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 .
Priority
Acknowledgment is made of applicant's prior application 63405350 filed September 9th 2022.
Acknowledgment is made of applicant's provisional application PCT/US23/73792 filed September 8th 2023.
The effective filing date is September 9th 2022.
Status of Claims
Claims 1, 2, 4-6, 9-12, 14-17, and 19-21 are currently pending and examined on the merits.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 2, 4-6, 9-12, 14-17, and 19-21 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 11 and 16 state: “…at least three manufacturing process parameters selected from a set of manufacturing process parameters measured from a cell culture in a bioreactor during the biomolecules manufacturing process, wherein each manufacturing process parameter of the set of manufacturing process parameters is listed in Table 1 in order of effect on the glycan distribution…” The table is not clearly defined by the claim, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention (that being the set of manufacturing process parameters). One of ordinary skill in the art would not understand which manufacturing process parameters are referred to. For the purposes of speedy examination, the Examiner interprets the claim as nonlimiting, meaning “at least three manufacturing process parameters” generally must be selected.
Claim 14 states: “The system of any of claim 1,wherein the glycan distribution indicates relative proportions of the one or more glycans attached to the molecules, the operations further comprising: adjusting at least one of the set of manufacturing process parameters to change the relative proportions of the one or more glycans.” No operations are mentioned in claim 1; therefore, “operations” are not clearly defined by the claim, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For the purposes of speedy examination, the Examiner interprets the claim as operations identifying and mathematically manipulating proportions of glycans attached to molecules.
Claims 2, 4-6, 9-10, 12, 14-15, 17, and 19-21 are dependent claims that inherit the rejection.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 2, 4-6, 9-12, 14-17, and 19-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental steps, mathematic concepts, organizing human activity, or a natural law without significantly more.
Step 2A, Prong 1
In accordance with MPEP § 2106, claims found to recite statutory subject matter (claims 18-36 are drawn to a method) (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea (reasonings in [brackets]):
1.
generating, via the processor, an indicator of glycan distribution by providing the at least three parameters as input to a probabilistic graphical model that has been trained to predict the glycan distribution using training data comprising, for each of a plurality of cell cultures in a biomolecules manufacturing process, values of the manufacturing process parameters and corresponding measured values of the indicator of glycan distribution [which is a mathematical concept of a mathematical calculation].
2. The method of claim 1, wherein the probabilistic graphical model is a Bayesian network model and/or is a Markov random field model. [mathematical calculation]
4. (Currently Amended) The method of claim 1,wherein the glycan distribution indicates relative proportions of the one or more glycans attached to the molecules, the method further comprising: adjusting at least one of the set of manufacturing process parameters to change the relative proportions of the one or more glycans [mathematical calculation]
7. The method of claim 6, wherein the at least one of the set of manufacturing process parameters is the total volume of the cell culture or the osmolality… [mathematical calculation]
9. The method of claim 6, wherein the one of the set of manufacturing process parameters is the amount of carbon dioxide sparged into the cell culture, or the amount of oxygen sparged into the cell culture…[mathematical calculation]
11.
… parameters selected from a set of manufacturing process parameters [which is a mental step, i.e. can be performed with pen and paper]
analyzing the at least three parameters using a trained probabilistic graphical model to predict the glycan distribution; [which is a mental step, i.e. can be performed with pen and paper]
and generating the glycan distribution based on the analyzing. [mental step]
12. The system of claim 11, wherein the probabilistic graphical model is a Bayesian network model and/or is a Markov random field model [mathematical calculation].
14. adjusting at least one of the set of manufacturing process parameters to change the relative proportions of the one or more glycans. [mental step].
16.
…process parameters selected…[mental step]
…from a set of manufacturing process parameters measured from a cell culture in a bioreactor…[mathematical calculation]
analyzing the at least three parameters using a trained probabilistic graphical model to predict the glycan distribution; [mental step]
and generating the glycan distribution based on the analyzing. [mental step]
17.
the probabilistic graphical model is a Bayesian network model and/or wherein the probabilistic graphical model is a Markov random field model. [mathematical process]
19.
adjusting at least one of the set of manufacturing process parameters to change the relative proportions of the one or more glycans. [mathematical calculation]
21.
generating an indicator of glycan distribution, via the processor, by providing the at least three parameters as input to a probabilistic graphical model that has been trained to predict the glycan distribution using training data comprising, for each of a plurality of cell cultures in a biomolecule manufacturing process, values of the at least three manufacturing process parameters and corresponding measured values of the indicator of glycan distribution. [mathematical calculation].
The claims also recite limitations which amount to data which further limit the claims from which they originate:
5. (Currently Amended) The method of claim 1,wherein the glycans include one or more of Man5, GOF-N, GO-N, GO, G1, GOF, GlF, or G2F.
10. The method of claim 1, wherein the molecules include a monoclonal antibody.
15. (Currently Amended) The system of claim 11,wherein the glycans include one or more of Mans, GOF-N, GO-N, GO, G1, GOF, GlF, or G2F.
20. The non-transitory CRM of claim 16,wherein the glycans include one or more of Man5, GOF-N, GO-N, GO, G1, GOF, GiF, or G2F.
The claims recite an abstract idea of analyzing biochemical molecules (See MPEP 2106.07(a)).
These recitations are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or mathematical relationships. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas.
There are no additional limitations that indicate that these claims require anything other than carrying out the recited mental process or mathematical concept in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then if falls within the “Mental processes” grouping of abstract ideas. As such, claim(s) 1, 2, 4-6, 9-12, 14-17, and 19-21 recite(s) an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 1: YES).
Step 2A, Prong 2
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to affect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment. Specifically, the claims recite the following additional elements:
1. receiving, at a processor… a bioreactor …
6… a sensor operationally connected to the bioreactor … a controller operationally connected to the bioreactor.
7. … a scale configured to weigh the cell culture or an osmometer, respectively, disposed within the bioreactor.
9. …. the controller is an air flow controller configured to control flow of the carbon dioxide sparged into the cell culture or the oxygen sparged into the cell culture, respectively.
11. … a processor…
16. … a processor…
There are no limitations that indicate that the claimed analysis engine or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. As such, claims 18-36 is/are directed to an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 2: NO).
Step 2B
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment. The instant claims recite the following additional elements:
1. receiving, at a processor… a bioreactor …
6… a sensor operationally connected to the bioreactor … a controller operationally connected to the bioreactor.
7. … a scale configured to weigh the cell culture or an osmometer, respectively, disposed within the bioreactor.
9. …. the controller is an air flow controller configured to control flow of the carbon dioxide sparged into the cell culture or the oxygen sparged into the cell culture, respectively.
11. … a processor…
16. … a processor…
Regarding claims 1, 2, 4-6, 9-12, 14-17, and 19-21, The steps of obtaining data and performing sample collection do not integrate the abstract idea into a practical application and constitutes an insignificant extra-solution activity (i.e., data gathering and presentation), which does not impose a meaningful limit on the abstract idea. As discussed above, there are no additional limitations to indicate that the claimed analysis engine requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims.
Furthermore, the additional elements recited in the claims amount to well-understood, routine and conventional activity, as evidenced by Sebastian Juan Reyes et al. (Processes 2022, 10(2), 189), who discloses Modern Sensor Tools and Techniques for Monitoring, Controlling, and Improving Cell Culture Processes.
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: NO). As such, claims 1, 2, 4-6, 9-12, 14-17, and 19-21 is/are not patent eligible.
Claim Rejections - 35 USC § 102
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 –
(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.
(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.
Claim(s) 1, 2, 5, 10-12, 15-17, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Liang Zhang et al. (Biotechnology Bioengineering, 118, 3447–3459).
Regarding claims 1,11, and 16, the Examiner interprets the claim regarding parameters as nonlimiting, meaning “at least three manufacturing process parameters” generally must be selected.
Regarding claims 1,11, and 16, Zhang et al. teaches a probabilistic model by bayesian network (BN) for the prediction of antibody glycosylation in perfusion and fed-batch cell cultures (Title). Zhang et al. further teaches a BN approach for glycosylation prediction of monoclonal antibodies (mAb) (pg. 3448, Methods, pg. 3449 sec. 2.3-2.4; pg. 3459, Data Availability; re: clm. 1, 11, 16, … A computer-implemented method [11, system…] [16, A non-transitory computer-readable medium (CRM) having stored thereon computer-readable instructions executable to cause performance of operations…] for predicting a glycan distribution of one or more glycans attached to molecules during a biomolecules manufacturing process…)
Zhang et al. further teaches on pg. 3452 Perfusion cultures with different cell densities and perfusion rates including nine culture parameters used to study cell densities and perfusion rates. Zhang et al. states: “Nine culture parameters, including the VCD, perfusion rate (D), CSPR, concentrations of glucose (Cglc), lactate (Clac), ammonium (Camm), and IgG (CIgG), cell growth rate (μ) and specific IgG productivity (qIgG) were measured or calculated. All these parameters were potential inputs of the present BN model.” (sec. 4.2, re: clm. 1, 11, 16 …receiving, at a processor, at least three manufacturing process parameters selected from a set of manufacturing process parameters measured from a cell culture in a bioreactor during the biomolecules manufacturing process, wherein each manufacturing process parameter of the set of manufacturing process parameters is listed in Table 1 in order of effect on the glycan distribution…)
In continued regard to claims 1, 11, and 16, the applicant defines “effect” in paragraph 0142 of the specification as “…the order of effect of the manufacturing process parameters on the glycan distribution that is predicted by the probabilistic graphical model can be established by ordering or ranking the Pearson correlation coefficients of each manufacturing process parameters with the glycan distribution.” Zhang et al. states on pg. 3454, Fig. 3, the impact of the culture parameters on the glycosylation evaluated by Pearson coefficient linear correlations, and states an interpretation of said parameters in sec. 4.2.1, commenting on which parameters “…had the largest impact on the glycosylation with both methods (pg. 3452, re: clm. 1, …wherein each manufacturing process parameter of the set of manufacturing process parameters is listed in Table 1 in order of effect on the glycan distribution…)
Zhang et al. further teaches use of a Baysesian network to produce a glycosylation model as stated on pg. 3451. Zhang et al. continues: “The unknown parameters w and b in the model can be estimated by minimizing the difference between the joint probability of the secreted glycans and their experimental values as follows…” Zhang et al. further teaches training the model on pg. 3456, stating: The BN modelling approach was first applied to all the data of the glycosylation profiles obtained in the fed batch cultures. The simulation gave an accurate fitting for both cultures (Figure 5g–h), and captured well the variations with time including the reverse trend observed at Day 8 and 10 in Glc culture. To finally validate the modelling approach by cross-validation, the data of the duplicates were considered in two separate data sets, 1 and 2. The data set of duplicate 2 was used to train the model, which was then tested using duplicate 1 set; and duplicate 2 set was used as testing set of the model trained with duplicate 1 set. The experimental data of glycosylation and the corresponding data predicted by the model were then compared (see Figure 6). “ (re: clm.1, …generating, via the processor, an indicator of glycan distribution by providing the at least three parameters as input to a probabilistic graphical model that has been trained to predict the glycan distribution using training data comprising, for each of a plurality of cell cultures in a biomolecules manufacturing process, values of the manufacturing process parameters and corresponding measured values of the indicator of glycan distribution.). Zhang et al. teaches the limitations of claims 1, 11 and 16.
Regarding claims 2, 12, and 17 , Zhang et al. teaches a Bayesian network model (Title, re: clm. 2 12, 17, …wherein the probabilistic graphical model is a Bayesian network model…).
Regarding claims 5, 15, and 20, Zhang et al. includes G0-N in their model as stated on pg. 3449 (re: clm. 5, …The method of claim 1,[11][16] wherein the glycans include one or more of Man5, GOF-N, GO-N, GO, G1, GOF, GlF, or G2F.)
Regarding claim 10, Zhang et al. teaches on pg. 3449, sec 2.1: “A CHO‐K1 cell line with glutamine synthetase‐based (GS) expression (Cytiva) producing a recombinant mAb (IgG1) was used in this experiment.” (re: clm. 10, … wherein the molecules include a monoclonal antibody.)
Therefore, Zhang et al. teaches the limitations of claims 1, 2, 5, 10-12, 15-17, and 20.
Claim Rejections - 35 USC § 103
Claim(s) 4, 6, 7, 9, 19 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. as applied to claims 1, 2, 5, 10-12, 15-17, and 20 above in view of Brandon Downey et al. (US20200354666A1).
Zhang et al. is applied to claims 1, 2, 5, 10-12, 15-17, and 20 above.
Regarding claims 4 and 19, Zhang et al. teaches a proportion of glycan (denoted as cell specific perfusion rate) as stated on pg. 3454, Table 2 (re: clm. 4, 19,… wherein the glycan distribution indicates relative proportions of the one or more glycans attached to the molecules, the operations further comprising: adjusting at least one of the set of manufacturing process parameters to change the relative proportions of the one or more glycans.). Zhang et al. also invites modulation of inputs to the BN stating on pg. 3458 “The very good predictive capacity demonstrated in the cross validation test could be used to support medium development and process optimization. The BN model could be used to virtually explore the design space.”
Zhang et al. does not teach adjusting glycan proportions explicitly (re: clm. 4, 19, … adjusting at least one of the set of manufacturing process parameters to change the relative proportions of the one or more glycans.
Downey et al. teaches a process for propagating a cell culture comprising selectively changing at least one condition within the cell culture based upon the calculated future concentration of the quality attribute in the cell culture (clm. 1).
In KSR Int 'l v. Teleflex, the Supreme Court, in rejecting the rigid application of the teaching, suggestion, and motivation test by the Federal Circuit, indicated that “The principles underlying [earlier] cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.” KSR Int'l v. Teleflex lnc., 127 S. Ct. 1727, 1740 (2007).
Applying the KSR standard to Zhang et al. in view of Downey et al. the examiner concludes that some teaching, suggestion, or motivation in the prior art would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.
One of ordinary skill in the art of chemistry would have been motivated to apply the teaching of selecting changing cell culture conditions as taught by Downey et al. to the monitoring of glycan concentration as disclosed by Zhang et al. as the combination would lead to a stronger glycosylation prediction model. In support of this motivation, as previously disclosed, Zhang et al. states that their BN model could be used to support medium development and process optimization which directly relates to the adjustment of manufacturing processes.
One of skill in the art before the effective filing date of the claimed invention would have had a reasonable expectation of success of combining the aforementioned teachings as because Zhang et al. exists in the same field of invention as Downey et al. In support of this motivation, Downey et al. discloses the state of the art of glycan concentration prediction monitoring on paragraphs 0007-0008. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Regarding claims 6 and 7, Downey et al. teaches a bioreactor with a dissolved oxygen sensor in communication with a controller in paragraph 0046-0047 of the specification (re: clm. 6, … wherein at least one of the set of manufacturing process parameters is measured by a sensor operationally connected to the bioreactor…). Downey et al. further teaches in paragraph 0042 of the specification that the bioreactor maybe placed in association with a load cell for measuring the mass of the culture within the bioreactor. Downey et al. further discloses a controller configured to monitor lactate concentration in a cell culture contained in the bioreactor (Spec, para. 0021), that “the controller may control and/or monitor the oxygen tension, the temperature, the agitation conditions, the pressure, foam levels, and the like.”, and a disclosure of titrant feed and osmolality in figures 15 and 16 as derived from culture (Spec. para. 0099, re: clm. 7, … wherein the at least one of the set of manufacturing process parameters is the total volume of the cell culture or the osmolality, and the sensor is a scale configured to weigh the cell culture or an osmometer, respectively, disposed within the bioreactor.)
Applying the KSR standard of obviousness to Zhang et al and Downey et al. the Examiner concluded that the combination of the glycosylation prediction model of Zhang et al. and with the sensors and monitoring apparatuses of Downey et al. represents an illustration of the reasoning that it would have been “obvious to try" choosing from a finite number of identified, predictable solutions to achieve the claimed process. One of ordinary skill in the art of chemistry would have found it obvious to monitor the osmolality, volume and or mass of a culture using the teachings of Downey et al. as applied to the prediction model of Zhang et al. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Regarding claim 9, Downey et al. discloses gas ports, a sparger and a sensor as they relate to oxygen and carbon dioxide on paragraph 0040 (re: clm. 9, … wherein the one of the set of manufacturing process parameters is the amount of carbon dioxide sparged into the cell culture, or the amount of oxygen sparged into the cell culture…). Downey et al. further teaches explicitly the bioreactor can be used to control inflow of oxygen or carbon dioxide in paragraph 0106 of the specification (re: clm. 9, … and the controller is an air flow controller configured to control flow of the carbon dioxide sparged into the cell culture or the oxygen sparged into the cell culture, respectively…). Therefore Zhang et al. in view of Downey et al. teach the limitations of claim 9.
Regarding claim 21, Zhang et al. teaches lactate concentration within a cell culture on pg. 3456 (“the culture was divided into pseudo steady states, as one state per day, and the average values of the culture parameters over 1 day were used for each state. Here, the pH, concentrations of glucose, galactose, lactate, NH4, cell growth rate, cell density, cell specific consumptions rates of glucose and galactose, and the cell specific productivities of IgG and lactate were used as inputs for modelling.”) Zhang et al. further teaches VCD as input to their model as disclosed on pg. 3452 and Table 2.
Zhang et al. in view of Dowson et al. teaches the amount of oxygen sparged into a cell culture per VCD per time (re: clm. 21, … receiving, at a processor, at least three manufacturing process parameters selected from a set of manufacturing process parameters measured from a cell culture in a bioreactor during the biomolecules manufacturing process, wherein the at least three manufacturing process parameters are selected from the group consisting of lactate concentration per cell culture volume per time; osmolality per time; base total per VCD per time; cell viability per time; sodium concentration per cell culture volume per time; amount of oxygen sparged into the cell culture per VCD per time; amount of carbon dioxide sparged into the cell culture per VCD per time; PCV per time; and qIgG; generating an indicator of glycan distribution, via the processor, by providing the at least three parameters as input to a probabilistic graphical model that has been trained to predict the glycan distribution using training data comprising, for each of a plurality of cell cultures in a biomolecule manufacturing process, values of the at least three manufacturing process parameters and corresponding measured values of the indicator of glycan distribution.). Therefore, Zhang et al. in view of Dowson et al. teaches the limitations of claim 21.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN T STUBBS whose telephone number is (571)272-0340. The examiner can normally be reached M-F 8-5 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Larry Riggs can be reached at 571-270-3062. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.T.S./Examiner, Art Unit 1686
/LARRY D RIGGS II/ Supervisory Patent Examiner, Art Unit 1686
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