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 .
Applicant’s Amendment/Request for Reconsideration-After Non-Final Rejection, filed 7/6/2026, has been entered and fully considered.
Information Disclosure Statement
The IDS filed 07/7/2026 has been considered and entered. Consequently, a 1449 form is attached.
Status of Claims
Claim 3-6, 9-10, 12, 14, 20, 22 are cancelled.
Claims 1-2, 7-8, 11, 13, 15-19, 21 and 23-29 are pending and examined on the merits.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. Priority of US application REPUBLIC OF KOREA 10-2023-0109872 filed 08/22/2023 is acknowledged.
Withdrawn Rejections/Objections
The rejections to claims 1-2, 7-8, 11, 13, 15-19, 21 and 23-24 under 35 U.S.C. 112(a) in the Office Action mailed 15 April 2026 are withdrawn in view of claim amendment filed 7/6/2026.
The rejection to claims 1-2, 7-8, 11, 13, 15-19, 21 and 23-29 under 35 U.S.C. § 112(b) in the Office Action mailed 15 April 2026 are withdrawn in view of claim amendment filed 7/6/2026.
Claim Rejections - 35 USC § 101
This rejection is maintained from the 4/15/2026 Office action. Modifications are necessitated by claim amendment filed 7/6/2026.
The instant rejection is maintained from the previous Office action.
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 7-8, 11, 13, 15-19, 21 and 23-29 are rejected under 35 USC 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Process, Machine, Manufacture or Composition
Claims 1-2, 7-8, 11, 13, 15-19, 21 and 23-24 are directed to a process, here a "method," for detecting minimal residual disease and adapting treatment in response to that minimum residual disease.
Claims 25-27 are directed to another process, here another "method," for detecting minimal residual disease and adapting treatment in response to that minimum residual disease.
Claims 28-29 are directed to a third process, here a third "method," for detecting minimal residual disease and adapting treatment in response to that minimum residual disease.
Step 2A Prong One: Identification of an Abstract Idea
The claims recite:
Detecting, by the one or more processors and based on the first sequencing data, the second sequencing data, and the third sequencing data, a minimal residual disease for the patient by (claims 1, 25 and 28):
This step recites detecting disease based on first, second and third sequencing data, which is interpreted as a series of judgements and decision-making with respect to the data sets, that can be achieved in human mind. Therefore this step equates to an abstract idea of a mental processes;
Identifying tumor tissue mutation information of the patient by comparing the first sequencing data and the second sequencing data, wherein the tumor tissue mutation information comprises a number of tumor tissue mutations of the patient (claims 1, 25 and 28);
This step recites identifying a number of tumor tissue mutations of the patient, which is interpreted as a series of judgement and decision-making with respect to the data comparison of the two sequencing data sets, that can be achieved in human mind. Therefore this step equates to an abstract idea of a mental processes;
Calculating, based on the number of tumor tissue mutations of the patient and based on an average sequencing depth of the third sequencing data, a limit of detection for the patient (claims 1, 25 and 28);
This step recites a calculation operation with inputs and an output, which equates to an abstract idea of mathematical concepts.
Performing, using genetic data associated with a plurality of sample patients who are distinct from the patient, background error filtering on the identified tumor tissue mutation information (claims 1, 25 and 28);
This step recites comparing detected mutation information against background information and filtering background information, which can be achieved in human mind. Therefore this step equates to an abstract idea of mental processes.
Calculating, based on the filtered tumor tissue mutation information, a tumor cell fraction for the patient (claims 1, 25 and 28);
This step recites calculating, which is a mathematical operation. Therefore this step equates to an abstract idea of mathematical concepts.
Correcting, using the genetic data, the tumor cell fraction (claims 1, 25 and 28);
This step recites correcting on the cell fraction (by another data), which is a mathematical operation. Therefore this step equates to an abstract idea of mathematical concepts.
Determining, based on the limit of detection and the corrected tumor cell fraction, whether the patient has tumor recurrence (claims 1, 25 and 28);
This step recites a series of judgement and decision-making with respect to the data comparison of data sets, that can be achieved in human mind. Therefore this step equates to an abstract idea of a mental processes;
Dependent claims further describe data, data analytical details, and therapy choices.
Step 2A Prong Two: Consideration of Practical Application
Claim 1 results in a process of computerized “performing” of additional treatment and/or surgery. Claim 1 does recite an additional elements. The recitation of performing actions based on the model output is particular in claim 1. However, the determined “tumor recurrence” is not integrated into the next step “receiving, from a trained machine learning model implemented using an artificial neural network and in response to input corresponding to the minimal residual disease, output indicating a recommendation associated with one or more of” in all the three independent claims 1, 25 and 28. In another words, the treatment or therapy pertains to the MRD but the MRD is disconnected to the “tumor recurrence”. However, “collection of a tumor biopsy sample” and “collection of blood sample” are not treatments.
Additionally, claim 28 result in alternative embodiments of performed treatment of additional treatment and/or surgery. The “chemotherapy” recited in the recommendation list is particular. The recommended “additional surgery” (claim 28) is not a particular surgery related to the determination of a minimum residual disease. Just say “surgery” is generic. Tumor tissue surgery is a particular treatment (related to the disease). “Collection of a tumor biopsy sample” and “collection of blood sample” are not treatments.
The last disconnection is between the recommendation output made by the artificial neural network and the recommendation performed. In all of claims 1, 25 and 28, “collection of a tumor biopsy sample” and “collection of blood sample” are not part of the output recommendation (claims 1 and 25) or the second treatment (claim 28), but listed in the recommendation performed (claims 1 and 25) or the second treatment (claim 28). In another word, the judicial exception (here the output recommendation (claims 1 and 25) or the second treatment (claim 28)) is not 100% applied by the additional elements and the additional elements do not capture and reflect 100% of the judicial exception.
This judicial exceptions are not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to 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 implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element 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.
Step 2B: Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea:
Acquiring, by one more processors of an information processing system, first sequencing data associated with a tumor tissue biopsy sample, of a patient, acquired prior to surgery of the patient (claims 1, 25 and 28);
Acquiring, by the one or more processors, second sequencing data associated with a normal blood sample, of the patient, acquired prior to the surgery of the patient (claims 1, 25 and 28);
Acquiring, by the one or more processors, after the surgery of the patient, and via whole genome sequencing, third sequencing data associated with a plasma sample of the patient, wherein the plasma sample of the patient was acquired after the surgery of the patient, and wherein the plasma sample includes cell free Deoxyribonucleic Acid (cfDNA) and circulating tumor Deoxyribosyl Nucleic Acid (ctDNA) (claims 1, 25 and 28);
Receiving, from a trained machine learning model implemented using an artificial neural network and in response to input corresponding to the minimal residual disease, output indicating a recommendation associated with one or more of: initiating a therapy selected from the group consisting of chemotherapy-based therapy, antibody-based therapy, and small molecule kinase inhibitor-based therapy, switching from a first therapy to a second therapy, the first therapy and the second therapy being selected from the group consisting of chemotherapy-based therapy, antibody-based therapy, and small molecule kinase inhibitor-based therapy; or perform an additional surgery on the tumor tissue (claim 1);
Receiving, from a trained machine learning model implemented using an artificial neural network and in response to input corresponding to the minimal residual disease, output indicating a recommendation associated with one or more of: chemotherapy-based therapy, antibody-based therapy, small molecule kinase inhibitor-based therapy, or additional surgery (claim 25);
Performing, within an interval of time corresponding to the minimal residual disease, the recommendation, wherein the recommendation comprises one or more of:
a surgery to reduce the tumor cell fraction for the patient,
a tumor tissue surgery,
collection of a tumor tissue biopsy sample,
collection of a blood sample,
the chemotherapy-based therapy,
the antibody-based therapy, or
the small molecule kinase inhibitor-based therapy.
(claims 1, 25 and 28);
Causing one or more user terminals to display an indication of recommendation (claim 21); and
Receiving, from a trained machine learning model implemented using an artificial neural network and in response to input corresponding to the minimal residual disease, output indicating the second treatment (claim 29).
The above additional elements can be divided into three groups: 1) elements of sample and data acquiring (first 3 elements); 2) elements of model output results (4th-5th, and 8th elements) at the terminals (the 7th element); and 3) treatment and/or surgery choices (6th element). Group 1 and group 2 additional elements are insignificant extra-solution activities as they are required for data inputting and outputting. Group 3 additional elements are related to therapeutic choices. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the additional elements are insignificant extra-solution activity or generic choice of therapies.
The claims do not include additional elements that are sufficient to amount of significantly more than the judicial exception because it is routine and conventional to perform the acts of acquiring necessary data for analysis. Other elements of the method include an artificial neural network modeling that serve to perform generic data model functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Therapy, surgery or collecting samples, are common in the clinical industry. Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Applicant’s Arguments
Applicant's arguments filed on 6 July 2026 have been fully considered but they are not persuasive. Particularly:
In the Remarks (page 13 2nd para), Applicant argues that claims are not directed to an abstract ideas, because they have nothing to do with "observations, evaluations, judgments, and opinions." Applicant’s argument refers to Step 2A/Prong One in the 35 USC 101 analysis.
In response, Applicant’s argument is not persuasive. Applicant argued that human mind is not equipped to perform the claim limitations. However, as discussed in the 35 USC 101 analysis above (Section “Step 2A Prong One: Identification of an Abstract Idea”), claims do recite abstract ideas in the mathematical concept grouping. Claim element like “identifying tumor tissue mutation information of the patient by comparing the first sequencing data and the second sequencing data, wherein the tumor tissue mutation information comprises a number of tumor tissue mutations of the patient” (claims 1, 25 and 28); Under a BRI and at its simplest embodiment, this encompasses the practice of comparing two sequence reads and identifying mutations. Such an activity can be accomplished in human mind, with the aid of a pen and paper.
Therefore, claims do recite elements directed to abstract ideas.
In the Remarks, Applicant argues (page 14, 1st para) that claims are integrated into a practical application. Applicant’s argument refers to Step 2A/Prong two in the 35 USC 101 analysis.
In response, Applicant’s argument is not persuasive. The recitation of performing actions of treatments and collection of samples based on the model output are not all particular in claim 1. However, the determined “tumor recurrence” is not integrated into the next step “receiving, from a trained machine learning model implemented using an artificial neural network and in response to input corresponding to the minimal residual disease, output indicating a recommendation associated with one or more of” in all the three independent claims 1, 25 and 28. In another words, the treatment or therapy pertains to the MRD but the MRD is disconnected to the “tumor recurrence”.
The last disconnection is between the recommendation output made by the artificial neural network and the recommendation performed. In all of claims 1, 25 and 28, “collection of a tumor biopsy sample” and “collection of blood sample” are not part of the output recommendation (claims 1 and 25) or the second treatment (claim 28), but listed in the recommendation performed (claims 1 and 25) or the second treatment (claim 28). In another word, the judicial exception (here the output recommendation (claims 1 and 25) or the second treatment (claim 28)) is not 100% applied by the additional elements and the additional elements do not capture and reflect 100% of the judicial exception.
In the Remarks, Applicant argues (page 14, last para through page 15, 2nd para) that claims like McRO, improve the functioning of a computer.
In response, Applicant’s argument is not persuasive. Contrary to appellant argument, the case of McRO is not analogous to the instant claims because the instant claims only involve a generic computer in the generation of an in silico resonation of a biological sequence. Unlike McRO, there is no improvement to the generic computer of the instant claims beyond the conventional use as a computational workhorse running algorithmic based programming.
Appellant did not provide evidence the claimed “computer system” is anything more than a generic computer that implements machine learning algorithms, etc., in the conventional and well-known way that computers ordinary function. To qualify as “a patent- eligible improvement,” the invention must be directed to a specific improvement in the computer’s functionality, not simply to use of the computer “as a tool” to implement an abstract idea. Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1363-1364 (Fed. Cir. 2020). Here, the invention falls into the latter category. It focuses on using a general purpose computer to carry out the abstract idea. Consequently, an inventive concept in how the computer system operates is not identified.
In the Remarks, Applicant argues (page 15, last para through page 16, 2nd para) that claims add significantly more than any alleged abstract idea. Applicant’s argument refers to Step 2B in the 35 USC 101 analysis.
In response, as discussed in the 35 USC 101 analysis, it is routine and conventional to perform the acts of acquiring necessary data for analysis. Other elements of the method include an artificial neural network model that serve to perform generic data modeling functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Therapies listed (surgery, collection of a sample, chemotherapy-based therapy, antibody-based therapy, and small molecule kinase inhibitor-based therapy) are common and well-known in the clinical industry. Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
Therefore, the 35 U.S.C. 101 rejection is maintained.
Conclusion
No claims are allowed.
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.
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/GL/
Patent Examiner
Art Unit 1686
/Anna Skibinsky/
Primary Examiner, AU 1635
