).
Claim 5
Crafts in view of Kain teaches the method of claim 3, and the combination further teaches wherein the cloud computing environment prohibits egress of data from the cloud computing environment (Kain [0060], [0126], noting a requested cohort dataset may be loaded into a secure, controlled virtual “sandbox” for analysis, considered equivalent to prohibiting egress of data from the sandbox because third parties may only access the data for analysis within the context of the controlled sandbox).
Claim 6
Crafts in view of Kain teaches the method of claim 3, and the combination further teaches limiting egress of data from the cloud computing environment to defined resources within the interactive user portal (Kain [0060], [0126], [0220], noting the secure, controlled virtual “sandbox” for analysis of cohort data, with various protocols for restricting processing of the data, considered equivalent to prohibiting egress of data from the sandbox to certain processing resources).
Claim 7
Crafts in view of Kain teaches the method of claim 3, and the combination further teaches wherein the cloud computing environment is accessible by a plurality of users including (Crafts [0090], [0115], noting different user roles (e.g. patient, clinician, researcher, etc.) with different levels of access to the data may interact with the system, such that certain users are considered to have greater functional control over the data than others). However, the present combination fails to explicitly disclose that one of the users is an owner of the defined dataset, and that the owner of the defined dataset is the user who has greater functional control over the defined dataset than the one or more other users. However, Kain further teaches that a variety of users may access the analytics system, including members who contribute their own data to the system and may retain 100% control and ownership of the data, with the ability to revoke consent at any time, as well as other users like administrative entities and third-parties who may access more limited aspects of the data in accordance with the member’s consent (Kain [0050], [0060], [0103]-[0105], [0221]). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the various user access levels of the combination such that data owners have greater functional control over the data than other users as in Kain in order to facilitate maximum autonomy for data owners so that they retain 100% control and ownership of the data, with the ability to revoke consent at any time (as suggested by Kain [0050]).
Claim 8
Crafts in view of Kain teaches the method of claim 1, and the combination further teaches wherein the cloud computing environment defines a specific workspace comprising a logically partitioned environment, and wherein one or more separate servers or virtual machines are provisioned to the specific workspace (Kain [0060], [0126], noting the requested cohort data is loaded into a secure, controlled virtual “sandbox” of a cloud computing environment, considered equivalent to a specific workspace comprising a logically partitioned environment with a separate provisioned virtual machine).
Claim 9
Crafts in view of Kain teaches the method of claim 1, and the combination further teaches wherein the cloud computing environment defines a workspace comprising a logically partitioned environment, the environment including preconfigured services to be implemented with the dataset (Crafts Figs. 8 & 16, [0106]-[0108], noting predefined analytical tools and/or workflows (i.e. services) that are applied to the selected data; see also Kain [0060], [0126], noting the requested cohort data is loaded into a secure, controlled virtual “sandbox” of a cloud computing environment, considered equivalent to a specific workspace comprising a logically partitioned environment for analytics. Taken together in the context of the combination explained above, these teachings show that data loaded into cloud sandbox workspaces as in Kain may be processed with the predefined analytic services of Crafts).
Claim 10
Crafts in view of Kain teaches the method of claim 9, and the combination further teaches wherein the workspace further comprises one or more compute resources, the compute resources provisioned to the workspace independently of the preconfigured services (Crafts [0085], [0102], noting the system utilizes cloud based and scalable resources; see also Kain [0127], noting cloud service includes a platform of servers. These disclosures indicate that one or more cloud compute resources such as servers may be provisioned as needed and ‘independently’ of any predefined analytic workflows or services).
Claim 11
Crafts in view of Kain teaches the method of claim 1, and the combination further teaches wherein the cloud computing environment defines a workspace (Kain [0060], [0126], noting the requested cohort data is loaded into a secure, controlled virtual “sandbox” of a cloud computing environment, considered equivalent to a specific workspace) and further comprises access rights for a plurality of users, the access rights determining eligibility for access to the workspace by each of the plurality of users (Crafts [0090], [0115], noting different user roles (e.g. patient, clinician, researcher, etc.) with different levels of access to the data may interact with the system, considered to include the sandbox workspace of Kain when considered in the context of the combination).
Claim 12
Crafts in view of Kain teaches the method of claim 11, and the combination further teaches wherein the access rights further determine limits on rights with respect to the dataset or other elements of the interactive portal, outside of the workspace (Crafts [0090], [0115], noting different user roles (e.g. patient, clinician, researcher, etc.) with different levels of access to the data or other functions of the system such as the ability to modify analytic models, i.e. another element of the interactive portal outside the specific loaded sandbox workspace of the combination).
Claim 13
Crafts in view of Kain teaches the method of claim 1, and the combination further teaches: receiving, within the notebook interface, a user selection of one of the notebooks; modeling the dataset according to the model or analyzing the dataset according to the analysis of the selected notebook; and applying the preconfigured visualizations or reportings to the modeled or analyzed dataset to provide results to the user via the interactive portal (Crafts [0112]-[0113], noting a user selects a button associated with a specific workflow and visualization (i.e. notebook) which results in corresponding predefined workflow and visualization analytics being applied to the data (i.e. the selected cohort data as in the combination with Kain) and results being filled in for the user at the interactive portal).
Claim 15
Crafts in view of Kain teaches the method of claim 13, and the combination further teaches wherein the model or analysis comprises a previously trained machine learning model, a machine learning model that is trained on the fly, or an unsupervised machine learning model (Crafts [0032]-[0033], noting the analytic tools applied to the selected data can include previously trained machine learning models and/or unsupervised machine learning models).
Claim 16
Crafts in view of Kain teaches the method of claim 13, and the combination further teaches wherein the model identifies optimal parameters to apply based on the dataset (Crafts [0052], [0070], noting rules and weights (i.e. parameters) are continuously tuned/determined to learn/identify the best parameters for analysis of data, e.g. as based on a patient’s similarities to other patients, considered equivalent to identifying optimal parameters to apply based on the selected dataset).
Claim 17
Crafts in view of Kain teaches the method of claim 13, and the combination further teaches wherein the notebook is blank at a time the user selection of one of the notebooks is received, and the model or analysis to apply to the dataset and the visualizations or reportings are defined by the user subsequent to the time the user selection of one of the notebooks is received (Crafts [0112]-[0113], noting a user selects a button associated with a specific workflow and visualization (i.e. notebook) which results in corresponding predefined workflow and visualization analytics being applied to the data (i.e. the selected cohort data as in the combination with Kain) and results being filled in for the user at the interactive portal; this is considered equivalent to the notebook being “blank” at the time of user selection of the notebook, because the analysis has not yet been performed and displayed to the user prior to the button being selected).
Claims 14 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Crafts and Kain as applied to claims 1 and 13 above, and further in view of Bellin et al. (US 20090076845 A1).
Claim 14
Crafts in view of Kain teaches the method of claim 13, but the present combination does not appear to discuss repeating cohort selection to generate and analyze a second cohort of patient data and compare the analysis results of the first and second cohorts, such that the present combination fails to explicitly disclose: receiving, via the interactive portal, a user selection of a second dataset representing a second cohort of subjects, wherein each subject in the second cohort of subjects has been diagnosed with one or more cancers, and wherein the second dataset comprises clinical information relating to each of the second subjects and molecular information relating to a tumor of each of the second subjects; modeling the second dataset according to the model or analyzing the second dataset according to the analysis of the selected notebook; and applying the preconfigured visualizations or reportings to the modeled or analyzed second dataset to provide second results to the user via the interactive portal, wherein the results and the second results are provided concurrently to permit direct comparison between the cohort and the second cohorts of subjects.
However, Bellin teaches an analogous clinical analytics system that allows a user to define both first and second cohorts of patients according to desired characteristics, perform the same selected analysis on both cohorts of patients so that preconfigured visualizations representing first and second results are provided via an interactive user portal so that direct comparison between the results for each cohort may be made (Bellin [0093], [0096], [0109]-[0110], [0114]-[0115], [0121], [0140], [0144], [0159], noting a user may select a desired analytic such as length of stay, mortality, lab outcomes, readmission, etc. (considered equivalent to a notebook) as well as define the characteristics of two cohorts so that the analytic may be run on the cohort data and results of the desired analytic may be directly compared between the two cohorts via a preconfigured visualization). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the clinical analytics method of the combination to permit entering additional criteria about a second cohort of patients, running a desired analysis on both cohorts of patients, and visualizing the results of the analysis for both of the cohorts for direct comparison as in Bellin in order to allow a user to draw inferences about relative care and understand differences in outcomes between groups so that the remediation efforts can be more targeted to improve patient care (as suggested by Bellin [0159]). The result of such a combination would include the ability to define multiple cohorts for comparison based on patient characteristics as in Bellin that include the specific characteristics of diagnoses like cancer and biomarker data (considered to include molecular information related to a tumor) as in Crafts, followed by analysis of the selected data with preconfigured analytics and corresponding visualizations as in Crafts and Bellin so that direct comparison may facilitated as in Bellin.
Claim 18
Crafts in view of Kain teaches the method of claim 13, and the combination further teaches: receiving a user selection of the model or analysis to apply to the dataset; and (Crafts [0112]-[0113], noting a user selects a button associated with a specific workflow (i.e. model or analysis) with a specific target output specifying one or more features to identify, which results in a corresponding predefined workflow being applied to the data (i.e. the selected cohort data as in the combination with Kain) and results being filled in for the user at the interactive portal). Though the present combination teaches selection of a specific workflow with a specific target output by a user, it fails to explicitly disclose specifically requesting a target output from the user upon receiving selection of the model or analysis.
However, Bellin teaches an analogous clinical analytics system that includes a user first selecting a specific analytic workflow for a set of patient data, the system responsively requesting data about a target output of the analysis, and then performing the defined analysis (Bellin [0093]-[0094], [0118], [0127], noting a user first selects between analytic models such as lab outcomes, mortality, length of stay, readmissions, etc., and responsive to a selected analytic the system requests additional parameters or values for the target output of the analysis such as the desired timeframe of a readmission analysis, desired type of laboratory outcomes and ranges for a laboratory outcome analysis, etc., which are then used when running the analysis to obtain results). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the single analysis selection step of the combination such that a desired analytic model is first selected and additional target output parameters are then requested from a user as in Bellin in order to facilitate increased analytic flexibility and customization by a user by permitting different parameter entry options that vary from analytic model to analytic model so that a very specific desired output type may be defined (as suggested by Bellin [0016] & [0094]).
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 KAREN A HRANEK whose telephone number is (571)272-1679. The examiner can normally be reached M-F 8:00-4:00 ET.
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/KAREN A HRANEK/ Primary Examiner, Art Unit 3684