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 Claims
Claims 1-27 were originally filed for examination and pending on November 20, 2023. Also, on November 20, 2023, Applicant filed a preliminary amendment, where Applicant amended claims 3-8, 13-17, and 20-27. On March 2, 2026, claims 1-27 were subject to a restriction/election requirement (the “March 2, 2026 Restriction/Election Requirement”). On April 8, 2026, Applicant elected claims 1-9 and claims 12-24 (Invention I) without traverse, in a response to the March 2, 2026 Restriction/Election Requirement (the “April 8, 2026 Response to Restriction Requirement”). As such, pursuant to the April 8, 2026 Response to Restriction Requirement, claims 1-27 as preliminarily amended in the amendment filed on November 20, 2023 are currently pending: of which (i) claims 1-9 and 12-24 are elected and examined; and (ii) claims 10, 11, and 25-27 are non-elected and withdrawn from consideration. Claims 1-9 and 12-24, as preliminarily amended on November 20, 2023, are subject to the non-final office action below.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the non-English application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on November 20, 2023 is in compliance with the provisions of 37 CFR 1.97, and has been considered by the examiner.
Claim Rejections - 35 USC § 112(b)
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-8, 12-17, and 19-24 are 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.
Claims 2, 12, and 19 recite the limitation "the group classified as having a high incidence risk" in line 2 of . However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). The only classified groups described in the independent claims refer to (1) those susceptible to a specific disease and (2) those not susceptible to the specific disease: none of the classified groups refer to “those having a high incidence risk”. Therefore, there is insufficient antecedent basis for the limitation directed to “the group classified as having a high incidence risk” in claims 2, 12, and 19.
Claims 3, 13, and 20 recite the limitation "both of the […] determination of degrees are performed" in line. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). The step(s) described in independent claims 1, 9, and 18 refer to a classification step comprising performing classification into (1) a group of those susceptible to a specific disease and (2) a group of those not susceptible to the specific disease (see claims 1, 9, and 18); and executing inference based on knowledge stored in a knowledge storage unit to generate disease risk evaluation information (see claim 18). The claims do not describe a step directed to determining degrees of any kind.
Further, claims 3, 13, and 20 recite the limitation “kinds of data used for determination then are changed”. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). None of claims 3, 13, and 20 or independent claims 1, 9, and 18 describe a limitation directed to data being used for any type of determination. Therefore, it is not clear how data is changed, because the claims do not previously describe the collection or use of any data. As such, there is insufficient antecedent basis for the limitations directed to “both of the […] determination of degrees are performed” and “kinds of data used for determination are then changed” in claims 3, 13, and 20.
Claims 4, 14, and 21 recite the limitation "a dataset used for" in line. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). First, the step(s) described in independent claims 1, 9, and 18 refer to a classification step comprising performing classification into (1) a group of those susceptible to a specific disease and (2) a group of those not susceptible to the specific disease (see claims 1, 9, and 18); and executing inference based on knowledge stored in a knowledge storage unit to generate disease risk evaluation information (see claim 18). The claims do not describe the classified groups being based on incidence risk (i.e., the classified groups do not refer to “those having a high incidence risk” or “those having a low incidence risk”).
Further, claims 1, 9, and 18 do not refer to the collection or use of any data or data set. Therefore, it is not clear how values in a data set can change according to “the degrees” or how such data can be excluded from a classification according to incidence risk, because the claims do not previously describe the collection or use of any data set or the classification into groups according to incidence risk. As such, claims 4, 14, and 21 are indefinite for these reasons.
Claims 5, 15, and 22 recite the limitation "wherein data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low" in line. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). The only classified groups described in the independent claims refer to (1) those susceptible to a specific disease and (2) those not susceptible to the specific disease: none of the classified groups are based on incidence risk (i.e., the classified groups do not refer to “those having a high incidence risk” or “those having a low incidence risk”). Therefore, there is insufficient antecedent basis for the limitation directed to “wherein data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low” in claims 5, 15, and 22.
Claims 6, 16, and 23 recite the limitation "wherein data-driven analysis means used for determination of the degrees" in line. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). While claims 1, 9, and 18 imply that a degree of progression of a disease is disregarded from the classification step, the claims do not actually recite a step for determining any kind of degrees. Therefore, there is insufficient antecedent basis for the limitation directed to “wherein data-driven analysis means used for determination of the degrees” in claims 6, 16, and 23.
Claim 7 recites the limitation "wherein gene information is not included in data sets" in line. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). Claims 1 and 7 do not describe any data sets. Therefore, it is not clear how gene information can be excluded from data sets, when the claims do not describe any data sets. Therefore, there is insufficient antecedent basis for the limitation directed to “wherein gene information is not included in data sets” in claim 7.
Lastly, claims 8, 17, and 24 recite the limitation "wherein," in line. However, there is insufficient antecedent basis for this limitation in the claims. See MPEP § 2173.05(e). The only classified groups described in the independent claims refer to (1) those susceptible to a specific disease and (2) those not susceptible to the specific disease: none of the classified groups are based on incidence risk (i.e., the classified groups do not refer to “those having a high incidence risk” or “those having a low incidence risk”). Further, the independent claims do not describe a step for presenting any information/data. Therefore, there is insufficient antecedent basis for the limitation directed to “” in claims 8, 17, and 24.
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 1-9 and 12-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. See MPEP § 2106 (hereinafter referred to as the “2019 Revised PEG”).
Step 1 of the Alice/Mayo Test
Following Step 1 of the 2019 Revised PEG, claims 1-9 and 12-17 are directed to a disease risk evaluation method or system, which are within one of the four statutory categories (i.e., a process or a machine or apparatus). See MPEP § 2106.03. Claims 18-24 are directed to a health information processing device, which is also within one of the four statutory categories (i.e., a manufacture). See id.
Step 2A of the 2019 Revised PEG - Prong One
Following Prong One of Step 2A of the 2019 PEG, the claim limitations are to be analyzed to determine whether they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. See MPEP §2106.04. An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: (1) Mathematical Concepts; (2) Certain Methods of Organizing Human Activity, and (3) Mental Processes. See MPEP § 2106.04(a).
Claims 1-9 and 12-24 are rejected under 35 U.S.C. § 101, because the claimed invention is directed to an abstract idea without significantly more. Representative independent claims 1, 9, and 18 include limitations that recite an abstract idea. Note that independent claim 1 is directed to a disease risk evaluation method, while claim 9 covers the matching disease risk evaluation system, and claim 18 is directed to a similar health information processing device. Specifically, independent claim 9 recites the following limitations:
A disease risk evaluation system, wherein a disease risk evaluation method comprises a step of performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease.
Similarly, independent claim 18 recites the following limitations:
A health information processing device, wherein
a disease risk evaluation method comprises a step of performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease; and
the health information processing device comprises a processor, the processor executing inference based on knowledge stored in a knowledge storage unit to generate disease risk evaluation information.
However, the Examiner submits that the foregoing underlined limitations constitute a process that, under its broadest reasonable interpretation, falls within the “Mental Processes” grouping of abstract ideas. See 2019 Revised PEG. The Mental Processes category covers concepts which are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper (including an observation, evaluation, judgment, or opinion) (i.e., a disease risk evaluation method, comprising: performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease; and generating disease risk evaluation information). See MPEP § 2106.04(a)(2)(III). That is, other than reciting some computer components and functions (the foregoing limitations in claims 9 and 18 which are not underlined), the context of claims 1, 9, and 18 encompass concepts that are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper (including an observation, evaluation, judgment, and/or opinion) (i.e., a disease risk evaluation method, comprising: performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease; and generating disease risk evaluation information).
The aforementioned claim limitations described in claims 1, 9, and 18 are analogous to claim limitations directed toward concepts which are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper, because they merely recite limitations which encompass a person mentally and/or manually: (1) performing classification of subjects into two groups: (i) a group of those susceptible to a specific disease; and (ii) a group of those not susceptible to the specific disease (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could mentally separate people into two different groups based on certain criteria); and (2) generating disease risk evaluation information (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could mentally generate disease risk evaluation information, such as writing the subjects in two aforementioned groups).
Therefore, the aforementioned underlined claim limitations may reasonably be interpreted as mental/manual observations, evaluations, judgments, and/or opinions made by a person, such as a healthcare professional. If a claim limitation, under its broadest reasonable interpretation, covers concepts which are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper, then it falls within the “Mental Processes” grouping of abstract ideas. See 2019 Revised PEG. Accordingly, claims 1, 9, and 18 recite an abstract idea that falls within the Mental Processes category.
Furthermore, Examiner notes that dependent claims 2-4, 6-8, 12-14, 16, 17, 19-21, 23, and 24 further define the at least one abstract idea (and thus fail to make the abstract idea any less abstract) as set forth below. Examiner notes that: (1) dependent claims 5, 6, 15, 16, 22, and 23 include limitations that are deemed to be additional elements, and require further analysis under Prong Two of Step 2A; and (2) dependent claims 2-4, 7, 8, 12-14, 17, 19-21, and 24 do not provide any limitations that are deemed to be additional elements which require further analysis under Prong Two of Step 2A.
- For example, claims 2, 12, and 19 describes further mental concepts directed to showing degrees for the group classified as having a high incidence risk. This step is deemed to be part of the abstract mental process, because showing degrees (such as percentages or probabilities) for a group classified as having a high incidence risk could reasonably and simply comprise a person manually writing down any threshold percentage number/probability value for that group/category of subjects on a piece of paper.
- Next, claims 3, 13, and 20 describe further limits on the abstract idea, by indicating that the kinds of data that is used for making classifications and determinations is changed. This is deemed to be part of the abstract mental process, because this limitation merely modifies the data that is used to perform the mental steps of classifying data and making some determination of the data.
- Claims 4, 14, 7, and 21 describe further limits on the abstract idea, by indicating that (1) the certain kinds of data that is used for the classification is excluded from the determination of the degrees (see claims 4, 14, and 21); and (2) gene information is not included in the data sets. These steps are deemed to be part of the abstract mental process, because these limitations also merely modify the data that is used to perform the mental steps of classifying the data and making some determination of the data.
- Claims 6, 16, and 23 include a further mental/manual step for changing values according to the degrees. This step is deemed to be part of the abstract mental process, because this limitation merely modifies the data that is used to perform the mental steps of changing the data that is used the determination of the degrees. However, Examiner notes that claims 6, 16, and 23 include a limitation that are deemed to be additional elements and require further analysis under Prong Two of Step 2A.
- Lastly, claims 8, 17, and 24 include further mental/manual steps for normalizing the degrees of incidence and displaying the degrees either in a radar chart (see claim 8) or with a score (see claims 17 and 24). These steps are deemed to be part of the abstract mental process, because these limitations merely modify the data by changing it into a uniform format and displaying it on a chart or through a score.
Step 2A of the 2019 Revised PEG – Prong Two
Regarding Prong Two of Step 2A of the 2019 Revised PEG, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. As noted in the 2019 Revised PEG, it must be determined whether any additional elements in the claims are indicative of integrating the abstract idea into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” See MPEP §§ 2106.05 (f)-(h).
In the present case, for independent claim 9, the additional limitations beyond the above-noted at least one abstract idea are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
A disease risk evaluation system (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)), wherein a disease risk evaluation method comprises a step of performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease.
Similarly, for independent claim 18 the additional limitations beyond the above-noted at least one abstract idea are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
A health information processing device (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)), wherein
a disease risk evaluation method comprises a step of performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease; and
the health information processing device comprises a processor (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)), the processor executing inference based on knowledge stored in a knowledge storage unit (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)) to generate disease risk evaluation information.
However, the recitation of these generic computer components and functions in claims 1, 9, and 18 are recited at a high-level of generality (i.e., using generic computer devices and software to perform the abstract mental process of: a disease risk evaluation method, comprising: performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease; and generating disease risk evaluation information), such that it amounts to no more than: (1) adding the words “apply it” (or is the equivalent of) with the judicial exception; mere instructions to implement an abstract idea on a computer; or merely uses a computer as a tool to perform an abstract idea; (2) adding insignificant extra-solution activity to the judicial exception; and (3) generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP § 2106.05(f)-(h). For the following reasons, the Examiner submits that the above identified additional limitations do not integrate the above-noted at least one abstract idea into a practical application.
- The following are examples of court decisions that demonstrate merely applying instructions by reciting the computer structure as a tool to implement the claimed limitations (e.g., see MPEP § 2106.05(f)):
- Invoking computers or other machinery merely as a tool to perform an existing process, e.g. see, Affinity Labs v. DirecTV – similarly, the current invention invokes computers (i.e., the disease risk evaluation system, the health information processing device, and processor) and other machinery to perform the existing process of generating the scores and the image with the scores.
- Requiring the use of software to tailor information and provide it to the user on a generic computer, e.g. see, Intellectual Ventures I LLC v. Capital One Bank – similarly, the current invention merely requires the inference executed by the processor and stored on the knowledge storage unit, to ultimately perform the abstract mental process of performing the classifications and generating the disease risk evaluation, as described in claim 1, 9, and 18.
Thus, the additional elements in independent claims 1, 9, and 18 are not indicative of integrating the judicial exception into a practical application. Similarly, dependent claims 2-4, 7, 8, 12-14, 17, 19-21, and 24 do not recite any additional elements outside of those identified as being directed to the abstract idea (or those additional elements which were already identified and analyzed in claims 1, 9, and 18), described above. Examiner notes that dependent claims 5, 6, 15, 16, 22, and 23 recite the following additional elements identified in bold font below (with limitations deemed to be part of the above identified abstract idea identified in underlined font):
wherein data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low is semi-supervised clustering or unsupervised clustering (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and generally linking the abstract idea to a particular field of use, as noted below, see MPEP § 2106.05(h)) (as described in claim 5, 15, and 22); and
wherein data-driven analysis means used for determination of the degrees is realized by using supervised learning (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and generally linking the abstract idea to a particular field of use, as noted below, see MPEP § 2106.05(h)) and such data that values change according to the degrees (as described in claims 6, 16, and 23).
As such, the additional elements in claims 1, 5, 6, 9, 15, 16, 18, 22, and 23 are not indicative of integrating the judicial exception into a practical application. Looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, unlike the claims that have been held as a whole to be directed to an improvement or otherwise directed to something more than the abstract idea, claims 1-9 and 12-24: (1) are not directed to improvements to the functioning of a computer, or to any other technology or technical field similar to the Enfish, LLC v. Microsoft Corp. case (see MPEP § 2106.05(a)); (2) do not apply or use a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (see MPEP § 2106.04(d)(2)); (3) do not apply the judicial exception with, or by use of, a particular machine (see MPEP § 2106.05(b)); (4) do not effect a transformation or reduction of a particular article to a different state or thing (see MPEP § 2106.05(c)); nor do they (5) apply or use 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 whole is more than a drafting effort designed to monopolize the exception (see MPEP § 2106.05(e) and MPEP § 2106.04(d)(2)). For these reasons, claims 1-9 and 12-24 do not recite additional elements that integrate the judicial exception into a practical application.
Step 2B of the 2019 Revised PEG
Regarding Step 2B of the 2019 Revised PEG, claims 1-9 and 12-24 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 abstract idea into a practical application, the additional elements of claims 1-9 and 12-24 amount to no more than: (1) adding the words “apply it” (or is the equivalent of) with the judicial exception; mere instructions to implement an abstract idea on a computer; or merely uses a computer as a tool to perform an abstract idea; (2) adding insignificant extra-solution activity to the judicial exception; and (3) generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP §§ 2106.05(f)-(h). Further the additional elements, other than the abstract idea per se, when considered both individually and as an ordered combination, amount to no more than limitations consistent with what the courts recognize, or those having ordinary skill in the art would recognize, to be well-understood, routine, and conventional computer components. See MPEP § 2106.05 (d).
Specifically, the Examiner submits that the additional elements of claims 1-9 and 12-24, as recited, the disease risk evaluation system; health information processing device; processor executing inference based on knowledge stored in a knowledge storage unit; and the steps directed to: “wherein data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low is semi-supervised clustering or unsupervised clustering”; and “wherein data-driven analysis means used for determination of the degrees is realized by using supervised learning”, are well-understood, routine, and conventional functions. See MPEP § 2106.05(d)(II).
- In regard to the disease risk evaluation system; health information processing device; processor executing inference based on knowledge stored in a knowledge storage unit; and the steps directed to: “wherein data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low is semi-supervised clustering or unsupervised clustering”; and “wherein data-driven analysis means used for determination of the degrees is realized by using supervised learning”, these additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than well-understood, routine, and conventional activities previously known to the industry, because:
- Applicant’s disclosure supports this assertion. For example, Applicant discloses that that the disease risk evaluation system is provided with a data processing unit and a database. See Applicant’s specification as filed on November 20, 2023, paragraph [0050]. These descriptions in the specification describe these additional elements as basic computer components and functions, such as well-understood, routine, and conventional computer components. Therefore, the Examiner submits that these computer components and functions represent well-understood, routine, and conventional computer components and functions which are known in the medical industry.
- The Examiner submits that these limitations amount to merely using a computer or other machinery as tools for performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f) and analysis of these limitations under Step 2A, Prong Two above).
- The Examiner submits that these limitations generally link the use of the judicial exception to a particular technological environment or field of use – for example, the limitations directed to: “wherein data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low is semi-supervised clustering or unsupervised clustering”; and “wherein data-driven analysis means used for determination of the degrees is realized by using supervised learning”, amount to limiting the abstract idea to the field of machine learning (see MPEP § 2106.05(h) and analysis of these limitations under Step 2A, Prong Two above).
Therefore, the additional elements described in claims 1-9 and 12-24 are deemed to be additional elements which do not amount to significantly more than the abstract idea identified above. Thus, taken alone, the additional elements of claims 1-9 and 12-24 do not amount to significantly more than the above-identified judicial exception (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 improves the functionality of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation. Therefore, whether taken individually or as an ordered combination, claims 1-9 and 12-24 are nonetheless rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5, 6, 9, 12, 13, 15, 16, 18-20, 22, and 23 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by:
- Chittenden et al. (Pub. No. US 2020/0327962).
Regarding claims 1 and 9,
- Chittenden et al. (Pub. No. US 2020/0327962) discloses:
- a disease risk evaluation method comprising (as described in claim 1) (Chittenden, paragraph [0033]; Paragraph [0033] discloses methods for classifications of multiple human tumor type designations, independent of tissue-specific annotation, to identify known and previously undescribed integrated molecular signatures of pan-cancer etiology and patient survival.); and a disease risk evaluation system (Chittenden, paragraph [0033]; Paragraph [0033] discloses systems for classifications of multiple human tumor type designations, independent of tissue-specific annotation, to identify known and previously undescribed integrated molecular signatures of pan-cancer etiology and patient survival.), wherein a disease risk evaluation method comprises (as described in claim 9) (Chittenden, paragraph [0033]; Paragraph [0033] discloses methods with the systems.):
- a step of performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease (as described in claims 1 and 9) (Chittenden, paragraphs [0097] and [0230]; Paragraph [0097] discloses that all samples were stratified into 3 risk quantiles (i.e., a step of performing classification) (low (i.e., classifying a group of those not susceptible to the specific disease), moderate, and high (i.e., classifying a group of those susceptible to the specific disease). Paragraph [0230] discloses that the high-risk patients are those that have a poor prognosis of early or late stage cancer (i.e., the high risk group is interpreted as the equivalent of classifying a group of those susceptible to the specific disease, regardless of a degree of progression of the disease, because the risk category is a reflection of the predicted prognosis of cancer recurrence or death based on prognostic variables regardless of what stage of cancer the patient has – likewise, the low risk group is interpreted as the equivalent of classifying a group of those who are not susceptible to the specific disease, regardless of a degree of progression of the disease).).
Regarding claim 18,
- Chittenden et al. (Pub. No. US 2020/0327962) discloses:
- a health information processing device, wherein:
- a disease risk evaluation method (Chittenden, paragraph [0033]; Paragraph [0033] discloses methods with the systems.) comprises a step of performing classification into a group of those susceptible to a specific disease and a group of those not susceptible to the specific disease, regardless of a degree of progression of the disease from a healthy stage until after onset of the disease (Chittenden, paragraphs [0097] and [0230]; Paragraph [0097] discloses that all samples were stratified into 3 risk quantiles (i.e., a step of performing classification) (low (i.e., classifying a group of those not susceptible to the specific disease), moderate, and high (i.e., classifying a group of those susceptible to the specific disease). Paragraph [0230] discloses that the high-risk patients are those that have a poor prognosis of early or late stage cancer (i.e., the high risk group is interpreted as the equivalent of classifying a group of those susceptible to the specific disease, regardless of a degree of progression of the disease, because the risk category is a reflection of the predicted prognosis of cancer recurrence or death based on prognostic variables regardless of what stage of cancer the patient has – likewise, the low risk group is interpreted as the equivalent of classifying a group of those who are not susceptible to the specific disease, regardless of a degree of progression of the disease).); and
- the health information processing device comprises a processor (Chittenden, paragraph [0283]; Paragraph [0283] discloses that the invention is implemented by a computer system/server, such as personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices.), the processor executing inference based on knowledge stored in a knowledge storage unit to generate disease risk evaluation information (Chittenden, paragraphs [0234] and [0235] disclose that the system makes risk determinations by utilizing multinomial models and comparing data related to 22 cancer types from a TCGA [The Cancer Genome Atlas] database (i.e., the processor executes inferences based on knowledge stored in a knowledge storage unit to generate disease risk evaluation information).).
Regarding claims 2, 12, and 19,
- Chittenden discloses the limitations of: claim 1 (which claim 2 depends on); claim 9 (which claim 12 depends on); and claim 18 (which claim 19 depends on), as described above.
- Chittenden further discloses a method, system, and device, comprising:
- a function of showing degrees for the group classified as having a high incidence risk (as described in claims 2, 12, and 19) (Chittenden, paragraph [0276]; Paragraph [0276] discloses that the survival models showed clearly delimited risk groups, with the high-risk groups having less than ˜60% survival by 30 months (i.e., showing degrees for the group classified as having a high incidence risk) compared to greater than 85% survival in the lower risk group.).
Regarding claims 3, 13, and 20,
- Chittenden discloses the limitations of: claim 1 (which claim 3 depends on); claim 9 (which claim 13 depends on); and claim 18 (which claim 20 depends on), as described above.
- Chittenden further discloses a method, system, and device, wherein:
- both of the classification into the groups and determination of the degrees are performed (Chittenden, paragraph [0276]; Paragraph [0276] discloses that the survival models showed clearly delimited risk groups, with the high-risk groups having less than ˜60% survival by 30 months compared to greater than 85% survival in the lower risk group (i.e., the system determines degrees of risk for each classified group).)., and kinds of data used for determination then are changed (as described in claims 3, 13, and 20) ) (Chittenden, paragraph [0227]; Paragraph [0227] discloses that the patient’s response [to treatment] may be recorded in a quantitative fashion like percentage change in tumor volume or cellularity or using a semi-quantitative scoring system (i.e., the kinds of data used for the determination of the degrees of risk are changed).).
Regarding claims 5, 15, and 22,
- Chittenden discloses the limitations of: claim 1 (which claim 5 depends on); claim 9 (which claim 15 depends on); and claim 18 (which claim 22 depends on), as described above.
- Chittenden further discloses a method, system, and device, wherein:
- data-driven analysis means used for determination of the classification into the groups according to whether the incidence risk is high or low is semi-supervised clustering or unsupervised clustering (as described in claims 5, 15, and 22) (Chittenden, paragraph [0052]; Paragraph [0052] discloses that various supervised and unsupervised machine learning (i.e., various unsupervised clustering techniques are used for the determinations of the classification into the groups) methods may be used in accordance with the present disclosure, including LASSO, Support Vector Machines, K-nearest-neighbor, Multivariate Partial Least Squares and Discriminant Analysis, Principal Component Analysis, Correspondence Analysis, and K-Means/K-Medians and Hierarchical clustering.).
Regarding claims 6, 16, and 23,
- Chittenden discloses the limitations of: claim 1 (which claim 5 depends on); claim 9 (which claim 15 depends on); and claim 18 (which claim 22 depends on), as described above.
- Chittenden further discloses a method, system, and device, wherein:
- data-driven analysis means used for determination of the degrees is realized by using supervised learning (as described in claims 6, 16, and 23) (Chittenden, paragraph [0052]; Paragraph [0052] discloses that various supervised (i.e., supervised learning techniques may be used for the determinations of the degrees of risk) and unsupervised machine learning methods may be used in accordance with the present disclosure, including LASSO, Support Vector Machines, K-nearest-neighbor, Multivariate Partial Least Squares and Discriminant Analysis, Principal Component Analysis, Correspondence Analysis, and K-Means/K-Medians and Hierarchical clustering.) and such data that values change according to the degrees (as described in claims 6, 16, and 23) (Chittenden, paragraph [0227]; Paragraph [0227] discloses that the patient’s response [to treatment] may be recorded in a quantitative fashion like percentage change in tumor volume or cellularity or using a semi-quantitative scoring system (i.e., data values change according to the degrees of risk).).
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.
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 4, 7, 8, 14, 17, 21, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over:
- Chittenden et al. (Pub. No. US 2020/0327962), in view of:
- Colley et al. (Pub. No. US 2021/0090694).
Regarding claims 4, 14, and 21,
- Chittenden et al. (Pub. No. US 2020/0327962) discloses the limitations of: claim 1 (which claim 4 depends on); claim 9 (which claim 14 depends on); and claim 18 (which claim 21 depends on), as described in the Claim Rejections - 35 U.S.C. § 102 Section above.
- Chittenden does not explicitly teach, however, in analogous art of disease classification systems, methods, and devices, Colley et al. (Pub. No. US 2021/0090694) teaches a cancer research, diagnosis, and treatment analysis method, system, and device, wherein:
- in comparison with a dataset used for classification according to the degrees, a dataset used for determination of the classification into the groups according to whether the incidence risk is high or low is a dataset from which such data that values change according to the degrees are excluded to perform the classification according to the incidence risk (as described in claims 4, 14, and 21) (Colley, paragraph [3035]; Paragraph [3035] generally teaches that genes associated with immunotherapy were excluded from the cancer expression profile analysis (i.e., values that changed according to the degrees are excluded from the classification of the incidence risk). Paragraph [3035] teaches that this feature is beneficial for determining over-expression and under-expression of certain cancer types.).
Therefore, it would have been obvious to one of ordinary skill in the art of disease classification systems, methods, and devices at the time of the effective filing date of the claimed invention to modify the method, system, and device for classifications of multiple human tumor type designations taught by Chittenden, to incorporate a step and feature directed to excluding certain data where values change according to the degrees of risk from the classification of incidence risk analysis, as taught by Colley, in order to determine over-expression and under-expression of certain cancer types. See Colley, paragraph [3035]; see also MPEP § 2143 G.
Regarding claim 7,
- Chittenden et al. (Pub. No. US 2020/0327962) discloses the limitations of: claim 1 (which claim 7 depends on), as described in the Claim Rejections - 35 U.S.C. § 102 Section above.
- Chittenden does not explicitly teach, however, in analogous art of disease classification systems, methods, and devices, Colley et al. (Pub. No. US 2021/0090694) teaches a cancer research, diagnosis, and treatment analysis method, wherein:
- gene information is excluded in data sets (Colley, paragraph [3035]; Paragraph [3035] generally teaches that genes associated with immunotherapy were excluded from the cancer expression profile analysis (i.e., gene information is excluded in data sets). Paragraph [3035] teaches that this feature is beneficial for determining over-expression and under-expression of certain cancer types.).
Therefore, it would have been obvious to one of ordinary skill in the art of disease classification systems, methods, and devices at the time of the effective filing date of the claimed invention to modify the method, system, and device for classifications of multiple human tumor type designations taught by Chittenden, to incorporate a step and feature directed to excluding gene information in its analysis, as taught by Colley, in order to determine over-expression and under-expression of certain cancer types. See Colley, paragraph [3035]; see also MPEP § 2143 G.
Regarding claim 8,
- Chittenden et al. (Pub. No. US 2020/0327962) discloses the limitations of claim 1 (which claim 8 depends on), as described in the Claim Rejections - 35 U.S.C. § 102 Section above.
- Chittenden does not explicitly teach, however, in analogous art of disease classification systems, methods, and devices, Colley et al. (Pub. No. US 2021/0090694) teaches a cancer research, diagnosis, and treatment analysis method, system, and device, wherein:
- in presentation of whether the incidence risk is high or low and degrees of incidence, each of the degrees of incidence is normalized (Colley, paragraph [2174]; Paragraph [2174] generally teaches a normalization framework is used to multiple datasets, where when decreased gene sequence length and lower sequencing depth decreases the likelihood of gene-level sequence read detection and quantification (i.e., data related to the determination of the degrees of incidence), the normalization process multiplies the reads by a correction factor that adjusts the number of reads to better reflect the actual number of molecular copies of those sequences in the sample (i.e., the degrees of incidence are normalized).), and a radar chart is used to display each of the degrees (as described in claim 8) (Colley, paragraph [2611]; Paragraph [2611] teaches that a comparative display may be presented to a user in order to compare a particular member of a dataset with other members of the dataset which share similarities, and that such a comparative display is known as a radar plot (i.e., a radar chart is used to display each of the degrees). Paragraph [2611] teaches that this feature is beneficial for displaying similar or distinct indicators such as additional dots around the center indicator.).
Therefore, it would have been obvious to one of ordinary skill in the art of disease classification systems, methods, and devices at the time of the effective filing date of the claimed invention to modify the method, system, and device for classifications of multiple human tumor type designations taught by Chittenden, to incorporate a step and feature directed to excluding certain data where values change according to the degrees of risk from the classification of incidence risk analysis, as taught by Colley, in order to display other members with similar or distinct indicators such as additional dots around the center indicator. See Colley, paragraph [2611]; see also MPEP § 2143 G.
Regarding claims 17 and 24,
- Chittenden et al. (Pub. No. US 2020/0327962) discloses the limitations of: claim 9 (which claim 17 depends on); and claim 18 (which claim 24 depends on), as described in the Claim Rejections - 35 U.S.C. § 102 Section above.
- Chittenden does not explicitly teach, however, in analogous art of disease classification systems, methods, and devices, Colley et al. (Pub. No. US 2021/0090694) teaches a cancer research, diagnosis, and treatment analysis method, system, and device, wherein:
- in presentation of whether the incidence risk is high or low and degrees of incidence, each of the degrees of incidence is normalized (Colley, paragraph [2174]; Paragraph [2174] generally teaches a normalization framework is used to multiple datasets, where when decreased gene sequence length and lower sequencing depth decreases the likelihood of gene-level sequence read detection and quantification (i.e., data related to the determination of the degrees of incidence), the normalization process multiplies the reads by a correction factor that adjusts the number of reads to better reflect the actual number of molecular copies of those sequences in the sample (i.e., the degrees of incidence are normalized).), and a score is used to display each of the degrees (as described in claims 17 and 24) (Colley, paragraphs [2099] and [2134]; Paragraph [2099] teaches that a scoring model is trained to use a propensity score with survival or time-to-event outcomes, such as a time until death, time until progression of the first condition, or time until an adverse event associated with the first condition is incurred (i.e., a score is displayed with the degree of incidence data). Paragraph [2134] teaches that this feature is beneficial for determining which subjects to select from an identified treatment and control cohort.).
Therefore, it would have been obvious to one of ordinary skill in the art of disease classification systems, methods, and devices at the time of the effective filing date of the claimed invention to modify the method, system, and device for classifications of multiple human tumor type designations taught by Chittenden, to incorporate a step and feature directed to excluding certain data where values change according to the degrees of risk from the classification of incidence risk analysis, as taught by Colley, in order to determine which subjects to select from an identified treatment and control cohort. See Colley, paragraph [2134]; see also MPEP § 2143 G.
Conclusion
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/N.A.A./Examiner, Art Unit 3686
/JONATHON A. SZUMNY/Primary Examiner, Art Unit 3686
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