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 .
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.
Election/Restrictions
Applicant’s election without traverse of species A2 from species Group A and species B1 from species Group B, directed to claim 8 with dependent claim 9 in the reply filed on 02/15/2026 to the office action dated 12/23/2025 is acknowledged.
Claims 2, 10-12, 16-17 and 19 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 02/15/2026.
Status of claims
Claims 1-4, 6-19 and 21 are pending.
Claim 2, 10-12, 16-17 and 19 are withdrawn, as discussed in the Election/Restrictions section above.
Claims 1, 3-4, 13 and 15 are amended.
Claims 5 and 20 are canceled.
Claim 21 is new.
Claims 1 and 15 are independent claims.
Claims 1, 3-4, 6-9, 13-15, 18 and 21 are examined below.
Priority
As detailed on the 12/07/2022 filing receipt, this application claims domestic priority to as early as 11/23/2021.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: S1 and S2 in Fig. 1. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Information Disclosure Statement
The Information Disclosure Statements filed on 04/19/2023, 12/20/2023, 04/03/2025 and 01/16/2026 are in compliance with the provisions of 37 CFR 1.97 and have been considered in full. A signed copy of the list of references cited from each IDS is included with this Office Action.
Claim Objections
Claim 14 is objected to because of the following informalities:
Claim 14 (line 3) recites “…XGBoots...” The recitation should be “XGBoost” to correct the spelling of the term.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 15-19 and 21 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 15 recites “A system for predicting implantation outcome of an embryo....” The claim does not recite the physical structure associated with the recited system, which is/are critical or essential to the practice of the invention but not included in the claim(s). See In re Mayhew, 527 F.2d 1229, 188 USPQ 356 (CCPA 1976). Paragraph [0012] of the instant specification discloses that FIG. 2 is a block diagram of the system to predict embryos' implantation outcomes following embryo transfer in IVF treatment by using artificial intelligence of the first embodiment according to the present invention, showing the system is connected to the database.
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 1, 3-4, 6-9, 13-19 and 21 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.
Claim 1 (line 8) and claim 15 (line 6) recite “…the basic information of the woman comprises an age, an information of chromosome abnormality…” The metes and bounds of the phrase, “an information of chromosome abnormality” is not clearly defined and renders the claim indefinite.
Claims 13 (lines 3-6, the term occurs 4 times in the claim) recites "...prioritized embryo...." The recited “prioritized” is a subjective term of relative or vague degree or form of association, neither defined in the specification, nor having a well-known and sufficiently particular definition in the art (See MPEP 2173.05(b)). A claim term that requires the exercise of subjective judgment without restriction may render the claim indefinite. In re Musgrave, 431 F.2d 882, 893, 167 USPQ 280, 289 (CCPA 1970) (See 2173.05(b)).
Claim 15 recites “A system for predicting implantation outcome of an embryo....” The metes and bounds of the recited “system” are not clearly defined and renders the claim indefinite. It is unclear what components/structures are included in the system or what the system encompasses.
Dependent claims are rejected for depending on rejected claims.
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, 3-4, 6-9 and 13-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Analysis of claims in Step 1.
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Independent claim 1 is directed to a 101 process, here a "method for predicting an implantation outcome of an embryo during in vitro fertilization treatment," with process steps such as "providing…"
[Step 1: claims 1, 3-4, 6-9 and 13-14: YES]
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, claims 1, 3-4, 6-9 and 13-14 recite the following limitations that equate to an abstract idea:
Mental processes recited include:
Claims 1 recites: "…to generate a prediction." Generating a prediction is an act of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Mathematical concepts recited include:
Claims 1 recites: "…providing an artificial intelligence prediction model, wherein the artificial intelligence prediction model…the prediction result is related to a predicted implantation rate, a pregnancy rate after the transfer of the embryo to the woman, or a result of whether a baby is born or not." Prediction model, implantation rate and pregnancy rate are mathematical concepts and/or formulas.
Claims 3 recites: "wherein the telomere length, the copy number of mtDNA and chromosome stability of the genetic information of the embryo are calculated based on a sequencing result." Calculating are mathematical concepts and/or formulas.
Claim 14 recites: "wherein the artificial intelligence prediction model is trained by using one of a plurality of algorithms comprising logistic regression, decision tree, random forest, support vector machine (SVM), LightGBM, XGBoots, Tabnet, and ensemble learning." The recited algorithms are mathematical concepts and/or formulas.
Law of nature recited include:
Claims 1 recites: "the genetic information of the embryo comprises a copy number of mitochondrial DNA and, a telomere length and chromosome stability; the basic information of the woman comprises an age, an information of chromosome abnormality, and a history of recurrent miscarriage… a predicted implantation rate, a pregnancy rate after the transfer of the embryo to the woman, or a result of whether a baby is born or not." The claim element recites a correlation between the genetic information of the embryo and implantation rate, pregnancy rate, whether the baby is born, which is a law of nature because it describes a consequence of natural processes in the human body, e.g., the naturally-occurring relationship between the genetic information of the embryo and implantation rate, pregnancy rate or whether the baby is born.
As indicated above, claim 1 recites "…to generate a prediction." Generating a prediction is an act of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper. Acts of evaluating and analyzing data could be practically performed in the human mind and/or with pen and paper because they merely require making observations, evaluations, judgments, and opinions (See MPEP 2106.04(a)(2) subsection III). Therefore, under the broadest reasonable interpretation, the indicated claims above can be practically carried out in the human mind or with pen and paper as claimed, which falls under the "Mental processes" grouping of abstract ideas.
Claims 1, 3 and 14 recite mathematical concepts and formulas as identified above. For instance, claim 1 recites implantation rate and pregnancy rate; claim 3 recites genetic information of the embryo are calculated based on a sequencing result; and claim 14 recites logistic regression, decision tree, random forest, support vector machine (SVM), LightGBM, XGBoots, Tabnet, and ensemble learning, which are mathematical concepts and/or formulas that falls under the “mathematical concepts” grouping of abstract ideas.
The claim limitations of claim 1 recites a correlation between the genetic information of the embryo and implantation rate, pregnancy rate, whether the baby is born, which is a law of nature because it describes a consequence of natural processes in the human body, e.g., the naturally-occurring relationship between the genetic information of the embryo and implantation rate, pregnancy rate or whether the baby is born.
As such, claims 1, 3-4, 6-9 and 13-14 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The above indicated judicial exceptions are not integrated into a practical application because the claims do not recite an additional elements that apply, rely on or use the judicial exception in such a manner to amount to integration into a practical application. For example, there are no limitations that reflect an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that equate to mere instructions to implement an abstract idea or insignificant extra solution activity. Specifically, the instant claims recite the following additional elements:
Claim 1 recites "providing an input interface, wherein a plurality of parameters is entered through the input interface, the plurality of parameters comprises a genetic information of an embryo and a basic information of a woman who is going to be implanted with the embryo; the genetic information of the embryo comprises a copy number of mitochondrial DNA and, a telomere length and chromosome stability; the basic information of the woman comprises an age, an information of chromosome abnormality, and a history of recurrent miscarriage; and providing an artificial intelligence prediction model, wherein the artificial intelligence prediction model receives the plurality of parameters to generate a prediction result based on the plurality of parameters; the prediction result is related to a predicted implantation rate, a pregnancy rate after the transfer of the embryo to the woman, or a result of whether a baby is born or not."
Claim 3 recites "comprising sequencing a genome of the embryo to obtain the genetic information of the embryo…"
Claim 4 recites: "wherein sequencing the genome of the embryo is conducted via Next Generation Sequencing (NGS)."
Claim 13 recites: "training the artificial intelligence prediction model by using a training data set, wherein the training data set comprises a plurality of training information; each of the plurality of training information comprises a genetic information of a prioritized embryo and a basic information of a woman corresponding to the prioritized embryo; the genetic information of the prioritized embryo comprises a copy number of mtDNA, a telomere length and chromosome stability; the basic information of the woman corresponding to the prioritized embryo comprises an age, an information of chromosome abnormality, a history of recurrent miscarriage."
Claims 6-9 provide information for what the data represents.
The elements of claims 1 and 3-4 as indicated above equate to insignificant extra solutional activities of data gathering and outputting. Data gathering serves as input to the recited judicial exception in the claims. Additionally, the listed additional elements are mere instructions to apply an exception because they recite no more than an idea of a solution or outcome and does not recite a technological solution to a technological problem. (See MPEP 2106.05(f)(1)). The process of training the prediction model in claim 13 requires inputting data that equates to insignificant extra solutional activity. As such, as currently recited, the claims do not appear to recite an improvement to technology or apply or use the recited judicial exception in some other meaningful way. Therefore, claims 1, 3-4, 6-9 and 13-14 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to well-understood, routine and conventional activities, insignificant extra-solution activity or mere instructions to implement the abstract idea on a generic computer. The instant claims recite the following additional elements:
Claim 1 recites "providing an input interface, wherein a plurality of parameters is entered through the input interface, the plurality of parameters comprises a genetic information of an embryo and a basic information of a woman who is going to be implanted with the embryo; the genetic information of the embryo comprises a copy number of mitochondrial DNA and, a telomere length and chromosome stability; the basic information of the woman comprises an age, an information of chromosome abnormality, and a history of recurrent miscarriage; and providing an artificial intelligence prediction model, wherein the artificial intelligence prediction model receives the plurality of parameters to generate a prediction result based on the plurality of parameters; the prediction result is related to a predicted implantation rate, a pregnancy rate after the transfer of the embryo to the woman, or a result of whether a baby is born or not."
Claim 3 recites "comprising sequencing a genome of the embryo to obtain the genetic information of the embryo…"
Claim 4 recites: "wherein sequencing the genome of the embryo is conducted via Next Generation Sequencing (NGS)."
Claim 13 recites: "training the artificial intelligence prediction model by using a training data set, wherein the training data set comprises a plurality of training information; each of the plurality of training information comprises a genetic information of a prioritized embryo and a basic information of a woman corresponding to the prioritized embryo; the genetic information of the prioritized embryo comprises a copy number of mtDNA, a telomere length and chromosome stability; the basic information of the woman corresponding to the prioritized embryo comprises an age, an information of chromosome abnormality, a history of recurrent miscarriage."
Claims 6-9 provide information for what the data represents.
The additional elements indicated above do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. The limitations equate to mere data gathering activities, which are insignificant extra solutional activities. The courts have recognized that techniques for analyzing DNA to provide sequence information or detecting allelic variants and amplifying and sequencing nucleic acid sequences as well-understood, routine, conventional activity in the life science arts when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. (See MPEP 2106.05(d)). Additionally, training a prediction model are well-known and conventional as disclosed by Leung (Leung, Michael KK, et al. "Machine learning in genomic medicine: a review of computational problems and data sets." Proceedings of the IEEE 104.1 (2015): 176-197.; as cited on the attached 892 form). The method of NGS is also well-known as disclosed by Voelkerding (Voelkerding, Karl V., Shale A. Dames, and Jacob D. Durtschi. "Next-generation sequencing: from basic research to diagnostics." Clinical chemistry 55.4 (2009): 641-658.; as cited on the attached 892 form). As explained by the Supreme Court, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional. (see MPEP 2106.05(g)). Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1, 3-4, 6-9 and 13-14 are not patent eligible.
Matter belonging to no 101 statutory category -- claims 15, 18 and 21
Independent claim 15 is not directed to a 101 process, machine, manufacture, or composition of matter. Claim 15 recites a "system," without any non-transitory elements.
[Step 1: claims 15-19 and 21: NO]
Claims 15-19 and 21 are rejected under 35 USC 101 because the claimed inventions are directed to non-statutory subject matter.
Claim 15 is to "a system," which is not, in all embodiments within a BRI, interpreted as belonging to any one particular category listed in 101. In a BRI, the claim reads on data and/or software comprising no structure other than data and/or software. The claim is not recited as a process, and the claim is not limited to any particular structure as a 101 machine or manufacture. (In re Nuijten, Federal. Circuit, 2006).
In a BRI, none of the dependent claims 16-19 and 21 clearly requires a non-transitory element, and therefore none of the dependent claims clearly remedies this rejection.
As appropriate, this rejection can be overcome by, for example, amending to recite structure such as non-transitory computer-readable storage medium comprising computer instructions stored and structurally configured to store the recited data and to accomplish the recited steps.
Judicial exceptions (JEs) to 101 patentability
Claims 15-19 and 21 are rejected under 35 USC 101 because the claimed inventions are not directed to patent eligible subject matter. After consideration of relevant factors with respect to each claim as a whole, each claim is directed to one or more judicially-recognized exceptions to patentability (JEs), i.e. an abstract idea, a natural phenomenon, a law of nature and/or a product of nature, as identified below. Below, it is not clear that any element or combination of elements in addition to the JE(s), i.e. and "additional elements," either integrate the identified JE(s) into a practical application and/or is a non-conventional additional element, such that it is not clear that any claim is directed to significantly more than the identified JE(s).
MPEP 2106 organizes JE analysis into Steps 1, 2A (1st prong & 2nd prong) and 2B as analyzed below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
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 for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Wells (US 2017/107571 A1., published Apr. 20, 2017; as cited on the 01/16/2026 IDS Document) in view of Keefe (US 2016/0032360 A1., published Feb. 4, 2016; as cited on the 01/16/2026 IDS Document) and Qui ("Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method." Journal of translational medicine 17.1 (2019): 317.; as cited on the attached Notice of References 892 form).
Regarding independent claims 1 and 15, Wells, Keefe and Qiu teaches the claim limitation of providing an input interface, wherein a plurality of parameters is entered through the input interface, the plurality of parameters comprises a genetic information of an embryo and a basic information of a woman who is going to be implanted with the embryo; the genetic information of the embryo comprises a copy number of mitochondrial DNA and, a telomere length and chromosome stability; the basic information of the woman comprises an age, an information of chromosome abnormality, and a history of recurrent miscarriage; and providing an artificial intelligence prediction model, wherein the artificial intelligence prediction model receives the plurality of parameters to generate a prediction result based on the plurality of parameters; the prediction result is related to a predicted implantation rate, a pregnancy rate after the transfer of the embryo to the woman, or a result of whether a baby is born or not.
Wells teaches the claim limitation of providing an input interface, wherein a plurality of parameters is entered through the input interface, the plurality of parameters comprises a genetic information of an embryo and a basic information of a woman who is going to be implanted with the embryo with “Reference levels may be stored in a suitable data storage medium (e.g., a database) and are, thus, also available for future diagnoses. This also allows efficiently analysis because suitable reference results can be identified in the database once it has been confirmed (in the future) that the subject from which the corresponding reference sample was obtained did successfully implant. As used herein a “database” comprises data collected (e.g., analyte and/or reference level information and/or patient information) on a suitable storage medium. Moreover, the database, may further comprise a database management system. … More preferably, the database will be implemented as a distributed (federal) system, e.g. as a Client-Server-System. More preferably, the database is structured as to allow a search algorithm to compare a test data set with the data sets comprised by the data collection. Specifically, by using such an algorithm, the database can be searched for similar or identical data sets being indicative of mtDNA levels. Thus, if an identical or similar data set can be identified in the data collection, the test data set will be associated with implantation potential. Consequently, the information obtained from the data collection can be used to predict embryo implantation potential based on a test data set obtained from a reference embryo sample.” ([0133]) and “Specifically, the inventors examined the relationship between human blastocyst mtDNA content, female patient age, embryo chromosome status, viability and implantation potential.” ([0067])
Wells teaches the claim limitation of the genetic information of the embryo comprises a copy number of mitochondrial DNA and chromosome stability; the basic information of the woman comprises an age with “Specifically, the inventors examined the relationship between human blastocyst mtDNA content, female patient age, embryo chromosome status, viability and implantation potential. Additionally, we attempted to shed light on the stage of preimplantation development during which mtDNA replication is first up-regulated, with the potential to increase the mtDNA content of individual cells. As well as relative quantification of mtDNA, a detailed analysis of the mitochondrial genome was undertaken, searching for mutations, deletions and polymorphisms.” ([0067]).
Wells teaches the claim limitation of providing an artificial intelligence prediction model, wherein the artificial intelligence prediction model receives the plurality of parameters to generate a prediction result based on the plurality of parameters with “In some cases, the kits comprise software useful for comparing DNA levels or occurrences with a reference (e.g., a prediction model). Usually the software will be provided in a computer readable format such as a compact disc, but it also may be available for downloading via the internet. However, the kits are not so limited and other variations with will be apparent to one of ordinary skill in the art. The present methods can also be used for selecting a treatment and/or determining a treatment plan for a subject, based on the expression levels of a gene set (e.g., those disclosed herein).” ([0132]).
Wells teaches the claim limitation of the prediction result is related to a predicted implantation rate, a pregnancy rate after the transfer of the embryo to the woman, or a result of whether a baby is born or not with “Statistical analysis of the final mtDNA values utilised unpaired two-tailed t-tests. Parameters which were compared during this study included female age (younger vs. older), embryo chromosome status (normal vs. aneuploid), and embryo viability/implantation potential (ongoing pregnancy vs. failure to implant).” ([0151]).
Wells does not teach the claim limitation of the genetic information of the embryo comprises a telomere length; basic information of the woman comprises an information of chromosome abnormality and a history of recurrent miscarriage in claims 1 and 15. However, these limitations are taught by Keefe and Qui.
Keefe teaches the claim limitation of the genetic information of the embryo comprises a telomere length and chromosome stability with “In another embodiment, the invention provides a method for predicting viability of an embryo (e.g., in connection with assisted reproductive technologies), said method comprising: (a) determining relative telomere length in one or more blastomeres isolated from the embryo using the method for determining relative telomere length (as described above), and (b) (i) determining that the embryo has high viability if the T/R ratio in the one or more blastomeres is similar to the standard T/R ratio, or (ii) determining that the embryo has low viability if the T/R ratio in the one or more blastomeres differs from the standard T/R ratio, wherein the standard T/R ratio is an average T/R ratio or a standard curve of T/R ratios of one or more blastomeres from an embryo that created the pregnancy.” ([0045]).
Keefe teaches the claim limitation of the basic information of the woman comprises an information of chromosome abnormality with “In a further embodiment, the invention provides a method for predicting chromosomal stability of an oocyte (e.g., in connection with assisted reproductive technologies), said method comprising:
(a) determining relative telomere length in a polar body corresponding to the oocyte using the method for determining relative telomere length (as described above), and
(b) (i) determining that the oocyte has high chromosomal stability if the T/R ratio in the polar body is similar to the standard T/R ratio, or (ii) determining that the oocyte has chromosomal instability if the T/R ratio in the polar body differs from the standard T/R ratio, wherein the standard T/R ratio is an average T/R ratio or a standard curve of T/R ratios for multiple healthy oocytes from healthy oocyte donors.” ([0044]). It is noted that the recited chromosome abnormality is interpreted to corresponds to chromosomal stability of an oocyte as taught by Keefe.
Qui teaches the claim limitation of the basic information of the woman comprises an age, an information of chromosome abnormality, and a history of recurrent miscarriage with “Taken together, we selected age, AMH, BMI, duration of infertility, previous live birth, previous miscarriage, previous abortion and type of infertility as predictors. Type of infertility was classified into tubal, anovulatory, male factor, unexplained and others (e.g. endometriosis, fibroids).” (page 4, col. 1, para. 1).
Regarding claim 13, Wells, Keefe and Qiu teaches the claim limitation of training the artificial intelligence prediction model by using a training data set, wherein the training data set comprises a plurality of training information; each of the plurality of training information comprises a genetic information of a prioritized embryo and a basic information of a woman corresponding to the prioritized embryo; the genetic information of the prioritized embryo comprises a copy number of mtDNA , a telomere length and chromosome stability; the basic information of the woman corresponding to the prioritized embryo comprises an age, an information of chromosome abnormality, a history of recurrent miscarriage.
Wells teaches the claim limitation of the genetic information of the prioritized embryo comprises a copy number of mitochondrial DNA and chromosome stability; the basic information of the woman comprises an age with “Specifically, the inventors examined the relationship between human blastocyst mtDNA content, female patient age, embryo chromosome status, viability and implantation potential. Additionally, we attempted to shed light on the stage of preimplantation development during which mtDNA replication is first up-regulated, with the potential to increase the mtDNA content of individual cells. As well as relative quantification of mtDNA, a detailed analysis of the mitochondrial genome was undertaken, searching for mutations, deletions and polymorphisms.” ([0067]).
Wells does not explicitly teach the claim limitation of training the artificial intelligence prediction model by using a training data set, wherein the training data set comprises a plurality of training information; each of the plurality of training information comprises a genetic information of a prioritized embryo and a basic information of a woman corresponding to the prioritized embryo; the genetic information of the prioritized embryo comprises a telomere length; basic information of the woman comprises an information of chromosome abnormality and a history of recurrent miscarriage in claim 13. Wells also does not explicitly teach the claim limitation of wherein the artificial intelligence prediction model is trained by using one of a plurality of algorithms comprising logistic regression, decision tree, random forest, support vector machine (SVM), LightGBM, XGBoots, Tabnet, and ensemble learning of claim 14. However, these limitations are taught by Keefe and Qui.
Keefe teaches the claim limitation of the genetic information of the prioritized embryo comprises a telomere length and chromosome stability with “In another embodiment, the invention provides a method for predicting viability of an embryo (e.g., in connection with assisted reproductive technologies), said method comprising: (a) determining relative telomere length in one or more blastomeres isolated from the embryo using the method for determining relative telomere length (as described above), and (b) (i) determining that the embryo has high viability if the T/R ratio in the one or more blastomeres is similar to the standard T/R ratio, or (ii) determining that the embryo has low viability if the T/R ratio in the one or more blastomeres differs from the standard T/R ratio, wherein the standard T/R ratio is an average T/R ratio or a standard curve of T/R ratios of one or more blastomeres from an embryo that created the pregnancy.” ([0045]).
Keefe teaches the claim limitation of the basic information of the woman comprises an information of chromosome abnormality with “In a further embodiment, the invention provides a method for predicting chromosomal stability of an oocyte (e.g., in connection with assisted reproductive technologies), said method comprising:
(a) determining relative telomere length in a polar body corresponding to the oocyte using the method for determining relative telomere length (as described above), and
(b) (i) determining that the oocyte has high chromosomal stability if the T/R ratio in the polar body is similar to the standard T/R ratio, or (ii) determining that the oocyte has chromosomal instability if the T/R ratio in the polar body differs from the standard T/R ratio, wherein the standard T/R ratio is an average T/R ratio or a standard curve of T/R ratios for multiple healthy oocytes from healthy oocyte donors.” ([0044])
Qui teaches the claim limitation of the basic information of the woman comprises an age, an information of chromosome abnormality, and a history of recurrent miscarriage with “Taken together, we selected age, AMH, BMI, duration of infertility, previous live birth, previous miscarriage, previous abortion and type of infertility as predictors. Type of infertility was classified into tubal, anovulatory, male factor, unexplained and others (e.g. endometriosis, fibroids).” (page 4, col. 1, para. 1).
Qui teaches the claim limitation of training the artificial intelligence prediction model by using a training data set, wherein the training data set comprises a plurality of training information with “In this study, the original dataset included more than 100 variables. Not all variables had a significant prediction effect on live birth and the candidate predictors should be clearly defined, standardized, and reproducible. Therefore, feature selection was performed based on subject knowledge, on pathophysiological mechanisms, or the results of previous studies and guidelines. We encoded categorical features using a one-hot encoding scheme. After data processing, 70% of the dataset was randomly selected as a training set for prediction model establishment, and the remaining 30% was used for validation. A stratified random sampling method was employed to ensure that the proportions of live birth and no live-birth cases were the same in both the training and validation sets as in the original dataset. Grid-search with k-fold cross-validation (k = 5) was used to find the optimal hyperparameters of the four classification classifiers mentioned above. The training set was subdivided into k folds. Each time, k − 1 folds were used for training and the remaining one was for validation. For each algorithm, models with different hyperparameters were scored by their mean accuracy. We chose the hyperparameter set that maximized the mean accuracy and fitted the model with the whole training dataset respectively. To evaluate the performance of each machine learning classifier, we assessed discrimination and calibration, which are widely used in prediction model validation. The receiver operating characteristic (ROC) curve and the calibration plot of the four chosen models for the validation set were adopted as a measure of discrimination and calibration.” (page 3, col. 1, para. 2)
Regarding claim 14, Qiu teaches the claim limitation of wherein the artificial intelligence prediction model is trained by using one of a plurality of algorithms comprising logistic regression, decision tree, random forest, support vector machine (SVM), LightGBM, XGBoots, Tabnet, and ensemble learning with “Four supervised machine learning algorithms were respectively considered to build the predictive models: logistic regression, random forest, extreme gradient boosting (XGBoost) and support vector machine (SVM). All algorithms can deal with classification problems. Logistic regression is a common supervised classification algorithm with a nice probabilistic interpretation. The SVM is good at high dimension data, making it popular for many machine learning practitioners. Compared with logistic regression and SVM, XGBoost and random forest are both ensemble techniques that produce a prediction model by constructing a set of weaker learners, typically decision trees, and predict by combining the outcomes of each individual tree. The biggest difference lies in the way the trees are built. The random forest trains each tree independently by random sampling from the data. The XGBoost builds trees sequentially with each new tree trying to correct for the errors in the previous tree. ((page 2, col. 2, para. 4) to (page 3, col. 1, para. 1)), Figure 2 (page 5) that depicts the performances of the logistic regression, random forest, SVM and XGBoost. and with “The XGBoost exhibited the best calibration among all models, although it tended to underestimate the probability for high-probability patients. In conclusion, XGBoost provided the most accurate and robust prediction on the cumulative live birth chance for the first complete IVF cycles.” (page 5, col. 1, para. 1).
It would have been prima facia obvious to combine the teachings of Wells and Keefe. Keefe’s method of SCT-pqPCR has an advantage over QFISH for telomere length at single cell levels because it is not dependent on cell division and does not bias results when testing a heterogeneous population of cells consisting of both dividing and quiescent cells ([0148]). A person of ordinary skill in the art would have been motivated to combine the teachings of Wells to include determining chromosomal stability and telomere length of embryos as taught by Keefe because Keefe’s method allows for the measurement of telomere length in single cells and the testing of a heterogeneous population of cells consisting of both dividing and quiescent cells without biases ([0148]). Furthermore, there would have been a reasonable expectation of success, since both Wells and Keefe teach methods that pertain to predicting viability of an embryo.
It would have been prima facia obvious to combine the teachings of Wells and Qui. Qui’s method of utilizing a prediction model based on XGBoost using age, AMH, BMI, duration of infertility,
previous live birth, previous miscarriage, previous abortion and type of infertility was able to provide personalized estimates of the cumulative live birth chance of the first complete IVF cycle before treatment with an average accuracy score of 0.70, compared to 0.69, 0.68 and 0.68 for random forest,
SVM and logistic regression, respectively (page 5, col. 2, para. 1). A person of ordinary skill in the art would have been motivated to combine the teachings of Wells to include training XGBoost with the additional feature of chromosome abnormality and miscarriage history as taught by Qui to accurately obtain a prediction of live birth. Furthermore, there would have been a reasonable expectation of success, since both Wells and Qui teach methods that pertain to the analysis of invitro fertilization outcomes.
Claims 3-4 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Wells (US 2017/107571 A1., published Apr. 20, 2017; as cited on the 01/16/2026 IDS Document) in view of Keefe (US 2016/0032360 A1., published Feb. 4, 2016; as cited on the 01/16/2026 IDS Document) and Qui ("Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method." Journal of translational medicine 17.1 (2019): 317.; as cited on the attached Notice of References 892 form) as applied to claims 1 and 13-15 under 35 U.S.C 103 as discussed above, and further in view of Nersisyan ("Computel: computation of mean telomere length from whole-genome next-generation sequencing data." PLoS one 10.4 (2015): e0125201.; as cited on the attached Notice of References 892 form)
Wells, Keefe and Qui are applied to claims 1 and 13-15 under 35 U.S.C 103 as discussed above.
Regarding claims 3 and 21, Wells teaches the claim limitation of sequencing a genome of the embryo to obtain the genetic information of the embryo, wherein the telomere length, the copy number of mtDNA and chromosome stability of the genetic information of the embryo are calculated based on a sequencing result with “One potential reason for altered mtDNA levels could be a proliferation of mitochondria as a compensatory response to the presence of defective organelles harbouring mutations in key genes. To explore this possibility NGS was used to sequence the entire mitochondrial genome of 23 TE samples. The samples were derived from chromosomally normal blastocysts, 9 of which had elevated quantities of mtDNA (initially determined using real-time PCR) and 14 that had mtDNA levels in the normal range (Table 3). The mitochondrial genome was sequenced to an average depth of ˜150 reads, permitting mutation detection and an estimate of degree of heteroplasmy. Mutations, usually in heteroplasmic form, were seen to some extent in all samples, but were no more prevalent in blastocysts with high mtDNA levels than they were in embryos with lower quantities of mtDNA.” ([0167]); “The relative amount of mtDNA in relation to the Alu sequence for both reference and test samples was determined by the equation 2-Delta Delta Ct. The Delta Ct for reference and test samples was the end result of a data normalisation process. This involved the calculation of the Delta Ct for reference and test loci (Ct-mtDNA minus Ct-Alu), and the adjustment of the test samples values in relation to the reference DNA sample (Delta Ct plus Normalisation factor) (Schmittgen et al., 2008 Nat Protoc 3:1101-1108). Statistical analysis of the final mtDNA values utilised unpaired two-tailed t-tests. Parameters which were compared during this study included female age (younger vs. older), embryo chromosome status (normal vs. aneuploid), and embryo viability/implantation potential (ongoing pregnancy vs. failure to implant).” ([0151]) and “Relative quantification of mtDNA using NGS involved determination of the number of DNA sequence reads attributable to the mitochondrial genome as a fraction of the total number of reads. The great majority of DNA fragments sequenced are derived from the nuclear genome and provide a control for the number of cells in the biopsy specimen.” ([0152]).
Wells teaches the claim limitation of sequencing a genome of the embryo to obtain the genetic information of the embryo chromosome stability of the genetic information of the embryo are calculated based on a sequencing result with “A total of 39 cleavage stage embryos and 340 blastocysts, which had been cytogenetically tested, were studied during the course of this investigation. All of the cleavage stage embryos had been characterised as being chromosomally normal after microarray comparative genomic hybridization (aCGH) analysis and transferred to the uterus. Of the blastocysts examined, 302 were analysed using aCGH, and 38 using next generation sequencing (NGS) methodology. Of these, 123 were determined to be aneuploid (99 via aCGH analysis and 24 via NGS analysis), while the remaining 217 were characterised as being chromosomally normal (203 via aCGH analysis and 14 via NGS analysis). One hundred and thirty one of the normal blastocysts and all 39 euploid cleavage stage embryos underwent uterine transfer. Embryo classification as chromosomally normal or aneuploid was based on results obtained after aCGH or NGS analysis of either a single blastomere (cleavage stage), or 5-10 TE cells (blastocysts).” ([0153]). It is noted that the recited embryo chromosome stability of the genetic information of the embryo are calculated based on a sequencing result is interpreted to refer to the number of embryos that are chromosomally normal as taught by Wells.
Wells does not teach the claim limitation of wherein the telomere length is calculated based on a sequencing result in claims 3 and 21. However, this limitation is taught by Nersisyan.
Nersisyan teaches the claim limitation of wherein the telomere length is calculated based on a sequencing result with “We have developed Computel, a program in R for computing mean telomere length from whole-genome next-generation sequencing data.” (abstract) and “The results have shown that Computel outperforms existing software in accuracy, independence of results from sequencing conditions, stability against inherent sequencing errors, and better ability to distinguish pure telomeric sequences from interstitial telomeric repeats. By providing a highly reliable methodology for determining telomere lengths from whole-genome sequencing data, Computel should help to elucidate the role of telomeres in cellular health and disease.” (abstract).
Regarding claim 4, Wells teaches the claim limitation of wherein sequencing the genome of the embryo is conducted via Next Generation Sequencing (NGS) with “Relative quantification of mtDNA using NGS involved determination of the number of DNA sequence reads attributable to the mitochondrial genome as a fraction of the total number of reads. The great majority of DNA fragments sequenced are derived from the nuclear genome and provide a control for the number of cells in the biopsy specimen.” ([0152]) and “To verify these results using an unrelated methodology, the inventors applied a different type of whole genome amplification (WGA) method followed by NGS to TE biopsies derived from 38 additional blastocysts. The advantage of NGS technology is its capability to simultaneously examine nuclear and mitochondrial genomes. NGS analysis demonstrated that 14 of the blastocysts were euploid, whereas chromosome abnormalities were scored for the remaining 24. This finding was confirmed via aCGH conducted using separate aliquots of each WGA product. As with the real-time PCR results, statistical analysis of NGS data showed a significant increase (P=0.006) in the quantity of mtDNA in aneuploid blastocysts compared to those that were chromosomally normal. This provided independent confirmation of the real-time PCR findings. The NGS mtDNA data are illustrated in FIG. 3.” ([0157]).
It would have been prima facia obvious to combine the teachings of Wells and Nersisyan. A person of ordinary skill in the art would have been motivated to combine the teachings of Wells to include calculating the telomere length based on a sequencing result as taught by Nersisyan because Nersisyan’s method provides an accurate and reliable method for determining telomere lengths (abstract). Furthermore, there would have been a reasonable expectation of success, since both Wells and Nersisyan teach methods that pertain to the analysis of DNA.
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Wells (US 2017/107571 A1., published Apr. 20, 2017; as cited on the 01/16/2026 IDS Document) in view of Keefe (US 2016/0032360 A1., published Feb. 4, 2016; as cited on the 01/16/2026 IDS Document) and Qui ("Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method." Journal of translational medicine 17.1 (2019): 317.; as cited on the attached Notice of References 892 form) as applied to claims 1 and 13-15 under 35 U.S.C 103 as discussed above, and further in view of Balogun ("Comparative analysis of predictive models for the likelihood of infertility in women using supervised machine learning techniques." Computer Reviews Journal 2.1 (2018): 313-330.; as cited on the attached Notice of References 892 form).
Wells, Keefe and Qui are applied to claims 1 and 13-15 under 35 U.S.C 103 as discussed above.
Wells does not teach the claim limitation of wherein the basic information of the woman comprises a family disease history, a cause of infertility and a history of gynecologic disease of claim 6 and wherein the basic information of the woman comprises a history of examination and surgery of claim 7. However, these limitations are taught by Balogun.
Regarding claim 6, Balogun teaches the claim limitation of wherein the basic information of the woman comprises a family disease history, a cause of infertility and a history of gynecologic disease with “The variables identified include: age of menarche, age of marriage, family history of infertility, menstrual cycle, diabetes mellitus, hypertension, thyroid disease, pelvi-abdominal operation, endometriosis, fibroid disease, polycystic ovary, genital infection, previous termination of pregnancy, Sexually Transmitted Infection (STI) and the likelihood of infertility (identified using the labels: Likely, Unlikely and Probably) (Table 1).” (page 315, para. 2) and Table 1 (page 315). Table 1 lists Identified variables for determining infertility that include Family History of infertility, Menstrual cycle, Gynecological history and Medical and Surgical history. It is noted that the recited family disease history is interpreted to correspond to the family history of infertility as taught by Balogun.
Qiu also teaches the cause of infertility with “Taken together, we selected age, AMH, BMI, duration of infertility, previous live birth, previous miscarriage, previous abortion and type of infertility as predictors. Type of infertility was classified into tubal, anovulatory, male factor, unexplained and others (e.g. endometriosis, fibroids).” (page 4, col. 1, para. 1).
Regarding claim 7, Balogun teaches the claim limitation of wherein the basic information of the woman comprises a history of examination and surgery with Table 1 (page 315). Table 1 lists Identified variables for determining infertility that include Family History of infertility, Menstrual cycle, Gynecological history and Medical and Surgical history.
It would have been prima facia obvious to combine the teachings of Wells, Qui and Balogun. A person of ordinary skill in the art would have been motivated to combine the teachings of Wells to include the variables family disease history, gynecologic disease history and medical and surgical history as taught by Balogun and the cause of infertility as taught by both Qui and Balogun because these variables are risk factors of infertility that affect pregnancy. Furthermore, there would have been a reasonable expectation of success, since both Wells, Qui and Balogun teach methods that pertain to the analysis of factors affecting pregnancy.
Claims 8-9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wells (US 2017/107571 A1., published Apr. 20, 2017; as cited on the 01/16/2026 IDS Document) in view of Keefe (US 2016/0032360 A1., published Feb. 4, 2016; as cited on the 01/16/2026 IDS Document) and Qui ("Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method." Journal of translational medicine 17.1 (2019): 317.; as cited on the attached Notice of References 892 form) as applied to claims 1 and 13-15 under 35 U.S.C 103 as discussed above, and further in view of Uyar ("Predictive modeling of implantation outcome in an in vitro fertilization setting: an application of machine learning methods." Medical Decision Making 35.6 (2015): 714-725.; as cited on the attached Notice of References 892 form).
Wells, Keefe and Qui are applied to claims 1 and 13-15 under 35 U.S.C 103 as discussed above.
Wells does not teach the claim limitation of wherein the plurality of parameters further comprises an information about physical characteristics of the woman, and the information about physical characteristics of the woman comprises an endometrial thickness of claims 8 and 18 and wherein the information about physical characteristics of the woman comprises a hormone level of claim 9. However, these limitations are taught by Uyar.
Regarding claims 8 and 18, Uyar teaches the claim limitation of wherein the plurality of parameters further comprises an information about physical characteristics of the woman, and the information about physical characteristics of the woman comprises an endometrial thickness with Figure 3 (page 720). Figure 3 depicts that endometrial thickness is an input feature.
Regarding claim 9, Uyar teaches the claim limitation of wherein the information about physical characteristics of the woman comprises a hormone level with “These parameters included age of the woman, peak estradiol level, and amount of follicle stimulating hormone (FSH) administered, which were in accordance with earlier individual studies.” (page 722, col. 2, para. 2), Table 1 (page 717) and Figure 3 (page 720). Table 1 lists FSH and Figure 3 depicts that FSH amount is an input feature.
It would have been prima facia obvious to combine the teachings of Wells and Uyar. A person of ordinary skill in the art would have been motivated to combine the teachings of Wells to include the information on endometrial thickness and hormone level as taught by Uyar because these factors affect pregnancy. Furthermore, there would have been a reasonable expectation of success, since both Wells and Uyar teach methods that pertain to the analysis of factors affecting pregnancy.
Conclusion
No claims are allowed.
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/K.K./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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