CTNF 18/007,126 CTNF 99265 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. Claim Status Claims 1-26 are pending. Claims 1-26 are rejected. Priority Applicant's claim for the benefit of a prior-filed application, 371 of PCT/US21/41973, filed, 07/16/2021, which claims benefit of 63/058,050 07/29/2020 is acknowledged. Accordingly, each of claims 1-26 are afforded the effective filing date of 07/29/2020. Information Disclosure Statement The information disclosure statements (IDS) filed on 01/27/2023, 09/22/2025, 12/17/2025, and 05/19/2026 are in compliance with the provisions of 37 CFR 1.97 and have therefore been considered. Signed copies of the IDS documents are included with this Office Action. Drawings The Drawings submitted 01/27/2023 are accepted. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more. MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials. Framework with which to Evaluate Subject Matter Eligibility : Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter; Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e . a law of nature, a natural phenomenon, or an abstract idea; Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept. Framework Analysis as Pertains to the Instant Claims: Step 1 With respect to Step 1 : yes, the claims are directed to method, system, and, non-transitory computer-readable medium i.e. , a process, machine, or manufacture within the above 101 categories [ Step 1: YES ; See MPEP § 2106.03]. Step 2A, Prong One With respect to Step 2A, Prong One , the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as: mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations); certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information). With respect to the instant claims , under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) are as follows: Independent claims 1, 12 and 21 : predicting , by the one or more processors applying the respective set of resin attribute values as inputs to a multivariate statistical model , a respective value of a performance indicator for the column chromatography purification process; selecting a resin of the one or more candidate resins based at least in part on the one or more predicted respective values of the performance indicator Dependent claims 5, 16, and 25: predicting a level of host cell protein resulting from the column chromatography purification process. Dependent claims 6 and 17: comparing the one or more respective values of the performance indicator to a predetermined acceptability threshold Dependent claim 7: predicting a respective range of values of the performance indicator; and comparing each of the one or more respective ranges of values to a predetermined acceptability threshold. Dependent claims 8, 18, and 26: applying the respective set of resin characteristics as inputs to a projection on latent structures (PLS) regression model Dependent claim 11: training the multivariate statistical model using historical small-scale and commercial-scale chromatography purification process data. Dependent claims 2-4, 9-10, 13-15, and 17-20 recite further steps that limit the judicial exceptions in independent claim 1 and, as such, also are directed to those abstract ideas. For example, claims 2-4 and 13-15 further limit the input of claim 1, claims 9-10 further limit the resin attributes of claim 1; Under the BRI, the instant claims recite judicial exceptions that are an abstract idea of the type that is in the grouping of a “mental process”, such as procedures for evaluating, analyzing or organizing information, and forming judgement or an opinion. The instant claims further recite judicial exceptions that are an abstract idea of the type that is in the grouping of a “mathematical concept”, such as mathematical relationships and mathematical equations. The claim recites selecting and comparing. The human mind is capable of selecting a resin and comparing the one or more respective values of the performance indicator to a predetermined acceptability threshold. The claims recite a mathematical concepts of predicting, by the one or more processors applying the respective set of resin attribute values as inputs to a multivariate statistical model, predicting a level of host cell protein, predicting a respective range of values of the performance indicator, applying the respective set of resin characteristics as inputs to a projection on latent structures (PLS) regression model, and training the multivariate statistical model. Therefore, claims 1, 12, and 21 and those claims dependent therefrom recite an abstract idea [ Step 2A, Prong 1: YES ; See MPEP § 2106.04]. Step 2A, Prong Two Because the claims do recite judicial exceptions, direction under Step 2A, Prong Two , provides that the claims must be examined further to determine whether they integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III). Additional elements, Step 2A, Prong Two With respect to the instant recitations, the claims recite the following additional elements : Independent claim 1: receiving , by one or more processors of a computing system, a respective set of resin attribute values, the respective set of resin attribute values including at least one analytical measurement of the candidate resin; for each of the one or more candidate resins performing the column chromatography purification process using the selected resin as a stationary phase. Independent claim 12: receive a respective set of resin attribute values, the respective set of resin attribute values including at least one analytical measurement of the candidate resin display the respective value of the performance indicator, or a result based on the respective value of the performance indicator, to a user to facilitate selection of a resin of the one or more candidate resins based at least in part on the one or more predicted respective values of the performance indicator a column chromatography system Independent claim 21: receive a respective set of resin attribute values, the respective set of resin attribute values including at least one analytical measurement of the candidate resin display the respective value of the performance indicator, or a result based on the respective value of the performance indicator, to a user to facilitate selection of a resin of the one or more candidate resins, for use as a stationary phase in the column chromatography purification process, based at least in part on the one or more predicted respective values of the performance indicator The claims also include non-abstract computing elements. For example, independent claims 1, 12, and 21 includes a computing system and a non-transitory computer-readable medium. Considerations under Step 2A, Prong Two With respect to Step 2A, Prong Two , the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “ receive(ing) ”, and to data outputting, such as “ display ”, perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)). Further steps directed to additional non-abstract elements of “computing system and a non-transitory computer-readable medium” do not describe any specific computational steps by which the “computer parts” perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, and therefore the claim does not integrate that judicial exceptions into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc.… are recited so generically ( i.e. , no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (MPEP 2106.05(f)). The additional elements of performing the column chromatography purification process using the selected resin as a stationary phase and a column chromatography system do not integrate the judicial exception into a practical application because these steps constitute as insignificant extra solution activity of data gathering. These additional elements only interact with the judicial exception by providing data to be processed by the judicial exception. Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [ Step 2A, Prong 2: NO ; See MPEP § 2106.04(d)]. Step 2B (MPEP 2106.05.A i-vi) According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s). With respect to the instant claims , the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)). As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)). With respect to claims 1, 12, and 21 and those claims dependent therefrom, the computer-related elements or the general purpose computer do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (see MPEP 2106.06(A)). The specification also notes that computer processors and systems, as example, are commercially available or widely used at [ 0034-0041 ]. The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III). The additional elements of performing the column chromatography purification process using the selected resin as a stationary phase and a column chromatography are well-understood, routine, and conventional in the art. The specification discloses the column chromatography system may be a commercial-scale column chromatography system used during the commercial manufacture of a therapeutic protein [0048]. The process of performing the column chromatography purification process is well known as disclosed by Rathorne et al. (Rathore, Anurag S., Devashish Kumar, and Nikhil Kateja. "Recent developments in chromatographic purification of biopharmaceuticals." Biotechnology letters 40.6 (2018), newly cited). Rathorne discloses dramatic improvements in development of novel stationary phases, in base bead as well as ligand chemistry to address the increased purity and capacity demands of modern bioprocessing in chromatographic resins [p. 896, col. 1, par. 4]. do not rise to the level of significantly more than the judicial exception. Therefore, the additional elements do not amount to significantly more than the above-identified judicial exception(s). 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 ; See MPEP § 2106.05]. Therefore, the instant claims are not drawn to eligible subject matter as they are directed to one or more judicial exceptions without significantly more. For additional guidance, applicant is directed generally to the MPEP § 2106. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-aia AIA Claim(s) 1-6, 12-17, and 21-25 is/are rejected under 35 U.S.C. 102 (a)1 as being anticipated by Hanke et al. (Hanke, Alexander T., and Marcel Ottens. "Purifying biopharmaceuticals: knowledge-based chromatographic process development." Trends in biotechnology 32.4 (2014), cited on IDS dated 01/27/2023) . Claim 1 is directed to a method of selecting raw materials for use in a column chromatography purification process, Hanke discloses novel techniques during various stages of biopharmaceutical downstream process development such as resin screening [p. 217, table 2]. Hanke further discloses Process Analytical Technology (PAT) as the use of process understanding, monitoring of raw material quality, and CPPs throughout the process to adjust process parameters in real- time with the goal of producing products with consistent quality [p. 210, glossary]. Hanke further discloses once the combination of models and parameters have been found to give sufficiently accurate predictions, the ability to simulate process performance can be useful during many stages of process development [p. 216, col. 2, par. 3]. Hanke also discloses one of the first choices that has to be made is a selection of resins to be used for the process [p. 216, col. 2, par. 3]. Hanke further discloses model-based approaches have been demonstrated to allow rational and fair comparison of resin separation performance under ideal conditions for each resin, while reducing the experimental load compared to conventional column scouting [p. 216, col. 2, par. 3]. the method comprising: for each of one or more candidate resins, receiving, by one or more processors of a computing system, a respective set of resin attribute values, the respective set of resin attribute values including at least one analytical measurement of the candidate resin; Hanke discloses schematic representation of the processes taking place inside a chromatographic column on the microscopic scale and the parameters commonly used to describe protein molecular properties, resin properties, and their interactions [p. 212, fig. 1]. Hanke further discloses resin properties including bed porosity, particle size distribution, particle porosity, pore size distribution, and ligand density. Hanke also discloses temperature, conductivity, ligand charge and other analytical measurements [p. 212, fig. 1]. for each of the one or more candidate resins, predicting, by the one or more processors applying the respective set of resin attribute values as inputs to a multivariate statistical model, Hanke discloses in this context the relationship between the CPP and CQA is usually of a statistical nature derived from a response surface analysis of a design of experiments (DoE) or multivariate data analysis [p. 211, col. 1, par. 2]. Hanke further discloses a 3D multivariate calibration based on the molecular weight, pI, and hydrophobicity of the proteins [p. 214, col. 2, par. 2]. Hanke also discloses the 3D characterization principle coupled to a multivariate random-forest calibration has shown mixed results [p. 214, col. 2, par. 2] which reads on a multivariate statistical model. a respective value of a performance indicator for the column chromatography purification process; Hanke discloses once the combination of models and parameters have been found to give sufficiently accurate predictions, the ability to simulate process performance can be useful during many stages of process development [p. 216, col. 2, par. 3]. Hanke further discloses one of the first choices that has to be made is a selection of resins to be used for the process [p. 216, col. 2, par. 3]. Hanke also discloses model-based approaches have been demonstrated to allow rational and fair comparison of resin separation performance under ideal conditions for each resin, while reducing the experimental load compared to conventional column scouting [p. 216, col. 2, par. 3]. selecting a resin of the one or more candidate resins based at least in part on the one or more predicted respective values of the performance indicator; and performing the column chromatography purification process using the selected resin as a stationary phase. Hanke discloses resin screening by techno-economic-driven selection based on productivity estimates and structure-based calculations or QSOR/MD [p. 217, table 2] and [p. 213, fig. 2]. Claims 2, 13, and 22 are directed to the method of claim 1, wherein predicting the respective value of the performance indicator further includes applying one or more harvest filtrate parameter values as inputs to the multivariate statistical model. Hanke discloses schematic representation of the processes taking place inside a chromatographic column on the microscopic scale and the parameters commonly used to describe protein molecular properties, resin properties, and their interactions [p. 212, fig. 1] which includes ph as a harvest parameter. Hanke further discloses the exact definitions of each parameter may vary with the models applied and some models may require only a subset or even more than the presented parameters [p. 212, fig. 1]. Claims 3, 14, and 23 are directed to the method of claim 1, wherein predicting the respective value of the performance indicator further includes applying one or more purification process parameter values as inputs to the multivariate statistical model. Hanke discloses schematic representation of the processes taking place inside a chromatographic column on the microscopic scale and the parameters commonly used to describe protein molecular properties, resin properties, and their interactions [p. 212, fig. 1] which includes conductivity as a purification process parameter. Hanke further discloses the exact definitions of each parameter may vary with the models applied and some models may require only a subset or even more than the presented parameters [p. 212, fig. 1]. Claims 4, 15, and 24 are directed to the method of claim 1, wherein predicting the respective value of the performance indicator includes applying (i) the respective set of resin attribute values, (ii) one or more harvest filtrate parameter values, and (iii) one or more purification process parameter values as inputs to the multivariate statistical model. Claim 4 is a combination of claims 1-3 and the cited art above applies. Claims 5, 16, and 25 are directed to the method of claim 1, wherein predicting the respective value of the performance indicator includes predicting a level of host cell protein resulting from the column chromatography purification process. Hanke discloses the HCP level, it is one known performance indicator of a chromatography purification process [p. 211, Box 1]. HCP level would therefore be used an indicator of resin selectivities [Table 2 Item 2 tasks] without use of any inventive skills. Claims 6 and 17 is directed to the method of claim 1, wherein selecting the resin includes comparing the one or more respective values of the performance indicator to a predetermined acceptability threshold. Hanke discloses in the purification process that at the second viral removal stage the 20-50 nm cut-off viral filtration threshold is used [p. 211, box 1] which reads on a performance indicator threshold. Claim 7 is directed to the method of claim 1 wherein: predicting the respective value of the performance indicator includes predicting a respective range of values of the performance indicator; and selecting the resin includes comparing each of the one or more respective ranges of values to a predetermined acceptability threshold. Hanke discloses a validated model allows analyzing the process towards robustness design space defined as the combination of ranges of process parameters and material quality attributes that have been demonstrated to result in a product compliant to the quality requirements [glossary]. Using threshold and range values to define target performance is common practice for defining target indicator that would be used without use of any inventive skills Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-20-02-aia AIA This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. A. Claims 8-9, 18-19, and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Hanke , as applied to claim 1as above, and in view of Robinson et al. (Robinson Julie r. et al: "QSAR models for prediction of chromatographic behavior of homologous Fab variants : QSAR Models for Fab Variants", BIOTECHNOLOGY AND BIOENGINEERING, vol. 114, no. 6, 12 December 2016, cited on IDS dated 01/27/2023). Claims 8, 18, and 26 are directed to the method of claim 1, wherein predicting the respective value of the performance indicator includes applying the respective set of resin characteristics as inputs to a projection on latent structures (PLS) regression model. Hanke discloses a powerful complementary technique to experimental parameter determination lies in their calculation through predictive models [p. 216, col. 1, par. 2]. Hanke further discloses using QSAR which models quantitative structure–activity relation [p. 213, fig. 2], but is silent on a (PLS) regression model. However, Robinson discloses QSAR models for prediction of chromatographic behavior of homologous fab variants [title]. Robinson further discloses using PLS as predictive model and training model is known [p. 1233, col. 1, QSAR model development] and would be used without use of any inventive skills when training a predictive QSAR model. Claims 9 and 19 are directed to t he method of claim 1, wherein, for each of the one or more candidate resins, receiving the respective set of resin attribute values includes receiving resin attribute values provided by a manufacturer or supplier of the candidate resin. Hanke discloses resin screening with resin selectivities through high-throughput batch absorption experiments [p. 217, table 2]. Hanke further discloses models can be connected to multiple data sources ranging from experimentally determined parameters to molecular dynamics based predictions [p. 218, col. 1, par. 2], but is silent on values provided by a manufacturer or supplier of the candidate resin. However, Robinson discloses the present study extends the existing framework by enabling in silico screening of Fab variant retention behavior based on an existing body of experimental data on similar Fabs [p. 1231, col. 1, par. 2] which reads on using solely data to run the experiment. The specification does not describe why it must come from a COA, therefore, the data is not dependent on the origin of the resin data. In regards to claim(s) 8-9, 18-19, and 26, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hanke with Robinson as they both disclose selecting resins for use in chromatography purification processes. The motivation would have been to modify the multivariate model of Hanke with the PLS model of Robinson to facilitate process development for the purification of biological products from product-related impurities by in silico screening of resin alternatives as disclosed by Robinson [abstract]. One could have therefore combined the elements as claimed by the known methods of Hanke and Robinson, and that in combination, each element merely would have performed the same function as it did separately for a predictable result. B. Claims 10-11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Hanke , as applied to claim 1 as above, and in view of Facco et al. (Facco, Pierantonio, et al. "Multivariate statistical estimation of product quality in the industrial batch production of a resin." IFAC Proceedings Volumes 40.5 (2007), newly cited) Claims 10 and 20 are directed to t he method of claim 1, wherein, the one or more candidate resins include a plurality of candidate resins that correspond to different manufacturing lots of a single resin type. Hanke is silent on candidate resins include a plurality of candidate resins that correspond to different manufacturing lots of a single resin type. However, Facco discloses multivariate statistical estimation of product quality in the industrial batch production of a resin [title]. Facco discloses in the last two decades, multivariate statistical techniques have proved to be excellent tools for the analysis and monitoring of processes where lots of process data are available [p. 94, col. 2, par. 1]. Facco also discloses the net result of this quite complex (and mostly manually driven) operating recipe is that, although the end-point quality of the resin usually falls within a very narrow range, the “internal” variability of the batches is very large [p. 95, col. 1, par. 4]. Facco further discloses the design of a system for the online monitoring of the whole production process, the design of a soft sensor for the estimation of µ and N A is considered, with the objective to make available online frequent and accurate estimations of the product quality indicators [p. 95, col. 2, par. 2]. Facco also discloses the quality monitoring approach we have developed relies on the partial least squares (PLS) regression technique [p. 95, col. 2, par. 3]. Claim 11 is directed to the method of claim 1, wherein: the column chromatography purification process is a commercial-scale chromatography purification process; and the method further comprises training the multivariate statistical model using historical small-scale and commercial-scale chromatography purification process data. Hanke is silent on the scale of the purification process. However, Facco discloses multivariate statistical estimation of product quality in the industrial batch production of a resin [title] which reads on commercial scale resin production for manufacture high added value goods, such as specialty chemicals and biochemicals, materials for microelectronics, and pharmaceuticals [p. 93, col. 1, par. 1]. In regards to claim(s) 10-11 and 20, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hanke with Facco as they both disclose ensuring quality resin for use in chromatography purification processes. The motivation would have been to modify the input data of multiple resin products of Hanke with the batches of a single product of Facco to improving the process development for the purification of biological products by to provide online the estimation of the acidity number and viscosity of a resin produced in an industrial batch polymerization process as disclosed by Facco [p. 98, col. 2, par. 1]. One could have therefore substituted the elements as claimed by the known methods of Hanke and Robinson, and that in substitution, each element merely would have performed the same function as it did separately for a predictable result. Conclusion No claims are allowed. Inquiries Any inquiry concerning this communication or earlier communications from the examiner should be directed to Dawn M. Bickham whose telephone number is (703)756-1817. The examiner can normally be reached M-Th 7:30 - 4:30. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached at 571-272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /D.M.B./Examiner, Art Unit 1685 /Soren Harward/Primary Examiner, TC 1600 Application/Control Number: 18/007,126 Page 2 Art Unit: 1685 Application/Control Number: 18/007,126 Page 3 Art Unit: 1685 Application/Control Number: 18/007,126 Page 4 Art Unit: 1685 Application/Control Number: 18/007,126 Page 5 Art Unit: 1685 Application/Control Number: 18/007,126 Page 6 Art Unit: 1685 Application/Control Number: 18/007,126 Page 7 Art Unit: 1685 Application/Control Number: 18/007,126 Page 8 Art Unit: 1685 Application/Control Number: 18/007,126 Page 9 Art Unit: 1685 Application/Control Number: 18/007,126 Page 10 Art Unit: 1685 Application/Control Number: 18/007,126 Page 11 Art Unit: 1685 Application/Control Number: 18/007,126 Page 12 Art Unit: 1685 Application/Control Number: 18/007,126 Page 13 Art Unit: 1685 Application/Control Number: 18/007,126 Page 14 Art Unit: 1685 Application/Control Number: 18/007,126 Page 15 Art Unit: 1685 Application/Control Number: 18/007,126 Page 16 Art Unit: 1685 Application/Control Number: 18/007,126 Page 17 Art Unit: 1685 Application/Control Number: 18/007,126 Page 18 Art Unit: 1685 Application/Control Number: 18/007,126 Page 19 Art Unit: 1685 Application/Control Number: 18/007,126 Page 20 Art Unit: 1685 Application/Control Number: 18/007,126 Page 21 Art Unit: 1685
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