DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
1. Claims 1-15 as amended on May 29, 2024, are pending and under consideration.
Priority
2. Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of the first paragraph of 35 U.S.C. 112. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosures of the prior-filed applications fail to provide adequate support or enablement in the manner provided by the first paragraph of 35 U.S.C. 112 for one or more claims of this application. Examiner has established a priority date of February 14, 2024 for claims 1-15 because the claims as currently constituted recite: c. importing the data values from said online sensors into a computer database, where they are evaluated by a statistical analysis model which is built on an independent training data set obtained previously in at least one model training run, wherein said training data set comprises offline data providing values of concentration, purity and/or potency, wherein the offline data were obtained based on samples being removed from the process, and online data corresponding to the time frame of the offline data, thereby performing a multivariate statistical analysis for determination of the at least one of concentration, purity, and potency of the biological product, and a review of the parent applications does not reveal the claimed limitation. Applicant is invited to submit evidence pointing to the serial number, page and line where support can be found establishing an earlier priority date.
Specification
3. The use of the term Äkta Pure, which is a trade name or a mark used in commerce, has been noted in this application. See AKTA PURE (Reg. No. 6580007, 2012-12-07). The term should be accompanied by the generic terminology; furthermore the term should be capitalized wherever it appears or, where appropriate, include a proper symbol indicating use in commerce such as ™,SM, or ® following the term.
Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) are permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
The specification is also objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). The claimed subject matter that does not have antecedent basis in the specification is c. importing the data values from said online sensors into a computer database, where they are evaluated by a statistical analysis model which is built on an independent training data set obtained previously in at least one model training run, wherein said training data set comprises offline data providing values of concentration, purity and/or potency, wherein the offline data were obtained based on samples being removed from the process, and online data corresponding to the time frame of the offline data, thereby performing a multivariate statistical analysis for determination of the at least one of concentration, purity, and potency of the biological product.
Because the claims as filed in the original specification are part of the disclosure, even though the material disclosed in the claims is not disclosed in the remainder of the specification, the applicant may amend the specification to include the claimed subject matter. In re Benno, 768 F.2d 1340, 226 USPQ 683 (Fed. Cir. 1985). Thus, amendment of the specification to include the material disclosed in the claims will obviate this objection.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
4. Claims 2 and 5 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claims 2 and 5 recite pH sensor(s) and temperature sensor(s). Claim 1, from which claims 2 and 5 depend, does not recite pH sensor(s) and temperature sensor(s) in the sensor Markush group. Thus, claims 2 and 5 fail to further limit the subject matter of the claim upon which they depend.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
5. Claim(s) 1, 2, 4-7, 10-13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over US 2014/0136146 A1 (McCready, CP May, 15, 2014), “McCready-146”.
McCready-146 teaches at paragraph 0010:
. . a prediction system for a batch-type manufacturing process associated with a finite duration is provided. The prediction system includes one or more sensors for measuring values of a plurality of variables of the manufacturing process including at least one dependent variable that represents a process parameter whose value is dependent on one more process conditions. The measured values include measured values of the plurality of variables associated with at least one historical batch run and measured values of the plurality of variables associated with at least one current batch run. The prediction system also includes a prediction module for estimating an unknown future value of the at least one dependent variable at a future point in time in the at least one current batch run using a partial least squares (PLS) regression approach. The prediction module includes a calibration component and an estimation component. The calibration component is configured to determine (1) a X matrix including the measured values of the plurality of variables associated with the at least one historical batch run, (2) a Y matrix including the measured value of the at least one dependent variable associated with the at least one historical batch run; and (3) a relationship between the X matrix and the Y matrix determined based on the PLS regression approach. The estimation component is configured to estimate the unknown future value of the at least one dependent variable in the at least one current batch run using the relationship from the calibration component and the measured values of the plurality of variables associated with the at least one current batch run.
McCready-146 teaches partial least squares (PLS) regression is a multivariate analysis. See ¶ 0005.
McCready-146 teaches monitoring the manufacturing process with a means for performing multivariate analysis on a combination of (1) the measured values of the variables and (2) at least one of the future values of the manipulated variables or the future values of the dependent variables to generate multiple multivariate statistics. See ¶¶ 0018-0021 and Fig. 1.
McCready-146 teaches that the process is useful pharmaceutical, biopharmaceutical fermentation and cell culture processes for predicting the future behavior of a manufacturing process in real time or in near real time. See ¶¶ 0003, 0008, 0016 and 0079.
McCready-146 teaches at paragraph 0016:
In some embodiments, the manufacturing process comprises growing a cell culture medium to achieve one or more quality profiles for the cell culture medium. In this case, the plurality of variables of the manufacturing process comprise a plurality of physical, chemical and biological parameters. The PLS regression approach is used to estimate an unknown future value of at least one dependent variable from the plurality of physical, chemical and biological parameters to achieve the one or more quality profiles. The physical parameters can include at least one of temperature, gas flow rate or agitation speed. The chemical parameters can include at least one of dissolved oxygen concentration, carbon dioxide concentration, pH concentration, osmolality, redox potential, metabolite level, amino acid concentration or waste by-products production. The biological parameters can include at least one of viable cell concentration, intra-cellular measurements or extra-cellular measurements. The one or more quality profiles can comprise a carbon dioxide profile, impurity profile, osmolality profile, viable cell concentration profile, and pH profile.
McCready-146 teaches measuring exemplary trajectories of measured and predicted values of process variables in a yeast fermentation culture like ethanol concentration, NH3 concentration, and sugar concentration. See ¶¶ 0079-0082 and Figs. 12 and 13.
McCready-146 teaches that variables that can be measured and manipulated include temperature, chemical concentrations, pH, and gas pressure. See ¶¶ 0046-0047.
McCready-146 teaches the dependent variables can be sampled and measured by the physical facility (offline), the data acquisition module or monitoring module (online/in situ) or a combination thereof. See ¶¶ 0059-0060 and 0080, Figs. 1, 2,7a and 7b.
McCready-146 teaches imputation by regression (IBR) method for predicting prospective behavior of a manufacturing process. See Fig. 4.
McCready-146 teaches the IBR method 250 includes two parts: (1) model calibration; and (2) prediction. First, measured values of one or more variables of the manufacturing process are collected (step 252). The measured values of the process variables can include two types: (1) measured values of the process variables associated with one or more historical batch runs that have been completed, where the historical data is used to train the PLS model; and (2) measured values of the process variables associated with a current batch run that are measured up to a current maturity. The IBR method 250 is used to predict future values of the process variables in the current batch run subsequent to the current maturity. See ¶¶ 0054 and Fig. 4.
McCready-146 teaches the IBR method 250 can be used to achieve high expression of product in a cell culture process with acceptable product quality profiles. Exemplary product quality profiles can include desired carbon dioxide level, impurity level, osmolality level, viable cell concentration, cell culture metabolites concentration, and/or pH level in the product. See ¶¶ 0079.
McCready-146 teaches using the process in biopharmaceutical fermentation and cell culture processes like monoclonal antibody production. See ¶¶ 0079.
McCready-146 also teaches determining chromatographic profiles. See ¶ 0047.
McCready-146 teaches the IBR method 250 is computationally efficient, which is an important quality in real-time or near real-time optimization (e.g., advanced process control) applications. See ¶ 00062.
McCready-146 teaches optimization of operating parameters through the use of the IBR method 250 can be used to achieve high expression of product in a cell culture process with acceptable product quality profiles. See ¶¶ 0079.
Although McCready-146 teaches that the prediction system includes one or more sensors for measuring values of a plurality of variables of the manufacturing process, McCready-146 does not specifically provide a working example with two or more independent online sensors. It would have been prima facie obvious at the time the invention was filed given that the level of skill in the art was high to combine the teachings of McCready-146 and use two or more online sensors to measure the oxygen concentration/pressure, carbon dioxide concentration/pressure, pH concentration, gas pressure, redox potential, metabolite level, amino acid concentration and/or waste by-products production as taught by McCready-146 to determine a carbon dioxide profile (concentration/pressure), impurity profile (purity), osmolality profile, viable cell concentration profile (potency), pH (concentration) and the concentration of products like biopharmaceuticals and monoclonal antibodies profile with the multivariate statistical and training methods as taught by McCready-146. One would have been motivated to monitor these various parameters with two or more online sensors to obtain the most complete monitoring of the manufacturing process.
6. Claim(s) 1-8 and 10- 15 are rejected under 35 U.S.C. 103 as being unpatentable over US 2014/0136146 (McCready, CP May, 15, 2014), “McCready-146” as applied to claims 1, 2, 4-7, 10-13, and 15 above, and further in view of US Pat No. 6,344,172 B1 (Afeyan et al. Feb. 5, 2002), “Afeyan”.
McCready-146 teaches as set forth above.
McCready-146 teaches as set forth above, but does not teach using a fluorescence censor or a specific type of chromatography unit.
Afeyan teaches a chromatography system and methods for the rapid and efficient separation of proteins and other biological macromolecules, like nucleic acids and therapeutic substances, and their purification. See abstract, paragraph bridging cols. 2-3, col. 12-lines 21-30, paragraph bridging cols. 22-23, and Fig. 1-6.
Afeyan teaches sensors for detecting pH, conductivity and UV or other spectral absorbance or fluorescence. See col. 8-lines 35-55 and Fig. 3.
Afeyan teaches that the columns include ion exchange, reverse phase, hydrophobic, and affinity chromatography columns. See col. 4-lines 39-42, col. 6- lines 50-56. col. 15-lines 37-53, and col. 19-lines 9-11.
Afeyan teaches that the advantages of the chromatography system and methods include rapid monitoring of the presence, quantity, and/or purity of a target solute in a product sample, during a preparative procedure. See col. 5-lines 40-50 and col. 7-lines 1-23.
It would have been prima facie obvious at the time the invention was filed given that the level of skill in the art was high to combine the teachings of McCready-146 and Afeyan and use the chromatography system and methods of Afeyan in combination with the processes of McCready because McCready-146 teaches using chromatographic separation methods and Afeyan teaches the that chromatography system and methods can be used for the rapid and efficient separation of proteins and other biological macromolecules. Given the advantages of the chromatography system and methods of Afeyan one would have been motivated to use the chromatography system and methods of Afeyan for the separation and purification proteins and other biological macromolecules, like nucleic acids, proteins and antibodies, in the processes of McCready-146.
7. Claim(s) 1, 2, and 4-15 are rejected under 35 U.S.C. 103 as being unpatentable over US 2014/0136146 (McCready, CP May, 15, 2014), “McCready-146” as applied to claims 1, 2, 4-7, 10-13, and 15 above, and further in view of US 2009/0312851 A1 (Mishra S, Dec. 17, 2009), “Mishra”.
McCready-146 teaches as set forth above, but does not teach using a filtration unit, a specific type of chromatography unit or a specific biological product.
Mishra teaches a multivariate system and method for controlling a bioprocess equipment includes developing a process model. The process model can be applied for process control purposes. See abstract, ¶¶ [0004]-[0011], and Figures 1-3.
Mishra teaches producing protein, therapeutic proteins, peptides, and nucleic acids. See ¶ [0042].
Mishra teaches using chromatography, like ion exchange, affinity, and reverse phase, for purification. See ¶ [0038].
Mishra teaches filtration process, like microfiltration, ultrafiltration, or a reverse osmosis process, any of which can be in a batch or continuous (feed-and-bleed)) format. Other filtrations include diafiltration and dead-end filtration. See ¶ [0037].
It would have been prima facie obvious at the time the invention was filed given that the level of skill in the art was high to combine the teachings of McCready-146 and Mishra and use the chromatography and filtration methods of Mishra in combination with the processes of McCready for the isolation and purification of biological products because McCready-146 teaches using chromatographic separation methods, filtration can initially be used to remove impurities and precipitates, and Mishra teaches using filtration process and chromatography in combination with a multivariate system and method for controlling a bioprocess equipment. Given that chromatography and filtration methods are routinely used in the art for biological molecule purification as shown by the teachings of Mishra, one of skill in the art would have been motivated with a reasonable expectation of success to chromatography and filtration methods in combination with the processes of McCready-146 for isolation and purification of biological products and biological therapeutics.
Conclusion
8. No claims allowed.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PETER J REDDIG whose telephone number is (571)272-9031. The examiner can normally be reached M-F 8:30-5:30 Eastern Time.
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/PETER J REDDIG/Primary Examiner, Art Unit 1646
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