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 office action is in response to the claims filed on May 28, 2024 for the application filed May 28, 2024 which claims priority to a provisional application filed on November 30, 2021. Claims 1-17 are currently pending and have been examined.
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 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Eligibility Step 1:
Under step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, claims 1-17 are directed towards a computerized method (i.e. a process), which is a statutory category. Since the claims are directed toward statutory categories, it must be determined if the claims are directed towards a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea). In the instant application, the claims are directed towards an abstract idea.
Eligibility Step 2A, Prong One:
Under step 2A, prong one of the 2019 Revised Patent Subject Matter Eligibility Guidance, independent claim 1 is determined to be directed to an judicial exception because an abstract idea is recited in the claims which fall within the subject matter groupings of abstract ideas. The abstract idea (identified in bold) recited in the claim 1 is identified as:
A computerized method for identifying a patient subjects for inclusion in a clinical trial, the method comprising:
accessing data indicative of times of a plurality of healthcare visits of a patient over time during an observation period;
determining a metric based on the times of the plurality of healthcare visits of the patient over time during the observation period; and
identifying the patient for inclusion in the clinical trial when the metric exceeds a metric threshold.
The identified limitations of the abstract idea of claim 1 fall within the subject matter grouping of mathematical concepts, such as mathematical relationships, mathematical formulas or equations, and mathematical calculations. Articulate how the claims recite a mathematical concept by mapping the limitations to one of mathematical relationships, mathematical formulas or equations, or mathematical calculations). See MPEP §2106.04(a)(2)(I).
The identified limitations of the abstract idea of claims 1 fall within the subject matter grouping of certain methods of organizing human activity related and the sub grouping of managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). The claims recite the human activity of identifying a patient subjects for inclusion in a clinical trial, regularly performed by healthcare professionals. The defined data, metric and thresholding are merely rules the healthcare professional should follow in order to identifying a patient subjects for inclusion in a clinical trial
The identified limitations of the abstract idea of claims determining the metric and identifying the patient fall within the subject matter grouping of mental processes. If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping, and the claim recites an abstract idea. Determining a metric based on data and identifying a patient when the metric exceeds a metric threshold can be performed in the human mind using observations, evaluations, judgments and opinions.
Accordingly, claim 1 recites an abstract idea under step 2A, prong one.
Eligibility Step 2A, Prong Two:
Under step 2A, prong two of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether the identified abstract ideas are integrated into a practical application. After evaluation, there is no indication that any additional elements or combination of elements integrate the abstract idea into a practical application, such as through: an additional element that reflects an improvement to the functioning of a computer, or an improvements to any other technology or technical field; an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; an additional element that implements the judicial exception with, or uses the judicial exception in connection with, a particular machine or manufacture that is integral to the claim; an additional element that effects a transformation or reduction of a particular article to a different state or thing; or an additional element that applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. As shown below, the additional elements, other than the abstract idea per se, when considered both individually and as an ordered combination, amount to no more than a recitation of: generally linking the abstract idea to a particular technological environment or field of use; insignificant extra-solution activity to the judicial exception; and/or adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea as evidenced below.
The additional elements recited in claim 1 are identified in italics as:
A computerized method for identifying a patient subjects for inclusion in a clinical trial, the method comprising:
accessing data indicative of times of a plurality of healthcare visits of a patient over time during an observation period;
determining a metric based on the times of the plurality of healthcare visits of the patient over time during the observation period; and
identifying the patient for inclusion in the clinical trial when the metric exceeds a metric threshold.
The additional limitation of “computerized” is determined to be mere instructions to apply an abstract idea under MPEP §2106.05(f). Specifying the method is “computerized” amount to no more than a recitation of the words "apply it" (or an equivalent) or no more than mere instructions to implement an abstract idea or other exception on a computer or no more than merely using a computer as a tool to perform an abstract idea.
The additional limitations of “XXX” are determined to be no more than insignificant extra-solution activity to the judicial exception under MPEP §2106.05(g). Provide an explanation using the guidance in MPEP §2106.05(g).
The additional limitations of “XXX” are determined to be no more than generally linking the use of a judicial exception to a particular technological environment or field of use under MPEP §2106.05(h). Provide an explanation using the guidance in MPEP §2106.05(h).
Accordingly, claim 1 does not recite additional elements which integrate the abstract idea into a practical application.
Eligibility Step 2B:
Under step 2B of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether provide an inventive concept by determining if the claims include additional elements or a combination of elements that are sufficient to amount to significantly more than the judicial exception. After evaluation, there is no indication that an additional element or combination of elements 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 limitation “computerized” is determined to be mere instructions to apply an abstract idea under MPEP §2106.05(f), which is do not amount to significantly more than the abstract idea.
Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements amounts to an inventive concept.
Dependent Claims:
The dependent claims merely present additional abstract information in tandem with further details regarding the elements from the independent claims and are, therefore, directed to an abstract idea for similar reasons as given above. None of these limitations are deemed to integrate the claims into a practical application or to amount to significantly more than the abstract idea as detailed below.
Regarding claims 1-4 merely define the metric and the determinations thereof and are also directed to the abstract ideas of certain methods of organizing human activity and mental processes.
Regarding claim 5, the use of the non-linear compression function to determine the metric is a mathematic calculation and therefore falls within the subject matter grouping of mathematical concepts. This applying the function to time intervals to determine the metric may also be performed in the human mind and therefore also falls within the subject matter grouping of mental processes.
Regarding claims 6-7, defining time intervals for used in determining the metric is directed to the abstract ideas of certain methods of organizing human activity and mental processes.
Regarding claim 8-14, the limitations are directed to mathematic calculations and therefore falls within the subject matter grouping of mathematical concepts which may also be performed in the human mind and therefore also fall within the subject matter grouping of mental processes.
Regarding claim 15-17, the limitations are determined to be directed to the abstract ideas of certain methods of organizing human activity and mental processes for similar reasons as detailed with respect to claim 1.
Therefore, whether taken individually or as an ordered combination, 1-17 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (U.S. Pub. No. 2016/0196411) in view of Nikpour et al. (Frequency and determinants of flare and persistently active disease in systemic lupus erythematosus).
Regarding claim 1, Zhang discloses a computerized method for identifying a patient subjects for inclusion in a clinical trial (Paragraph [0008]), the method comprising:
accessing data Paragraph [0046], Advantageously, the one or more patient data management systems 12 can retrieve or be updated with patient data in real time. For example, one or more of the patient data management systems 12 can be updated with results of laboratory tests for the patient in real time. Accordingly, the data extraction module 18 can access the most recent patient data. Paragraph [0034], As used herein, the term “recent” when used with patient data can refer to patient data gathered within a certain time period. In some instances, the time period can be within a year. In other instances, the time period can be within six months. In further instances, the time period can be within three months. In still other instances, the time period can be within a month. In still other instances, the time period can be within two weeks. Also see paragraph [0066].);
determining a metric Paragraph [0045], For example, the patient data can include demographic information and clinical information. The demographic information can include age, race, sex, etc. The clinical information can include primary diagnosis, tumor-node-metastasis (TNM) classification, metastasis status, stage group, laboratory reports, etc. In some instances, the data extraction module 18 can access specific predefined categories of patient data from the one or more patient data management systems 12.); and
identifying the patient for inclusion in the clinical trial when the metric exceeds a metric threshold (Paragraph [0067], At 64, the patient data can be evaluated (e.g., by matcher 27 of evaluation module 24) against eligibility criteria (e.g., entered in a structured format using the data entry module 22) for a plurality of clinical trials (e.g., from a clinical trial management system 14). The evaluation can include normalizing units of the patient data to facilitate a comparison between the patient data and the eligibility criteria. For example, the eligibility criteria can be stored as a structured eligibility checklist based on eligibility variables stored in a library. The eligibility variables can include a variable identifier, a set of valid variables, a minimum value and a maximum value, a unit of measurement, a description about the subject of the eligibility criterion, and/or a variable type (Boolean, categorical, dynamic categorical, or continuous)).
Zhang does not disclose that the data is indicative of times of a plurality of healthcare visits of a patient over time; or that the metric is based on the times of the plurality of healthcare visits of the patient over time.
Nikpour teaches that it was old and well known in the art of clinical trials at the time of the filing to access data indicative of times of a plurality of healthcare visits of a patient over time and determine a metric based on the times of the plurality of healthcare visits of the patient over time (Nikpour, Page 1156, Discussion, left column, 1st paragraph, discusses that PAD is defined as a SLEDAI-2K score of ≥ 4 on ≥ 2 consecutive visits with a minimum interval between visits of 2 months. Page 1156, Discussion, right column, 1st paragraph, discusses that PAD may be an inclusion criterion for clinical trials.) to reduce the difficulty in the selection of patients for inclusion in trials (Page 1152, Introduction, left column, 1st paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art of clinical trials at the time of the filing to modify the method of Zhang such that the data is indicative of times of a plurality of healthcare visits of a patient over time and such that the metric is based on the times of the plurality of healthcare visits of the patient over time, as taught by Nikpour, in order to reduce the difficulty in selection of patients for inclusion in trials, for example, when the clinical trial is for patient with systemic lupus erythematosus (SLE).
Regarding claim 2, Zhang does not disclose, but Nikpour teaches that it was old and well known in the art of clinical trials at the time of the filing wherein the metric is indicative of a pattern of occurrence of the plurality of healthcare visits over time during the observation period (Nikpour, Page 1156, Discussion, left column, 1st paragraph, discusses that PAD is defined as a SLEDAI-2K score of ≥ 4 on ≥ 2 consecutive visits with a minimum interval between visits of 2 months.) to reduce the difficulty in the selection of patients for inclusion in trials (Page 1152, Introduction, left column, 1st paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art of clinical trials at the time of the filing to modify the method of Zhang such that the metric is indicative of a pattern of occurrence of the plurality of healthcare visits over time during the observation period, as taught by Nikpour, in order to reduce the difficulty in selection of patients for inclusion in trials, for example, when the clinical trial is for patient with systemic lupus erythematosus (SLE).
Regarding claim 3, Zhang does not disclose, but Nikpour teaches that it was old and well known in the art of clinical trials at the time of the filing wherein determining the metric comprises analyzing a spacing of the plurality of healthcare visits over time during the observation period (Nikpour, Page 1156, Discussion, left column, 1st paragraph, discusses that PAD is defined as a SLEDAI-2K score of ≥ 4 on ≥ 2 consecutive visits with a minimum interval between visits of 2 months.) to reduce the difficulty in the selection of patients for inclusion in trials (Page 1152, Introduction, left column, 1st paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art of clinical trials at the time of the filing to modify the method of Zhang such that determining the metric comprises analyzing a spacing of the plurality of healthcare visits over time during the observation period, as taught by Nikpour, in order to reduce the difficulty in selection of patients for inclusion in trials, for example, when the clinical trial is for patient with systemic lupus erythematosus (SLE).
Regarding claim 4, Zhang as modified by Mandan does not appear to explicitly disclose wherein determining the metric comprises determining a degree to which the plurality of healthcare visits are irregularly spaced over time during the observation period.
Lokku teaches that it was old and well known in the art of SLE disease activity at the time of the filing that when determining disease activity/trajectory, irregular visits, and therefore the extent of irregularity needs to be considered and that the extent of irregularity can be quantified using a score which indicates the extent to which the plurality of healthcare visits are irregularly spaced over time during the observation period (Pages 20-21, section 2.3.2 and page 26, Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art of SLE disease activity at the time of the filing to modify the method of Zhang and Mandan to include determining a degree to which the plurality of healthcare visits are irregularly spaced over time during the observation period, as taught by Lokku, in order to determine a disease activity metric.
5. (Currently Amended) The computerized method of claim 1, wherein determining the metric comprises applying a non-linear compression function to a plurality of time intervals, the plurality of time intervals comprising at least each time interval between the plurality of healthcare visits, wherein the non-linear compression function compresses larger values more than smaller values.
6. (Original) The computerized method of claim 5, wherein the plurality of time intervals further comprises a beginning time interval between a beginning of the observation period and a first healthcare visit of the plurality of healthcare visits.
7. (Original) The computerized method of claim 6, wherein the plurality of time intervals further comprises an ending time interval between a last healthcare visit of the plurality of healthcare visits and an ending of the observation period.
8. (Currently Amended) The computerized method of claim 5, wherein determining the metric comprises determining a first value by summing the compressed plurality of time intervals.
9. (Currently Amended) The computerized method of claim 5, wherein determining the metric comprises determining a first value by summing the compressed plurality of time intervals, wherein time intervals between healthcare visits that occurred more recently in time are accorded greater weight than time intervals between healthcare visits that occurred less recently in time.
10. (Currently Amended) The computerized method of claim 5, wherein determining the metric comprises determining a second value by applying the non-linear compression function to a quotient of (i) a sum of the plurality of time intervals and (ii) a number of time intervals.
11. (Currently Amended) The computerized method of claim 5, wherein determining the metric comprises determining a second value by applying the non-linear compression function to a quotient of (i) a sum of the plurality of time intervals, wherein time intervals between healthcare visits that occurred more recently in time are accorded greater weight than time intervals between healthcare visits that occurred less recently in time and (ii) a number of time intervals.
12. (Currently Amended) The computerized method of claim 10, wherein determining the metric comprises multiplying the second value by the number of time intervals to generate a third value.
13. (Original) The computerized method of claim 12, wherein determining the metric comprises dividing the third value by the first value.
14. (Currently Amended) The computerized method of claim 5, wherein the non-linear compression function includes at least one of a logarithm function, a square root function, a cube root function, an inverse function, an arcsine function, and a Box-Cox function.
Regarding claim 15, Zhang does not disclose, but Nikpour teaches that it was old and well known in the art of clinical trials at the time of the invention to perform:
determining a number of the plurality of healthcare visits that occurred over a second time period; determining whether the number of the plurality of healthcare visits exceeds a visit threshold; and identifying the patient for inclusion in the clinical trial when the number of the plurality of healthcare visits exceeds the visit threshold and the metric exceeds the metric threshold (Nikpour, Page 1156, Discussion, left column, 1st paragraph, discusses that PAD is defined as a SLEDAI-2K score of ≥ 4 on ≥ 2 consecutive visits with a minimum interval between visits of 2 months. Page 1156, Discussion, right column, 1st paragraph, discusses that PAD may be an inclusion criterion for clinical trials. The PAD metric includes a visit threshold of ≥2 in a time period of >2 months and therefore, exceed the PAD metric threshold also exceed the visit threshold.) to reduce the difficulty in the selection of patients for inclusion in trials (Page 1152, Introduction, left column, 1st paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art of clinical trials at the time of the filing to modify the method of Zhang to include the limitations above, as taught by Nikpour, in order to reduce the difficulty in selection of patients for inclusion in trials, for example, when the clinical trial is for patient with systemic lupus erythematosus (SLE).
Regarding claim 16, Zhang as modified by Nikpour wherein the second time period is shorter than the observation period (Paragraph [0034], As used herein, the term “recent” when used with patient data can refer to patient data gathered within a certain time period. In some instances, the time period can be within a year. In other instances, the time period can be within six months. In further instances, the time period can be within three months. In still other instances, the time period can be within a month. In still other instances, the time period can be within two weeks. A time period of >2 months can be shorter that an observation period of 1 year. Also see Nikpour, Page 1153, Results, 1st paragraph, The minimum and maximum time intervals between SLEDAI-2K values used to diagnose flare and PAD in 2004 and 2005 were 2.1 and 9.5 months, and 2.0 and 9.8 months, respectively.)
Regarding claim 17, Zhang as modified by Nikpour further discloses wherein the metric is indicative of a disease flare of a disease of the patient (Nikpour, Page 1156, Discussion, left column, 1st paragraph, Based on this study, we defined flare as an increase in SLEDAI-2K score of ≥4 from the previous visit, with a minimum interval between visits of 2 months. Based on our definition of flare, we defined PAD as a SLEDAI-2K score of ≥4, excluding serology alone, on ≥2 consecutive visits with a minimum interval between visits of 2 months.).
Subject Matter Allowable Over the Prior Art
Claims 4-14 are determined to be allowable over the prior art. Regarding claim 4, the prior art does not disclose “wherein determining the metric comprises determining a degree to which the plurality of healthcare visits are irregularly spaced over time during the observation period”. Lokku (Summary Measures for Quantifying the Extent of Visit Irregularity in Longitudinal Data) discloses quantifying the extent of irregular patient visits using a AUC score, but it is applicable to study data and not to individual patient visit data for determining whether a patient should included in a clinical trial. Regarding claim 5, the prior art does not disclose “wherein determining the metric comprises applying a non-linear compression function to a plurality of time intervals, the plurality of time intervals comprising at least each time interval between the plurality of healthcare visits, wherein the non-linear compression function compresses larger values more than smaller values”. Lokku (Summary Measures for Quantifying the Extent of Visit Irregularity in Longitudinal Data) discloses quantifying the extent of irregular patient visits using a AUC score but does not disclose that the AUC score the non-linear compression function.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ibanez et al. (Summarizing disease features over time: I. Adjusted mean SLEDAI derivation and application to an index of disease activity in lupus) discuss determining a AMS metric based on the times of the plurality of healthcare visits of the patient over time during the observation period.
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/DEVIN C HEIN/Examiner, Art Unit 3686