DETAILED ACTION
Applicant’s response, filed 05 Feb. 2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-4 and 17-20 are cancelled.
Claims 5-16 and 21-28 are pending.
Claims 5-16 and 21-28 are rejected.
Priority
The effective filing date of the claimed invention is 21 Feb. 2018.
Information Disclosure Statement
The information disclosure statement filed 05 Feb. 2026 fails to comply with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 because it did not include a copy of each publication in accordance with CFR 1.98(a)(2).
It has been placed in the application file, but the information referred to therein has not been considered as to the merits. Applicant is advised that the date of any re-submission of any item of information contained in this information disclosure statement or the submission of any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the statement, including all certification requirements for statements under 37 CFR 1.97(e). See MPEP § 609.05(a).
Claim Interpretation
Claim 21 recites “generating… yield data and purity data for a number of proteins, the yield data and the purity data indicating yield and purity for each of a plurality of proteins over a range of pH values, over a range of salt concentrations, and for a stationary phase material of a column chromatography technique”. Given the limitation is being performed by one or more processors, the step of generating yield and purity data for a number of proteins is interpreted to encompass an in-silico analysis of already generated assay data (e.g. chromatography data) to determine the yield and purity.
Claim Rejections - 35 USC § 112(a)
The rejection of claims 5-10 under 35 U.S.C. 112(a) in the Office action mailed 04 Sept. 2025 has been withdrawn in view of claim amendments received 05 Feb. 2026.
Claim Rejections - 35 USC § 112(b)
The rejection of claims 6-7 under 35 U.S.C. 112(b) in the Office action mailed 04 Sept. 2025 has been withdrawn in view of claim amendments received 05 Feb. 2026.
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.
Claims 5-10 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. This rejection is newly recited and necessitated by claim amendment.
Claim 5, and claims dependent therefrom, are indefinite for recitation of “performing…a training process…, wherein the training process identifies, for individual stationary phrase materials of the plurality of stationary phase materials…”. Claim 5 previously recites “…determine purification data including…values determined using a plurality of stationary phase materials” in the third limitation and “performing…a training process…for a plurality of stationary phase materials”. As a result, it is unclear if “the plurality of stationary phase materials” the training process identifies is referring to the plurality of stationary phase materials of the purification data, of the plurality of stationary phase materials previously recited in the “performing…training” step, or if these are all intended to be the same plurality of stationary phase materials. For purpose of examination, each recitation of plurality of stationary phrase materials is interpreted to refer to the same stationary phase materials, given the purification data is used to generate training data. If Applicant agrees, claim 5 can be amended to recite “performing…a training process…for the [[a]] plurality of stationary phase materials…”.
Response to Arguments
Applicant’s arguments filed 05 Feb. 2026 regarding 35 U.S.C. 112(b) have been fully considered but they are not persuasive because they do not pertain to the new grounds of rejection set forth above.
Claim Rejections - 35 USC § 101
The rejection of claims 5-10 under 35 U.S.C. 101 in the Office action mailed 04 Sept. 2025 has been withdrawn in view of Applicant’s claim amendments and arguments received 05 Feb. 2026 at pg. 24, para. 4 to pg. 17, para. 1). In particular, the specific combination of assays and analytical techniques of performing laser ramen spectroscopy, performing one or more chromatography processes over a range of Ph values and a range of salt concentrations, performing one or more analytical tests to determine the recited measured attribute(s) are not conventional when considered in combination. While each individual technique is conventional, as demonstrated by the cited references in the Office action mailed 04 Sept. 2025, the combination of the assays in providing a particular training data set is unconventional, and thus the instant claims amount to significantly more than the recited judicial exception.
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 11-16 and 21-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea and law of nature without significantly more. Any newly recited portion is necessitated by claim amendment.
The Supreme Court has established a two-step framework for this analysis, wherein a claim does not satisfy § 101 if (1) it is “directed to” a patent-ineligible concept, i.e., a law of nature, natural phenomenon, or abstract idea, and (2), if so, the particular elements of the claim, considered “both individually and as an ordered combination,” do not add enough to “transform the nature of the claim into a patent-eligible application.” Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016) (quoting Alice, 134 S. Ct. at 2355). Applicant is also directed to MPEP 2106.
Step 1: The instantly claimed invention (claims 11 and 21 being representative) is directed to a method. Therefore, the instantly claimed invention falls into one of the four statutory categories. [Step 1: YES]
Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in in Prong Two if the recited judicial exception is integrated into a practical application of that exception.
Step 2A, Prong 1: Under the MPEP § 2106.04, the Step 2A (Prong 1) analysis requires determining whether a claim recites an abstract idea, law of nature, or natural phenomenon.
Claim 11 recites the following steps which fall under the mathematical concepts and/or mental processes groupings of abstract ideas:
determining yield values and purity values that include a yield value and a purity value for each well of the plurality of wells;
determining a reference dataset derived from a subset of the plurality of wells, the reference dataset including, for the subset of the plurality of wells, a portion of the yield values, a portion of the purity values, and combinations of stationary phase materials, pH values, and concentrations of the salt;
iteratively selecting, using a computational algorithm, additional subsets of the plurality of wells and determining an amount of error between additional yield values and additional purity values of the additional subsets of the plurality of wells and the portion of the yield values and the portion of the purity values of the reference data set until an optimized well arrangement is determined for which the amount of error is minimized;
generating, based on yield data, purity data, and chromatography conditions for the optimized well arrangement, a model to predict additional yield values and additional purity values for an additional protein;
obtaining data corresponding to an additional protein; and
determining….a plurality of yield values and a plurality of purity values for the additional protein with respect to a plurality of pH values, a plurality of salt concentrations, and a plurality of chromatography techniques.
Claim 21 recites the following steps which fall under the mathematical concepts and/or mental processes groupings of abstract ideas:
generating yield data and purity data for a number of proteins, the yield data and the purity data indicating yield and purity for each of the number of proteins over a range of pH values, over a range of salt concentrations, and for a plurality of stationary phase materials of a plurality of column chromatography techniques;
obtaining sequence data indicating at least a portion of amino acid sequences of individual proteins of the number of proteins;
obtaining structure data indicating one or more structures exhibited by individual proteins of the number of proteins;
generating characterization data for the number of proteins, the characterization data including values obtained from analytical tests that indicate values of properties of the number of proteins;
generating a model to predict, at one or more pH values and one or more salt concentration values, yield and purity of an additional protein for the plurality of stationary phase materials, wherein the model includes a sequence component that indicates a similarity between the amino acid sequences of the plurality of proteins and an additional amino acid sequence of the additional protein and a characterization component that indicates similarities between values of the properties for the number of proteins and additional values of the properties for the additional protein;
obtaining data corresponding to the additional protein; and
determining….a plurality of yield values and a plurality of purity values for the additional protein with respect to a plurality of pH values, a plurality of salt concentrations, and a plurality of chromatography techniques.
The identified claim limitations falls into the group of abstract ideas of mental processes for the following reasons. In this case, regarding claim 21, the step of determining or generating yield data and purity data encompasses analyzing generated chromatography column data, as discussed above in claim interpretation, which amounts to a mere analysis of data. Similarly, obtaining or determining sequence data indicating a portion of amino acid sequences and obtaining structure data indicating structures encompasses mentally analyzing mass spectrometry data and structural models or the ramen spectroscopy data of the proteins to identify a sequence and structure for each protein, which is a mental process. Furthermore, regarding claim 21 and generating characterization, reference or training data including values obtained from analytical tests can be performed mentally by analyzing data of the analytical tests to determine the characterization data (i.e. sequences, secondary structures, biophysical properties, etc., as discussed in para. [0043] of the specification) and by combining and organizing information generated from the various tests in claim 5 aided with pen and paper. The step of generating a model to predict yield and purity of an additional protein encompasses fitting a linear regression model to the yield and purity data using input data (i.e. sequences, pH values, salt concentrations) of the plurality of proteins, which can be practically performed in the mind aided by pen and paper by performing multiplication and addition. Furthermore, the model including a sequence component that indicates a similarity between sequences and a characterization component indicating similarities between values of the properties of proteins encompasses performing subtraction to identify a distance between points. Obtaining data corresponding to an additional protein encompasses analyzing information of a protein to determine data of interest for the protein, which is a mental process. Last, determining a plurality of yield and purity values for the protein with respect to a plurality of pH values, a plurality of salt concentrations, and a plurality of chromatography techniques amounts to a mental process because it involves inputting the input data for the additional protein into the trained model (e.g. a linear regression model) and performing multiplication and addition to determine outputs for each condition.
Regarding claim 11, the steps of determining a yield value and a purity value for each well of the plurality of wells encompasses analyzing completed chromatography column data to determine the amount of pure protein yielded, which amounts to a mere analysis of data. Determining a reference data set, as claimed, can be performed mentally by organizing information corresponding to a selected subset of the wells. Iteratively selecting additional subsets using a computational algorithm to minimize an error involves taking random subsets of wells, inputting corresponding information into a linear regression model to output a predicted purity/yield, subtracting the prediction from the observed purity/yield, and picking the subset of wells that resulted in the lowest error; this amounts to a mere analysis of data that can be performed mentally aided with pen and paper. Generating, based on yield, purity data, and chromatography conditions for the well arrangement, a model to predict additional yield and purity values can be practically performed in the mind aided with pen and paper by fitting a linear regression model using the known yield and purity values of the optimized subset of the reference set of wells. Obtaining data for an additional protein can be performed mentally as discussed above for claims 1 and 5. Last, determining a plurality of yield and purity values for the protein with respect to a plurality of pH values, a plurality of salt concentrations, and a plurality of chromatography techniques amounts to a mental process because it involves inputting the input data for the additional protein into the trained model (e.g. a linear regression model) and performing multiplication and addition to determine outputs for each condition.
Overall, the claims are analogous to the claims of "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind in Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). Furthermore, other than reciting these limitations are carried out by a processor or computing device, nothing in the claims precludes the steps from being practically performed in the mind. See MPEP 2106.04(a)(2) III.
The steps of generating a model to predict yield and purity of an additional protein, including the sequence component and characterization component of the model, iteratively selecting, using a computational algorithm, addition subsets and determining an amount of error until an optimized well arrangement is determined for which the error is minimized (claim 11), generating a model (as recited in claim 11), determining a metric indicating a similarity, and determining a plurality of yield and purity values for the additional protein with respect to a plurality of pH values, a plurality of salt concentrations, and a plurality of chromatography techniques further recite a mathematical concept. That is, the claims encompass using mathematical models, such as machine learning (see para. [0016]) to generate the models to calculate the yield and purity data , and subtraction to determine the recited similarities or similarity metric. Similarly, the iteratively selecting a subset using a computational algorithm by minimizing an error amounts to a textual equivalent to performing mathematical calculations (e.g. subtraction to calculate the error). Last, determining a plurality of yield and purity values for the protein with respect to a plurality of pH values, a plurality of salt concentrations, and a plurality of chromatography techniques amounts to a mental process because it involves inputting the input data for the additional protein into the trained model (e.g. a linear regression model) and performing multiplication and addition to determine outputs for each condition, which requires mathematical calculations. As such, these limitations amount to a textual equivalent to performing mathematical calculations, and thus recite a mathematical concept. See MPEP 2106.04(a)(2) I.
Last, claims 11 and 21 further recite the law of nature of a natural correlation between protein properties and environmental properties (i.e. pH and salt) and the proteins ability to bind a stationary phase material. 2106.04(b).
Dependent claims 12-13, 16, 22-28 further recite an abstract idea and/or are part of the abstract idea identified above. Dependent claim 12 further recites the mental process of assigning quadrants to a plate. Dependent claim 13 further limits the mental process of determining the reference to be from at least 75% of the wells in one of the quadrants. Dependent claim 16 further limits the mathematical concept of claim 11 to require selecting additional subsets using a Monte Carlo algorithm, which is a mathematical concept. Dependent claim 22 further limits the mental process and mathematical concept of generating the model to be a model to predict yield and purity for each of the number of proteins over a range of pH values and salt concentrations. Dependent claim 23 further recites the mental process and mathematical concept of generating, using the plurality of models, purification conditions including at least one pH value of the range of pH values, at least one salt concentration of the range of salt concentrations, and one or more stationary phase materials that maximize a combination of the yield and the purity of the protein in a chromatographic process and minimize a cost of performing the chromatographic process at the at least one pH value and the at least one salt concentration with respect to the one or more stationary phase materials. Dependent claim 24 further recites the mental process of determining the one or more stationary phase materials based at least partly on a durability of individual stationary phase materials of the plurality of stationary phase materials, determining an amount of the one or more stationary phase materials to be utilized in a chromatography column to purify the protein, and determining a size of the chromatography column. Dependent claim 25 further limits the mental process and mathematical concept of claim 23 to indicate utilizing a first and second stationary phase at a first pH and salt concentration and a second pH and salt concentration, respectively. Dependent claim 26 further recites the mental process of identifying a measure of performance for each well of a plurality of wells of a plate, the measure of performance of an individual well of the plurality of wells indicating adsorption of the protein with respect to the stationary phase material included in the individual well; individual wells of the plurality of wells include a stationary phase material of a column chromatography system, an amount of one or more proteins, and an amount of a solution having a pH and a concentration of a salt. Dependent claim 27 further limits the mental process of identifying a measure of performance to include yield or purity. Dependent claim 28 further recites the mental process and mathematical concept of generating a plurality of models based on the measurement of performance for each well. Therefore, claims 11-16 and 21-28 recite an abstract idea and/or law of nature. [Step 2A, Prong 1: YES]
Step 2A: Prong 2: Under the MPEP § 2106.04, the Step 2A, Prong 2 analysis requires identifying whether there are any additional elements recited in the claim beyond the judicial exception(s), and evaluating those additional elements to determine whether they integrate the exception into a practical application of the exception. This judicial exception is not integrated into a practical application for the following reasons.
Claims 12-13, 16, and 22-28 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
The additional elements of claims 11 and 21 include:
one or more processors (claim 21);
one or more non-transitory computer-readable storage media storing (claim 21); and
causing, by the one or more computing devices, display of a graphical user interface on a display device, the graphical user interface including: a number of user interface elements to capture first user input including information about the additional protein and to capture second user input indicating one or more types of results related to the plurality of chromatography techniques (i.e. data input); and an additional user interface element that includes a plurality of visual indicators that correspond to a plurality of chromatography techniques, individual visual indicators of the plurality of visual indicators indicating a yield value and a purity value and being selectable to modify the graphical user interface to display chromatography conditions that correspond to the yield value and the purity value and an indicator of monetary cost corresponding to the chromatography conditions (i.e. data output) (claims 11 and 21).
Regarding the processor, computer-readable storage medium/memory, receiving data, and displaying data, the courts have found the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).
Furthermore, the limitations relating to displaying information including visual indicators corresponding to chromatography techniques pertaining to an input additional protein, this limitation does not integrate the recited judicial exception into a practical application for the following reasons. First, the display does not appear to actually rely on or use the judicial exception (relating to generating a model to predict yield and purity of an additional protein) recited previously in the claims. Instead, the claim just broadly recites the interface includes visual indicators, but none of these indicators are required to provide information about the additional protein. The display includes “visual indicators” for a yield and purity value, but these are not required to be any of the yield or purity values determined in the previous step by the judicial exception for the additional protein.
Furthermore, while the interface includes user interface elements “selectable to modify…to display”, this merely requires the interface is interactive. As a result, this limitation merely serves to generally link the judicial exception to a particular technological environment (i.e. computers and interactive graphical user interfaces), which does not integrate the recited judicial exception into a practical application. See MPEP 2106.05(h). In addition, even if the displayed information was for the purity and yield values determined for the additional protein based on the model, this would only serve to output information generated by the abstract idea, which would not integrate the recited judicial exception into a practical application. See MPEP 2106.05(g).
The additional elements of claim 11 further include:
providing a plate having a plurality of wells, wherein individual wells of the plurality of wells include (i) a stationary phase material of a column chromatography system, (ii) an amount of a protein, and (iii) an amount of a solution having a pH and a concentration of a salt; wherein: each well of the plurality of wells has a different combination of the stationary phase material, pH, and concentration of the salt; the pH associated with each well of the plurality of wells is included in a range of pH values; the concentration of the salt associated with each well of the plurality of wells is included in a range of salt concentration values; and a first individual stationary phase material of a first number of wells of the plurality of wells is different from a second individual stationary phase material of a second number of wells of the plurality of wells; and
determining a measure of performance for each well of the plurality of wells, the measure of performance of an individual well of the plurality of wells indicating adsorption of the protein with respect to the stationary phase material included in the individual well.
The additional elements of claims 14-15 include:
wherein the range of pH values is about 3 to X (claim 14); and
wherein the stationary phase material is related to ion exchange chromatography, high pressure liquid chromatography, mixed mode chromatography, hydrophobic interaction chromatography, size exclusion chromatography, affinity chromatography, hydroxyapatite, reversed phase chromatography, or combinations thereof (claim 15).
The additional elements of claims 11 and 14-15 encompass providing a plate with wells with different combinations of a stationary phase, pH in a range of 3 to 8, and salt concentration and measuring a performance indicating adsorption of a protein for each well (i.e. determining protein yield after chromatography). These additional elements only serve to collect data for use by the abstract idea to generate the training data and ultimately the model to predict yield and purity of an additional protein, which amounts to insignificant extra-solution activity that does not integrate the recited judicial exception into a practical application. See MPEP 2106.05(g).
Therefore, the additionally recited elements amount to insignificant extra-solution activity and/or merely invoke computers as a tool to perform the abstract idea, and, as such, the claims as a whole do no integrate the abstract idea into practical application. Thus, claims 11-16 and 21-28 are directed to an abstract idea. [Step 2A, Prong 2: NO]
Step 2B: In the second step it is determined whether the claimed subject matter includes additional elements that amount to significantly more than the judicial exception. See MPEP § 2106.05.
The claims do not include any additional steps appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception for the following reasons. Claims 12-13, 16, 22-28 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception. The additional elements of claims 11, 14-15, and 21 are indicated above.
First, the computer, memory, processor, non-transitory computer-readable medium, inputting data, and outputting data, these are conventional computer components and/or functions. The courts have found the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).
The additional elements of claims 11 and 14-15 encompass providing a plate with wells with different combinations of a stationary phase, pH in a range of 3 to X, and salt concentration and measuring a performance indicating adsorption of a protein for each well (i.e. determining protein yield after chromatography).
The additional elements relating to chromatography are well-understood, routine, and conventional. This position is supported by Singh et al. (Downstream Processing Technologies/Capturing and Final Purification: Opportunities for Innovation, Change, and Improvement. A Review of Downstream Processing Developments in Protein Purification, Feb. 2017, Adv Biochem Eng Biotechnol, 165, pg. 115-178; previously cited). Singh reviews protein purification techniques, and best practices for design of experiments (DoE) approaches (Abstract; pg. 120, para. 3), citing several studies that utilize and overview DoE approaches (pg. 137, para. 2). Singh discloses such DoE approaches explore different concentrations of salt, protein concentration and pH levels from 6.5 to 7.5, with different combinations of a stationary phase, salt concentration, and pH levels arranged in wells of a plate, each well with an amount of protein (i.e. the plate includes a number of proteins) (Fig. 4, e.g. see plate setup with chromatography resin/stationary phase; Fig. 5, e.g. see design factors; pg. 139, para. 2 to pg. 140, para. 1), and then analyze the resulting protein yield for each design experiment (i.e. each well) (Fig. 5, e.g. see “response” column). Singh further discloses custom chromatography resin plates can be used that allow for the analysis of different resins in wells of the plate (i.e. a first and second stationary phase material) (pg. 140, para. 4 to 141, para. 1). Singh further discloses column chromatography is a traditional method that can be implemented in high throughput and DoE experiments (pg. 141, para. 1 and pg. 142, para. 1).
Last, the additional elements of the graphical user interface (including user interface elements that can capture information from a user is well-understood, routine, and conventional. First, Applicant’s own specification only states the user interface can include “selectable options” at para. [00114]-[00115], demonstrating the well-understood, routine, and conventional nature of the additional element. See MPEP 2106.05 I stating, the analysis as to whether an element (or combination of elements) is widely prevalent or in common use is the same as the analysis under 35 U.S.C. 112(a) as to whether an element is so well-known that it need not be described in detail in the patent specification. See Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1377, 118 USPQ2d 1541, 1546 ( Fed. Cir. 2016). Furthermore, Wang et al. (Open source libraries and frameworks for biological data visualization: A guide for developers, 2015, Proteomics, pg. 1356-1374; previously cited) reviews various graphical user interfaces for biological data (Abstract), including numerous publicly available visualization tools that allow for the creation of custom displays (i.e. they receive user input) (Table 1, Figure 3; pg. 1360, col. 1, para. 1 and col. 2, para. 3; pg. 1363, col. 2, para. 5), demonstrating the conventionality of user interfaces that have elements to receive user input. Wang further discloses various graphical user interfaces with interactive features and graphs (pg. 1662, col. 2, para. 2; pg. 1363, col. 1, para. 2-3; pg. 1634, col. 2, para. 2; pg. 1365, col. 2, para. 2-4), such that the functionality of selecting elements to display information is conventional in graphical user interfaces.
Therefore, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself. [Step 2B: NO]
Therefore, the instantly rejected claims are not drawn to eligible subject matter as they are directed to an abstract idea and natural correlation without significantly more. For additional guidance, applicant is directed generally to applicant is directed generally to the MPEP § 2106.
Response to Arguments
Applicant's arguments filed 05 Feb. 2026 regarding 35 U.S.C. 101 as applied to claims 11-16 and 21-28 have been fully considered but they are not persuasive.
Applicant remarks the claimed features allow for optimal conditions for purification of proteins being determined for a number of proteins without having to perform actual runs of chromatographic processes for each evaluated protein, citing para. [0023]-[0024] of the specification, and thus the cost of determining optimal conditions is reduced, and furthermore the claims improve the functioning if a computer that executes the model by minimizing an amount of data which saves computing resources (Applicant’s remarks at pg. 14, para. 1 to 3). Applicant further remarks previous approaches for determining chromatography conditions have a trial and error process based on journal articles, research papers, and textbooks, which is inefficient, and the claimed method utilizes machine learning with data collected with different chromatography techniques to predict optimal conditions, and therefore, the claimed method saves money and time and alleviates inefficiencies (Applicant’s remarks at pg. 14, para. 4 to pg. 15, para. 3). Applicant remarks the elements of claims 5 and 11 recite features that correspond to these improvements (Applicant’s remarks at pg. 15, para. 4 to pg. 17, para. 2).
This argument is not persuasive. It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. Furthermore, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology.
In the instant case, the alleged improvement in determining optimal purification conditions for proteins is an improvement to the abstract idea, which is not a technology. Applicant’s specification at para. [0020]-[0024] describes advantages of the generated model in predicting yield and purity for stationary phase materials based on a training data set. Applicant’s arguments cited above, similarly describe the solution to the problem of determining optimal chromatography conditions is the utilization of a machine learning model to predict the optimal conditions. Advantages of the generated model, amounts to an improved abstract idea (i.e. improved data analysis), rather than improvement to technology as set forth above.
Regarding Applicant’s argument that the claims improve the functioning of a computer by minimizing amount of data, MPEP 2106.05(a) states: in computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016), and further provides an example that the courts have indicated is not sufficient to improve computer-functionality of accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016). In the instant case, the claims are merely utilizing a general purpose computer to carry out the abstract idea, and the alleged improvement in computer-functionality is simply the result of utilizing a computer on an improved abstract idea that uses less data. This does not serve to improve the capabilities of the computer, and instead the claims invoke a computer as a tool to carry out an improved abstract idea, which is not an improvement to technology.
The additional elements pertaining to generating training data recited in the claims only serve to collect data for use by the abstract idea, which is not sufficient to integrate the judicial exception into a practical application as set forth in MPEP 2106.05(g). While it is acknowledged the claimed abstract idea of using a model to predict optimal chromatography conditions may be useful, as described above by Applicant, nor can one patent "a novel and useful mathematical formula," Parker v. Flook, 437 U.S. 584, 585, 198 USPQ 193, 195 (1978).
Applicant remarks that claims are not directed to a judicial exception because for most claim elements, the Office provides no explanation for why these claim elements are directed to mental steps or mathematical concepts and requests an explanation for why each of the features of claims 5, 11, and 21 are included in the mental process and mathematical concepts groupings (Applicant’s remarks at pg. 18, para. 1).
This argument is not persuasive. First, it appears Applicant intends to argue that the claims do not recite a judicial exception under Step 2A, Prong 1, rather than the claims are not directed to a judicial exception under Step 2A, Prong 2. Regarding, Step 2A, Prong 1, the previous Office action and the rejection above explicitly provides nearly 2 pages of explanation for the limitations reciting an abstract idea of claims 5, 11, and 21. Therefore, it is not clear what other explanation is being requested by Applicant.
Applicant remarks that some features of claims 5, 11, and 21 do not recite mathematical relationships, but are based on or involve a mathematical concept, including: “determining a reference dataset…”, “iteratively selecting, using a computational algorithm…”, “generating, based on yield data...a model to predict…” and “determining…executing the model, a plurality of yield values…” in claim 11; and “generating a model…” and “determining…executing the model, a plurality of yield values…” in claim 21 (Applicant’s remarks at pg. 18, para. 2 to pg. 21, para. 1). Applicant remarks that support that these features do not recite mathematical concepts are in the specification at para. [0017] and [0021] which state the models of claims 5, 11, and 21 are machine learning models (Applicant’s remarks at pg. 21, para. 2).
This argument is not persuasive. First, it is noted that the limitation of claim 11 of “determining a reference dataset” was not identified as reciting a mathematical concept, and instead was identified as reciting a mental process. Furthermore, MPEP 2106.04(a)(2) I. C. explains there is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
In the instant case, the claims are using words to describe a mathematical calculation when given the broadest reasonable interpretation in light of the specification. That is, the claims encompass using mathematical models, such as machine learning (see para. [0016]) to generate the models to calculate the yield and purity data , and subtraction to determine the recited similarities or similarity metric. For example, the claims encompass using and/or training a linear regression model to calculate the yield and purity data, which amounts to a textual equivalent to performing multiplication and addition to calculate values. Using mathematical methods to calculate values is not merely based on math, but simply uses words to describe mathematical calculations, consistent with MPEP 2106.04(a)(2) I. C. discussed above. Similarly, determining a similarity metric between sequences amounts to a textual equivalent to performing subtraction/ calculating a distance. It is further noted that these limitations also recite a mental process for the reasons discussed in the above rejection, regardless of whether they additionally recite a mathematical concept.
Last, the instant claims do not use a pseudo random number generator to generate a distribution of values and/or train a neural network on digital images as in Examples 38-39. Applicant is directed to Examples 47-49, which include various claims that recite an abstract idea despite reciting machine learning.
Applicant remarks training and implementing a machine learning model cannot be practically performed in the human mind because the training is performed with a specific set of training data (Applicant’s remarks at pg. 22, para. 3 to pg. 24, para. 1).
This argument is not persuasive. As explained in the above rejection, the step of generating a model to predict yield and purity of an additional protein encompasses iteratively fitting a linear regression model to the yield and purity data using input data (i.e. sequences, pH values, salt concentrations) of the plurality of proteins, which can be practically performed in the mind aided by pen and paper by performing multiplication and addition. It is not persuasive that a human mind is not equipped to perform multiplication and addition on values in a linear model to acquire an output, subtract the output from a known true output to determine a cost (e.g. in a cost function), adjust parameters of a linear model, and then recalculate the output.
Applicant remarks that the Office cation conclusory states that the claims recite a law of nature and that Applicant points out the claimed features do not recite laws of natures (Applicant’s remarks at pg. 24, para. 2).
This argument is not persuasive because Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out why the language of the claims do not recite a law of nature. Contrary to Applicant’s assertion, a clear explanation was provided as to the exact natural correlation recited in the claims.
Applicant’s remarks that the specific combination of additional elements in claims 5, 11, and 21, when considered in combination, are not well-understood, routine, and conventional under Step 2B, and points to the additional elements of claim 5 of performing mass spectrometry, performing laser ramen spectroscopy, performing a chromatography processes, and performing analytical tests which are used to generate a training set (Applicant’s remarks at pg. 24, para. 4 to pg. 26, para. 1).
First, this argument is persuasive with respect to claim 5, which requires the combination of performing mass spectrometry, performing laser ramen spectroscopy, performing a chromatography processes, and performing analytical tests, as noted by Applicant at pg. 24, para. 4 of the remarks.
However, claim 11 only includes the additional element of “providing a plate…”, as claimed, and therefore, Applicant’s arguments regarding the combination of assays/tests are not applicable to claim 11. Singh does demonstrate that design of experiment approaches in protein purification techniques, including providing plates with different stationary phase materials, pH and concentrations, are conventional. Similarly, claim 21 does not require any physical assays, and therefore these arguments are not applicable to claim 21.
Applicant remarks that Wang describes visualization techniques such as charts, networks, and hierarchical represents, but these do not provide a graphical user interface “that includes a plurality of visual indicators that correspond to the plurality of chromatography techniques, individual visual indicators…”, and therefore the features of claims 11 and 21 are not conventional (Applicant’s remarks at pg. 26, para. 2). Applicant remarks the physical testing procedures and graphical user interface features enable improved determination of chromatography conditions, and each limitation enhances the others to provide the improvement (Applicant’s remarks at pg. 26, para. 3 to pg. 27, para. 2).
This argument is not persuasive. First, Applicant’s arguments regarding an improvement are not persuasive for the reasons discussed above. These conclusions from Step 2A, Prong 2 are carried over to Step 2B, as set forth in MPEP 2106.05 II.
Furthermore, the type information displayed on the user interface is generated by and is part of the abstract idea, and therefore is not evaluated under step 2B. The claims simply utilize a conventional user interface with selectable elements to provide information generated by the abstract idea, which is not sufficient to provide significantly more.
Regarding Applicant’s argument that the display is conventional because there are no user interfaces that provide information such as “chromatography conditions” and “an indicator of monetary cost” in response to a selection of a visual indicator, data is abstract. Simply providing new information using a conventional user interface that has selectable elements is not sufficient to provide significantly more.
Regarding Applicant’s argument regarding the combination, each of the assays to generate data for the abstract idea (e.g. providing a plate) in claim 11 and conventional graphical user interface simply serves to gather information for use by the abstract idea and output information generated by the abstract idea, respectively, which is insignificant extra solution activity. 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. Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). Furthermore, Wang does demonstrate the conventionality of creating integrated data visualization for particular uses cases for biological data visualization (Abstract), as explained in the above rejection. Therefore, even considered in combination, the additional elements amount to conventional insignificant extra-solution activity that does not provide an inventive concept.
Conclusion
No claims are allowed.
Claims 5-10 are patent eligible for the reasons discussed above.
Claims 5-16, and 21-28 are free of the prior art for the reasons discussed in the Office action mailed 13 June 2024.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685
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