DETAILED ACTION
Claim Status
Claims 1-10, 14-22, 24 are pending.
Claims 1-10, 14-22, 24 are rejected.
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 .
Priority
This application claims Foreign Priority to application #GB2014608.0, filed 09/16/2020. Foreign Priority is acknowledged. Therefore, the effective filing date of claim(s) is 09/16/2020. This application is a 371 of PCT/GB2021/052400, filed 09/16/2021. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The Information Disclosure Statement filed on 06/06/2023 is in
compliance with the provisions of 37 CFR 1.97 and have been considered in full. A signed copy of list of
references cited from each IDS is included with this Office Action.
Drawings
The drawings filed on 03/15/2023 are accepted.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitation(s) is/are: “a device configured to perform quantitative analysis” in claim 1.
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
The “device” is described in figure 3 of the drawings, and on pages 12 (¶ 3) – 14 (¶ 4).
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
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 14 and 24 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 14’s “such as disease states” is exemplary language that makes the claim indefinite because it is unclear if these are just exemplary or if the claim is limited to disease states.
“The distributed sample” in claim 24 lacks antecedent basis. The examiner recommends amending the claim to depend from claim 22 to overcome the rejection.
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 1-10, 14-22, 24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
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 (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
1. set the parameters under which the quantitative analysis of the sample is performed in the device in dependence upon said retrieved data; perform analysis using a general model to create a predicted result of the quantitative analysis from the device;
1. compare said quantitative analysis received from the device with the predicted result; and update said data store with at least one of the output of the comparison and said received quantitative analysis data.
2. The system according to claim 1, wherein the output of the comparison between the quantitative analysis received from the device and the predicted result is a confirmation of the predicted result.
3. The system according to claim 1, wherein the output of the comparison between the quantitative analysis received from the device and the predicted result is a deviation from the predicted result.
4. The system according to claim 1, wherein circuitry configured to perform said analysis comprises a machine learning algorithm.
6. The system according to claim 5, wherein the processing circuitry is further configured to update the personal data relating to the individual's sample analyzed.
8. the step of updating the data store includes updating the accuracy score
9. The system according to claim 1, wherein each predicted result generated by the system has an associated accuracy score.
14. The system according to claim 4, wherein the machine learning algorithm includes a plurality of specific models relating to clinically relevant outputs such as disease states.
15. The system according to claim 4, wherein the machine learning algorithm is configured such that each quantitative analysis carried out by the device informs both specific and general models.
19. The system according to claim 4, wherein the parameters set by the machine learning algorithm include sample preparation parameters.
20. The system according to claim 4, wherein the parameters set by the machine learning algorithm include device conditions.
21. The system according to claim 4, wherein the parameters set by the machine learning algorithm include setting an expectation of the outcome of the analysis.
These claims set forth steps for “setting parameters,” “performing analysis,” and “comparing analysis” using a general model. The general model is limited to a machine learning model, but there are many simple embodiments of machine learning that can be performed by a person, such as linear regression. Thus, these are tasks that can be performed by a human being using a pen and paper. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. While claims recite performing some aspects of the analysis with a “processing circuitry”, there are no additional limitations that indicate that this processing circuitry requires anything other than carrying out the recited mental process or mathematical concept in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then if falls within the “Mental processes” grouping of abstract ideas. As such, claim(s) 1-10, 14-22, 24 recites 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). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to effect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment. Specifically, the claims recite the following additional elements:
1. A system for improving the quantitative analysis of a sample, the system comprising: a device configured to perform quantitative analysis of bio-macromolecular interactions in solution on a fluid sample to provided quantitative analysis data; a data store storing: personal data relating to a plurality of individuals; data relating to bio-macromolecular interactions; processing circuitry configured to access the data store and identify and retrieve data relevant to the sample;
1. receive quantitative analysis data of the sample from the device
5. The system according to claim 1, wherein the sample is obtained from an individual and wherein the processing circuitry is configured to perform further analysis of the quantitative analysis data received from the device in order to produce clinically relevant data for the patient.
7. the data relating to bio-macromolecular interactions includes anonymised data from individuals and experimental data.
8. each data point in the data store has an associated accuracy score
10. the data relating to bio-macromolecular interactions includes predicted data based on adjacent data.
16. The system according to claim 1, wherein the quantitative analysis of the sample includes a measurement of affinity of a bio-macromolecular interaction.
17. The system according to claim 1, wherein the quantitative analysis of the sample includes a measurement of the concentration of a bio- macromolecule of interest within the sample.
18. The system according to claim 1, wherein the quantitative analysis of the sample includes analysis of the heterogeneity of the sample.
22. the device comprises a microfluidic network configured to enable combination and distribution of a sample fluid and an auxiliary fluid to create a distributed sample and subsequent division of the distributed sample into two or more parts and measurement of at least one of the parts.
24. the device is configured to divide the distributed sample into more than two parts and measurement is carried out on each divided part.
There are no limitations that indicate that the claimed analysis engine or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
The limitations for receiving data are “mere data gathering”, similar to presenting offers and gathering statistics, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93. The limitations for the device are also “mere data gathering” as it is a form of performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989);
As such, claims 1-10, 14-22, 24 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 mere instructions to apply the recited exception in a generic way or in a generic computing environment. The instant claims recite additional elements enumerated above in the section on step 2A.
The steps for receiving data are well-understood, routine and conventional, similar to presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93. The limitations for the microfluidic device are well-understood, routine and conventional, see the abstract of Gharib et al. (Biosensors (Basel). 2022 Nov 16;12(11):1023.). Gharib’s device is a microfluidic device that separates fluids into two or more parts for measurement where measurement is carried out on the divided parts.
As discussed above, there are no additional limitations to indicate that the claimed analysis engine requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. The additional elements 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. Therefore, the claims do not amount to significantly more than the judicial exception itself ( Step 2B : No). As such, claims 1-10, 14-22, 24 are not patent eligible.
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.
Claims 1-4, 10, and 16-18 are rejected under 35 U.S.C. 103as being unpatentable over Keskin et al (Chem.Rev.2016,116,4884−4909) in view of Kaljurand et al. (Molecules 2021, 26, 4918.).
Regarding claim 1, Keskin discloses:
a system for improving the quantitative analysis of a sample, the system comprising (the abstract, last sentence, in combination with section "7. Computational Methods for Prediction of PPIs" on pages 4892-4893: each of the computational state-of-the-art implemented corresponds by to methods a reviewed computational the system for in system, Keskin improving quantitative analysis of a sample of claim 1):
the device configured to perform quantitative analysis of bio- macromolecular interactions in solution on a fluid sample to provided quantitative analysis data (page 4893, paragraph bridging the left and the right column, in particular the fourth sentence of this paragraph: "For positive interaction set, there are several resources which contain verified PPIs ...", in combination with section "11. PPI databases" on pages 4901-4902, in particular the first sentence in this section: it is implicit to the skilled person that the high- throughput and low-throughput experiments were performed on a fluid sample using at least one analysis device; see also section "2. Experimental detection of protein interactions" on pages 4886 and 4887);
Kaljurand’s device is a capillary electrophoresis device (abstract) with an H-filter (pg 5 ¶ 1) that separates fluids into their components for analysis. Comparing fig. 1 of Kaljurand to fig. 3 of the instant application confirms that they are the same type of device.
a data store storing (page 4893, paragraph bridging the left and the right column, in particular the fourth sentence of this paragraph: "For positive interaction set, there are several resources which contain verified PPIs ...", in combination with section "11. PPI databases" on pages 4901-4902: a PPI database in Keskin corresponds to the data store of claim 1):
data relating to bio-macromolecular interactions (page 4893, paragraph bridging the left and the right column, in particular the fourth sentence of this paragraph: "For positive interaction set, there are several resources which contain verified PPIs ...", in combination with section "11. PPI databases" on pages 4901-4902);
processing circuitry configured to access the data store and identify and retrieve data relevant to the sample (page 4893, paragraph bridging the left and the right column, in particular the fourth sentence of this paragraph: “the data required for the positive interaction set retrieved from verified PPIs corresponds to data relevant to the sample”);
set the parameters under which the quantitative analysis of the sample is performed in the device in dependence upon said retrieved data (page 4893, paragraph bridging the left and the right column, in particular the second sentence of this paragraph: “for training the classifiers the data from the PPIs databases is retrieved;” it is implicit in Keskin that at least one training parameter is based on data from the positive examples);
perform analysis using a general model to create a predicted result of the quantitative analysis from the device (second paragraph in section "7. COMPUTATIONAL METHODS FOR PREDICTION OF PPIS" on page 4893: the prediction model of a computational method of Keskin corresponds to the general model of claim 1); receive quantitative analysis data of the sample from the device (page 4893, paragraph bridging the left and the right column: “the data required for the positive interaction set retrieved from verified PPIs corresponds analysis data of the sample”);
to quantitive compare said quantitative analysis received from the device with the predicted result (second paragraph in section "7. COMPUTATIONAL METHODS FOR PREDICTION OF PPIS" on page 4893: it is implicit to the skilled person that supervised learning is trained on known data and validated by
comparing the predicted result to the known result; see also second to last paragraph in section 7 on page 4896 in Keskin: "5-fold cross— validation”);
The additional features of claims 2 and 3 comprise the two possible results of the comparison, which is implicit for the skilled person. If a method includes a result prediction before a final result is found, the only two outcomes from receiving the final result are that the prediction is confirmed, or that it deviates from the prediction. These two claims together form the entire universe of possibilities of the results of claim 1, and therefore do not limit claim 1 any further.
The additional features of claim 4 are disclosed in Keskin (see Keskin, first two paragraphs of section 7 on pages 4892 and 4893 of Keskin);
Regarding claim 16, Keskin teaches analyzing proteins within a sample (fig. 2).
Regarding claim 17, Keskin suggests analyzing concentration measures: “The types of PPI depend on different conditions, most importantly pH, protein concentration, concentration of other components in the cell, temperature, etc. (pg 4890 ¶ 2)”
Regarding claim 18, Keskin writes that their goal is to analyze the heterogeneity of the sample: “Further, protein−protein interactions are dynamic. They might change depending on the condition and state of the cell as explained above. This heterogeneity leads to difficulty in PPI detection techniques and thus in definition of an interactome. Pairwise protein interactions can be detected with high-throughput or low-throughput experimental techniques.” (pg 4885 right col ¶ 1).
Regarding claim 10, Keskin discloses an adjacency matrix for using similar shape proteins to predict the interactions (pg 4895, section 7.6, right col ¶ 3).
Regarding claims 1-4, 10, and 16-18, An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. Keskin provides suggestions to improve the computational analysis of protein-protein interactions, in order to proceed towards a more complete picture of proteome interactions (abstract). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art; when viewing the section of Keskin "11. PPI databases" on pages 4901-4902, in particular the first sentence in this section, it is implicit to the skilled person that the high- throughput and low-throughput experiments were performed on a fluid sample using at least one analysis device, similar to the microfluidic analysis device of Kaljurand. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Kaljurand by employing the suggested analysis steps of Keskin, in order to proceed towards a more complete picture of proteome interactions (abstract).
Claims 5-10, 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Keskin and Kaljurand as applied to claims 1-4, 10, 16-18 above, and further in view of Zhang et al. (PLoS Computational Biology, March 2011 | Volume 7 | Issue 3 | e1001114).
Keskin teaches the limitations these claims are dependent upon.
Regarding claim 5, Zhang discloses producing a cancer prognosis from PPI prediction (abstract).
Regarding claim 6, Zhang provides a suggestion to use personal mutation and expression data for the prognosis prediction and update the accuracy score (pg 8 right col ¶ 1).
Regarding claim 7, individual and experimental data is analyzed in Zhang (pg 8 right col ¶ 1).
Regarding claim 8, an accuracy score is updated in Zhang (pg 8 right col ¶ 1).
Regarding claim 9, an accuracy score is updated for each result (pg 8 right col ¶ 1).
Regarding claim 14, Zhang’s cancer prognosis (abstract) reads on the output of disease state.
Regarding claim 15, Keskin teaches a general model (second paragraph in section "7. COMPUTATIONAL METHODS FOR PREDICTION OF PPIS" on page 4893: the prediction model of a computational method of Keskin corresponds to the general model of claim 1).
Keskin is silent as to a specific model.
Zhang teaches specific models for per-patient prognosis of breast cancer outcomes (abstract).
Regarding claims 5-10, 14-15 An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. There is a teaching to use personal data to produce clinically relevant prognosis using specific models in the text of Zhang, in order to predict disease prognosis for specific patients (pg 8 right col ¶ 1). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art, as they are both machine learning methods for protein-protein interaction prediction. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Keskin by incorporating the specific models of Zhang, in order to improve the model’s predictive power for individual cancer prognosis (pg 8 right col ¶ 1).
Claims 19-21 are rejected under 35 U.S.C. 103 as being unpatentable over Keskin and Kaljurand as applied to claim 1-4, 10, 16-18 above, and further in view of Chicco (BioData Mining (2017) 10:35).
Regarding claims 19-21, Chicco discusses that machine learning datasets and parameters should be chosen based on domain-specific features and the scientific area being probed (pg 3 ¶ 5).
Regarding claims 19-21, An invention would have been prima facie obvious to one of ordinary
skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. There is a suggestion to use domain-specific features unique to the scientific area being probed in the text of Chicco (pg 3 ¶ 5). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art, as the specifics of the microfluidic device and an expected outcome would be available as possible domain-specific parameters that could be added. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Keskin by applying the suggestion of Chicco to use domain-specific parameters, in order to improve the predictive power of the model (pg 3 ¶ 5).
Claims 22 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Keskin and Kaljurand as applied to claim 1-4, 10, 16-18 above, and further in view of Masqualier et al. (US 9,975,122 B2).
The microfluidic device with partitioning of claim 1 of Masqualier teaches the microfluidic device of claims 22 and 24.
Regarding claims 22 and 24, An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. There is a teaching to use a partitioned microfluidic device in the text of Masqualier (claim 1). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art, as the device could create the input data for the method of Keskin. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Keskin by using a partitioned microfluidic device, in order to receive the input data (abstract).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRACELYN M HILL whose telephone number is (571)272-9871. The examiner can normally be reached Monday-Friday 8:30-5pm.
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/G.M.H./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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