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 .
Information Disclosure Statement
The IDS filed 7/28/2021 and 8/24/2021 have been considered by the Examiner.
Priority
Acknowledgment is made of applicant's claim for foreign priority under 35 U.S.C. 119(a)-(d) to EP 19154278.6 filed 1/29/2019.
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 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Process, Machine, Manufacture or Composition
Claims 1-12 are drawn to a method, so a process.
Step 2A Prong One: Identification of an Abstract Idea
The claim(s) recite(s):
1. Inputting abundance values for a panel of at least two obese pregnancy specific metabolite biomarkers of Table 15 obtained from an assayed biological sample, and optionally one or more clinical risk factors into a computational model.
This step reads on inputting information or applying data such as numerical values to a mathematical model. The step reads on math and can also be performed by the human mind and is therefore an abstract idea.
2. Inputting a patient parameter for the pregnant obese woman selected from at least one ethnicity, risk of gestational diabetes, fetal sex, number of pregnancies and level of obesity into the computational model.
This step reads on a process that can be performed by the human mind or with math. Selecting a patient parameter and inputting the parameter into a model reads entering values into a mathematical relationship. The step is therefore an abstract idea.
3. the computational model is configured to select from the panel a subset of obese pregnancy specific biomarkers comprising the two metabolite biomarkers.
The is step of selecting metabolite biomarkers can be performed by the human mind and is therefore an abstract idea.
4. calculate a predicted risk of pre-eclampsia based on the abundance value for the subset of biomarkers.
This step reads on a process that can be performed by the human mind or by math and is therefore an abstract idea. The step also recites a natural correlation between naturally occurring biomarkers and a biological condition which is preeclampsia.
Claim 2-12 further recite data and data analysis steps which further describe the recited abstract idea and are therefore also drawn to the abstract idea.
Step 2A Prong Two: Consideration of Practical Application
The claims are drawn to predicting a risk of pre-eclampsia based on biomarker abundance. The clams do not recite additional elements that integrate the judicial exception into a practical application.
This judicial exception is 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. The recited additional elements are drawn to:
“a computer implemented method”
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims include recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. The computer is tangentially applied as discussed in MPEP 2106.05(f). 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.
Claim Rejections - 35 USC § 112-2nd paragraph
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 1-12 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 pre-AIA the applicant regards as the invention.
Claim 1 recites “the abundance values for the subset of obese pregnancy specific biomarkers.” There is lack of antecedent basis support for this limitation. The claim does not recite selecting abundance values for the subset of biomarkers. It is suggested that the limitation instead recite “abundance values for the subset of obese pregnancy specific biomarkers.”
Claim 6 recites “the obese pregnancy specific protein is selected from.” There is lack of antecedent basis support for this limitation. The limitation should recite “an obese pregnancy specific protein is selected from.”
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims under 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of 35 U.S.C. 103(c) and potential 35 U.S.C. 102(e), (f) or (g) prior art under 35 U.S.C. 103(a).
Claims 1-12 are rejected under 35 U.S.C. 103(a) as being unpatentable over Kuc et al. (PLoS vol. 9 (2014) pages 1-8)
Kuc et al. teach determining specific signature patterns of metabolites altered in the first trimester of women who developed preeclampsia (PE) compared to healthy pregnancies (Abstract) and creating a model (page 5, col. 1, section “Model selection”) to predict onset of PE. Kuc et al. teach prediction models for early and late onset of preeclampsia based on metabolite biomarkers including taurine, asparagine and glyclylglycine (page 6, Table 4 and Figure 1)(i.e. instant specification Table 15, row 3 and 34)(i.e. model configured to select from the panel a subset of obese pregnancy specific markers comprising at least two parameter specific metabolite biomarkers), as in claim 1.
Kuc et al. teach applying a model for PE prediction to data of biomarkers (page 5, col. 1, section “Validation”)(i.e. calculate a prediction risk of pre-eclampsia based on abundance values for the subset of biomarkers), as in claim 1.
Kuc et al. teach that the model parameters are adjusted for gestation, weight and ethnicity (page 4, col. 1, par. 3)(i.e. inputting a patient parameter for pregnant obese women selected from ethnicity, risk of gestation and level of obesity).
Kuc et al. do not specifically teach “inputting abundance values” for metabolite biomarkers, as in claim 1.
Kuc et al. teach collecting serum concentrations of two standard placental biomarkers from blood (page 2, col. 1, section “Study populaton”); Kuc et al. teach identifying two molecules of which serum concentrations were significantly decreased in maternal serum (page 5, col. 2, par. 2)(i.e. abundance values for at least two metabolite obese pregnancy biomarkers)
It would have been obvious to one of ordinary skill in the art at the time the invention was made to have applied the process of Kuc et al. for creating a statistical model of biomarker data taken from obese pregnant women for the purpose of predicting preeclampsia wherein the statistical model receives biomarker concentration data (i.e. abundance values are input into the computational model). Kuc et al. provide motivation by teaching that concentrations of biomarkers and their differences are useful in the prediction of preeclampsia (page 1-2, connecting par. and page 2, col. 1, par. 1-3). Such a combination of elements taught by Kuc et al. is a combination that would yield a predictable result of using measured biomarker concentration in pregnant women to predict preeclampsia from previously determined biomarkers, by inputting measured concentration values.
Kuc et al. teach taurine and glyclylglycine as biomarkers, as in claims 2 and 4.
Kuc et al. teach characteristics for predicting PE pregnancies including male fetal sex (page 4, Table 2, line 12), adjusting model parameters according to fetal sex (page 3, col. 1, par. 2) and arterial pressure MAP (i.e. blood pressure) (page 3, col. 1, par. 2), as in claim 3.
Kuc et al. teach diagnosis of PE is typically based on protein in urine (proteinuria)(page 1, col. 1, par. 1); Kuc et al. also teach PAPP-A as a study biomarker (page 2, col. 1, section “Study population”) wherein it would be obvious to combine the biomarkers in the model taught by Kuc et al. with the additional biomarker of a PAPP-a protein also taught by Kuc et al. Such is a combination of known elements which would yield a predictable result of a model that includes biomarkers including an obese specific protein, as in claims 5-6.
Kuc et al. teach inputting prior risk (page 4, col.. 1, par. 4) and “MAP” mean arterial blood pressure into the model (page 6, Table 4 )(i.e. predict a risk based on clinical risk factors), as in claim 7.
Kuc et al. teach statistical analysis with logistic regression (Abstract) to predict development of PE in combination with metabolites and arterial pressure (i.e. combine abundance values of metabolites and clinical risk factor using a multivariable algorithm); Kuc et al. teach validation by using independent data in the biomarker based model and comparing the outcome to the model with only the prior risk (page 5, col. 1, section “Validation”)(i.e. compare risk score with a reference risk score); Kuc teach a that the models predict risk (page 4, col. 2, par. 2)(i.e output a predicted risk of pre-eclampsia based on the comparison), as in claim 8.
Kuc et al. teach determining the risk of early onset EO-PE and late onset LO-PE (page 4, col. 2, par. 2)(i.e. preterm and term pre-eclampsia), as claims 9-10.
Kuc et al. teach that their model includes “prior risk”; Kuc et al. include detecting risk to develop PE (page 5, col. 2, par. 1); Kuc et al. teach recognizing patients with “high risk” (page 1, col. 1, par. 1), wherein when risk is not detected, it is inherent that the subject is at “low risk,” as in claims 11-12.
E-mail communication Authorization
Per updated USPTO Internet usage policies, Applicant and/or applicant’s representative is encouraged to authorize the USPTO examiner to discuss any subject matter concerning the above application via Internet e-mail communications. See MPEP 502.03. To approve such communications, Applicant must provide written authorization for e-mail communication by submitting the following statement via EFS Web (using PTO/SB/439) or Central Fax (571-273-8300):
Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.
Written authorizations submitted to the Examiner via e-mail are NOT proper. Written authorizations must be submitted via EFS-Web (using PTO/SB/439) or Central Fax (571-273-8300). A paper copy of e-mail correspondence will be placed in the patent application when appropriate. E-mails from the USPTO are for the sole use of the intended recipient, and may contain information subject to the confidentiality requirement set forth in 35 USC § 122. See also MPEP 502.03.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Anna Skibinsky whose telephone number is (571) 272-4373. The examiner can normally be reached on 12 pm - 8:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Ram Shukla can be reached on (571) 272-7035. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Anna Skibinsky/
Primary Examiner, AU 1635