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 .
Response to Amendment
In the amendment filed 12/30/2025, the following has occurred: claims 1-3, 8-10, and 15-17 have been amended. Now, claims 1-20 are pending.
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 1-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A Prong One
Claims 1, 8, and 15 (claim 1 representative) recite receiving a request related to a candidate; accessing, in response to the request, a database that includes a collection of data related to the candidate, wherein the collection of data comprises candidate data from a plurality of disparate electronic sources including at least one of electronic health records, laboratory records, and third-party databases; receiving an update to the collection of data; automatically evaluating the updated collection of data against a plurality of trial criteria; determining at least one potential trial for the candidate based on the evaluation; converting the updated collection of data into one or more criteria sections; and automatically displaying a message to one or more users related to eligibility of the candidate for the at least one potential trial.
These limitations, as drafted, given the broadest reasonable interpretation, encompass managing interactions between people, which is a subgrouping of Certain Methods of Organizing Human Activity. For example, the claims encompass an accessing and updating regarding a clinical trial candidate in response to a request, evaluating the updated data against trial criteria to determine a trial for the candidate, and providing a message to a user related to eligibility of the candidate for the trial. Thes steps could be carried out manually between individual in the process of finding candidates for clinical trials. Such manual steps encompass Certain Methods of Organizing Human Activity.
Claims 2-7, 9-14, and 16-20 incorporate the abstract idea identified above and recite additional limitations that expand on the abstract idea. Claims 2, 9, and 16 further define the sources of data and identifying updates in one of the sources to aggregate and evaluate data for eligibility of the candidate. Similar to above, these steps encompass managing interactions between people. Claims 3, 10, and 17 further expand on identifying the trial for the candidate using criteria selections and a completion score. This could further involve a user manually finding trials for candidates. Claims 4-7, 11-14, and 18-20 further recite candidate interest response, indicative of the candidate being interested or not interested in the trial, and updating or providing data in response. These additional steps could similarly be caried out by individuals, such as a potential candidate and someone involved in the potential trial. As explained above, these manual steps encompass Certain Methods of Organizing Human Activity.
Step 2A Prong Two
This judicial exception is not integrated into a practical application because the remaining elements amount to no more than general purpose computer components programmed to perform the abstract ideas along with adding elements similar to adding the words “apply it” to the abstract idea, and generally linking the abstract idea to a particular technological environment, along with insignificant, extra-solution data gathering activity.
Claims 1-20 directly or indirectly, recite the following additional elements at a high level of generality and merely utilized as tools to implement the abstract idea:
Claims 1, 8, 15:
“automatically generating…a graphical user interface (GUI).”
“automatically displaying, within the GUI, a message”
Generating and displaying “a trials dashboard tab within the GUI, wherein the trials dashboard tab includes the one or more criteria sections, wherein the generating comprising populating the one or more criteria sections regarding the at least one potential trial on the trial dashboard tab.
Claim 8 additionally recites:
“one or more processors; and one or more memories that include instructions executable by the one or more processors to perform operations.”
Claim 15 additionally recites:
“A non-transitory computer-readable memory storing a plurality of instructions executable by one or more processors for causing the one or more processors to perform operations.”
Claims 5-7:
Various steps carried out by “a processor.”
Claims 6-7, 13-14, 20:
Storing data in “a trial candidate module.”
The written description discloses that the recited computer components encompass generic components including “the computing devices can include any combination of servers, personal computers, laptops, tablets, smartphones, etc.” (see paragraph 0031). With regard to recitations of The GUI including a tab and sections, this represents no more than a generic computer display. Considered in combination with the other limitations, this element still amounts to no more than generic computer components configured to implement the abstract idea. As set forth in the MPEP 2106.04(d) “merely including instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
Claims 1-20, directly or indirectly, recite the following additional elements at a high level of generality, involving no more that extra-solution data gathering and transmitting activity:
Claim 1, 8, and 15:
Receiving, via a graphical user interface (GUI)…”
These additional elements are recited at a high degree of generality and are merely involved in insignificant extra solution data gathering and transmitting of data over a generic computer network. As set forth in MPEP 2106.05(g) insignificant, extra-solution activity, such as insignificant acquisition and data transmission, is an example of when an abstract idea has not been integrated into a practical application.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration into a practical application, the additional elements are recited at a high level of generality, and the written description indicates that these elements are generic computer components. Using generic computer components to perform abstract ideas does not provide a necessary inventive concept. See Alice, 573 U.S. at 223 (“mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”).
Insignificant, extra solution, data gathering activity (e.g. transmitting and receiving data over a computer network) has been found to not amount to significantly more than an abstract idea (see MPEP 2106.05(g) and Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)).
Storing and retrieving information in memory (e.g. collecting data into a module) has been recognized as well-understood, routine, and conventional activity of a general-purpose computer (see MPEP 2106.05(d) and 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).
Additionally, the aforementioned additional elements, considered in combination, do not provide an improvement to a technical field or provide a technical improvement to a technical problem. Therefore, whether considered alone or in combination, the additional elements do not amount to significantly more than the abstract idea.
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) 1-4, 8-11, and 15-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran, US Patent Application Publication No. 2020/0381087 in view of Kalathil, US Patent Application Publication No. 2015/0161336.
As per claim 1, Ozeran teaches a computer-implemented method comprising: receiving, via a graphical user interface (GUI), a request related to a candidate (see paragraph 0134; providers can access databases, including patient data, with queries of the databases); accessing, in response to the request, a database that includes a collection of data related to the candidate (see paragraph 0130; patient data from multiple sources), wherein the collection of data comprises candidate data from a plurality of disparate electronic sources including at least one of electronic health records, laboratory records, and third-party databases (see paragraph 0130; multiple sources of data include clinical records, lab results and imaging data); receiving an update to the collection of data (see paragraph 0132; as new patient data becomes available, database can be updated); aggregating candidate data from the plurality of disparate electronic sources to generate an updated collection of data (see paragraph 0256; patient data store may be aggregated from many different sources (described above as the plurality of disparate electronic sources); automatically evaluating the updated collection of data against a plurality of trial criteria (see paragraph 0155; performs comparison between patient data and clinical trial eligibility data); determining at least one potential trial for the candidate based on the evaluation (see paragraph 0174; performs matching between patients and clinical trials); converting the updated collection of data into one or more criteria sections (see paragraph 0256; incoming patient and clinical trial information converted to a structured format, as well as mapping to preserve inclusion and exclusion criteria); automatically generating, substantially contemporaneous to determining the at least one potential trial, a trials dashboard tab within the GUI, wherein the trials dashboard tab includes the one or more criteria sections (see paragraph 0178; GUI shows clinical trial matching along with criteria sections; Additionally, Figures 10-15 include GUI displays encompassed by “trials dashboard tab” and populated criteria sections), wherein the generating comprises populating the one or more criteria sections regarding the at least one potential trial on the trials dashboard tab (see paragraph 0116; a clinical trial may specify patients diagnosed with stage I breast cancer (criteria section) and populate data fields corresponding to stage/grade with stage I and populating other fields; Additionally, Figures 10-15 include GUI displays encompassed by “trials dashboard tab” and populated criteria sections); and automatically displaying, within the GUI, a message related to an eligibility of the candidate for the at least one potential trial (see paragraph 0174; GUIs show which trials the patient is eligible for).
Ozeran describes updating a collection of data from disparate data sources (see paragraph 0132; as new patient data becomes available, database can be updated) and updating the collection of data from disparate data sources (see paragraph 0256; patient data store may be aggregated from many different sources (described above as the plurality of disparate electronic sources). However, Ozeran does not explicitly teach the aggregating is in response to the update. Kalathil teaches updating patient data with data from disparate data sources (see paragraphs 0069 and 0093; an EHR vault is updated with data from disparate providers (including clinical laboratories, and other sources), and in response to the update, aggregating candidate data from the disparate data sources (see paragraph 0108; aggregator aggregating the EHR data for use in matching with clinical trials). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to incorporate the aggregation of updated data in the system of Ozeran with the motivation of establishing a more complete and contemporaneous collection of patient data (see paragraph 0090 of Kalathil).
As per claim 2, Ozeran teaches the method of claim 1 as described above. Ozeran further teaches the plurality of disparate electronic sources include the electronic health records, the laboratory records, and the third-party databases (see paragraph 0130; multiple sources of data include clinical records, lab results and imaging data), and wherein the method further comprises continuously monitoring for updates to the candidate data from at least one of the plurality of disparate electronic sources (see paragraph 0132; as new patient data becomes available, database can be updated), and aggregating the subsequent update ((see paragraph 0256; patient data store may be aggregated from many different sources (described above as the plurality of disparate electronic sources) and re-evaluating the eligibility of the candidate for the at least one potential trial (see paragraph 0155; performs comparison between patient data and clinical trial eligibility data).
As noted above, Ozeran does not explicitly teach the aggregating is in response to the update. Kalathil teaches updating patient data with data from disparate data sources (see paragraphs 0069 and 0093; an EHR vault is updated with data from disparate providers (including clinical laboratories, and other sources), and in response to the update, aggregating candidate data from the disparate data sources (see paragraph 0108; aggregator aggregating the EHR data for use in matching with clinical trials). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to incorporate the aggregation of updated data in the system of Ozeran for the reasons given above with respect to claim 1.
As per claim 3, Ozeran teaches the method of claim 1 as described above. Ozeran further teaches evaluating the updated collection of data against the plurality of trial criteria comprises producing, for each of the at least one potential trial, a completion score for the candidate (see paragraph 0182; scores of matched trials can be determined based on previously described updated data), the method further comprising: receiving, via the trials dashboard tab, additional information regarding qualifications of the candidate relevant to criteria for the at least one potential trial (see paragraph 0212; clinical trial matching qualifications can be updated; paragraphs 0248-0249; updating features in the patient data store can be used for matching patients with clinical trials); and updating the completion score associated with the at least one potential trial (see paragraphs 0294 and 0307; continuously updated patient and trial data used in matching resulting in updated matching scores), wherein the trials dashboard tab displays the completion score for the candidate (see Figure 10 including a matching score).
As per claim 4, Ozeran teaches the method of claim 1 as described above. Ozeran further teaches receiving, for each of the at least one potential trial, a response regarding a candidate interest in a potential trial (see paragraph 0119; patient enrollment along with requesting an additional site for the trial are responses regarding candidate interest in a potential trial).
Claims 8-11 and 15-18 recite substantially similar system and computer memory limitations to method claims 1-4 and, as such, are rejected for similar reasons as given above.
Claim(s) 5-7, 12-14, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ozeran, US Patent Application Publication No. 2020/0381087 in view of Kalathil, US Patent Application Publication No. 2015/0161336 and further in view of Borno, US Patent Application Publication No. 2024/0257924.
As per claim 5, Ozeran teaches the method of claim 4 as described above. Ozeran further teaches each response that indicates that the candidate is not interested in the potential trial, the method further comprises removing, by a processor, the potential trial associated with the response (see paragraph 0184; selecting “no” removes the trial from the trial list). Although “no” selections may be recorded, Ozeran does not explicitly teach updating, by the processor, the updated collection of data with the response regarding the candidate interest in the potential trial. Borno teaches updating, by a processor, updated collection of data with a response regarding a candidate interest in a potential trial (see paragraph 0066; trials are matched to patients and a provider may select “leave” to remove the trial from a list of matched trials, this is an update to a collection of data with a response regarding a candidate interest in a potential trial). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to update a list of potential trials associated with a candidate based on the interest or non-interest of the candidate in the trial matching system of Ozeran with the motivation of providing benefits to existing clinical trial matching (see paragraph 0056 of Borno).
As per claim 6, Ozeran teaches the method of claim 4 as described above. Ozeran further teaches a response indicates that the candidate is interested in the potential trial (see paragraph 0184; a matched clinical trial can be selected with “yes”). Ozeran does not explicitly teach for each response that indicates that the candidate is interested in the potential trial, the method further comprising exporting, by a processor, the updated collection of data regarding the potential trial associated with the response into a trial candidate module. Borno teaches for a response that indicates that a candidate is interested in a potential trial, the method further comprising exporting, by a processor, an updated collection of data regarding a potential trial associated with the response into a trial candidate module (see paragraphs 0060-0061; matched trials can be added to a trial candidate module (dashboard) by selected “add to my trials”). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to update a list of potential trials associated with a candidate based on the interest or non-interest of the candidate in the trial matching system of Ozeran with the motivation of providing benefits to existing clinical trial matching (see paragraph 0056 of Borno).
As per claim 7, Ozeran and Borno teaches the method of claim 6 as described above. Ozeran does not explicitly teach importing, automatically by the processor, additional information regarding the potential trial into the trial candidate module, the additional information related to an available candidate that has expressed interest in at least one other trial similar to the potential trial. Borno further teaches importing, automatically by the processor, additional information regarding the potential trial into the trial candidate module, the additional information related to an available candidate that has expressed interest in at least one other trial similar to the potential trial (see paragraphs 0060-0061; matched trials can be added to a trial candidate module (dashboard) by selected “add to my trials”; since the list of trials have been matched to patients, they are similar and each trial added to the dashboard is an expression of interest for a respective candidate). It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to update a list of potential trials associated with a candidate based on the interest or non-interest of the candidate in the trial matching system of Ozeran with the motivation of providing benefits to existing clinical trial matching (see paragraph 0056 of Borno).
Claims 12-14 and 19-20 recite substantially similar system and computer memory limitations to method claims 5-7 and, as such, are rejected for similar reasons as given above.
Response to Arguments
In the remarks filed 12/30/2025, Applicant argues (1) highlighted steps [a] – [i] do not recite abstract ideas for reasons explained a pages 11-13; (2) the claimed invention integrates the abstract idea into a practical application by providing a technical solution to a technical problem, described at pages 14-15; (3) the claimed invention integrates the abstract idea into a practical application by providing an improved graphical user interface, described at pages 15-16; (4) Ozeran does not teach updating candidate data from a plurality of disparate electronic sources, described at pages 16-17; (5) Ozeran does not teach the dynamically assembled and updated trial dashboard tab, described at page 17; (6) Ozeran does not teach the dynamic operations of claims 2 and 3, described at page 18; (7) Borno does not cure the deficiencies of Ozeran.
In response to argument (1), while the examiner acknowledges that some of the steps involve the use of computer components, the examiner respectfully maintains that these steps also recite parts of the abstract idea. Additionally, these arguments are not persuasive because the basis for why they are asserted to not recite an abstract idea includes additional features that are not recited in the claim. With regard to step [a], the use of a GUI has been treated as an additional element and the step does not require triggering communication with a database, standardized, automated input, or system driven workflow. With regard to step [b] the claim recites accessing data from a plurality of sources, such as lab records and third-party data. This step does not require the argued features of asynchronous and incompatible data or connection, extraction, and combining records from heterogeneous electronic sources. Step [c] merely requires an update to collected data. This does not include the argued features of monitoring for updates from multiple sources, triggering aggregating with continuous or periodic checks. With regard to step [d], the aggregating of updated data does not require deduplication and normalization. With regard to step [e], the recited evaluation of updated collection of data against trial criteria does not include any requirements of complex, structured data or comparisons to changing eligibility requirements. The assessment of step [f] is accurate with the exception of requiring it to be performed by the system (claim 1, for example, is a computer-implemented method but does not specify any system element to carry out this step). Step [g] does not include any recitations regarding mapping raw, multi-source data into GUI elements. Steps [h] and [i] include recitations that are part of the abstract idea as well as additional elements. Because the arguments are not commensurate in scope with the recitations in the claims, these arguments are not found to be persuasive.
In response to argument (2), the examiner respectfully submits that the claims do not include limitations reflecting the argued technical solution to the technical problem. To begin with, the recited “disparate electronic sources” do not include fragmented data with proprietary formats and asynchronous updates. The claims do not include any limitations on the formats (different or otherwise) or the frequency of updates regarding the “disparate electronic sources.” The claims do not recite continuous monitoring the sources for new data for “immediately aggregating and normalizing.” There is not recitation related to aggregating being “immediate” nor any type of data “normalizing.” Furthermore, while the accessed data is from “a plurality of disparate electronic sources,” the recited “electronic health records, laboratory records, and third-party databases” are only listed for selecting “at least one.” The source of data could be, for example, two, different laboratory records. This does not require different types of data or different schedules for updating the data. Therefore, the argued technical solution is not commensurate in scope with the limitations recited in the claims.
In response to argument (3), the recited features of the GUI are that it includes a trials dashboard tab that includes the criteria sections and populating the criteria sections. In other words, the recited elements require a single displayed tab populated with data. As identified in the rejections, this encompasses a generic computer display for outputting the data. The recitation of the GUI being generated “substantially contemporaneous to determining the at least one potential trial,” simply requires the GUI to be displayed after the potential trial is determined. Applicant argues features for dynamic assembly and continuously assembling and updating the display, but such limitations are not recited in the claims. Therefore, based on the broadest reasonable interpretation of the GUI as recited in the claims, the examiner respectfully maintains that this additional element does not integrate the abstract idea into a practical application.
In response to argument (4), Ozeran teaches that patient data may be acquired from “multiple sources (such as lab results...imaging data…clinical record(s)” (see paragraph 0130). Furthermore, as new patient data becomes available, the patient data can be updated (see paragraph 0132). Additionally, aggregating “in response to the updating” relies on a new ground of rejection set forth above.
In response to argument (5), the citations of Ozeran have been updated in the above rejections to teach the amendment features regarding the GUI. Additionally, claim 1, for example, recites a single instance of the trials dashboard tab being displayed within the GUI. Therefore, arguments regarding dynamic assembly of the GUI dashboard are not persuasive because they are not commensurate in scope with the claims.
In response to argument (6), the continuous monitoring in claim 2 refers to updates to candidate data from at least one of the sources. As noted above, Ozeran teaches updating patient data “as new patient data becomes available” (see paragraph 0132). Updated data as new data becomes available is encompassed by monitoring one source of data for updates as recited in claim 2. Additionally, the updating of the score in claim 3 does not require any dynamic adjustments. Rather, the claim simply requires updating the score associated with the potential trial and displaying it. As described in the rejections, the score is based on the patient and trial data, where the patient data is updated as new patient comes available. Therefore, a new score, based on new patient data is encompassed by this limitation.
Applicant’s argument (7) has been fully considered but is moot in view of the pending rejections.
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 C. Luke Gilligan whose telephone number is (571)272-6770. The examiner can normally be reached Monday through Friday 9:00 - 5:00.
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C. Luke Gilligan
Primary Examiner
Art Unit 3683
/CHRISTOPHER L GILLIGAN/ Primary Examiner, Art Unit 3683