DETAILED ACTION
Applicant’s response, filed Dec 12 2025, has been fully considered. Rejections and/or objections not reiterated from previous Office Actions are hereby withdrawn. 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 .
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 1-2, 7-8, 10-11, 13, 15-16, 19, 21, 25, 27, 30, 32-34, 36-37, 42-43, 45, 51, 56, 65, 67, and 69 are pending.
Claims 3-6, 9, 12, 14, 17-18, 20, 22-24, 26, 28-29, 31, 35, 38-41, 44, 46-50, 52-55, 57-64, 66, 68, and 70 are canceled.
Claims 1-2, 7-8, 10-11, 13, 15-16, 19, 21, 25, 27, 30, 32-34, 36-37, 42-43, 45, 51, 56, 65, 67, and 69 are rejected.
Priority
The instant Application claims domestic benefit to US provisional application 62/826,910, filed Mar 29 2019.
Applicant's claim for the benefit of a prior-filed application, PCT/US2020/025444, filed Mar 27 2020, is acknowledged.
Accordingly, each of claims 1-2, 7-8, 10-11, 13, 15-16, 19, 21, 25, 27, 30, 32-34, 36-37, 42-43, 45, 51, 56, 65, 67, and 69 are afforded the effective filing date of Mar 29 2019.
Drawings
The replacement drawing sheets submitted Dec 12 2025 are accepted and the outstanding objections from the previous Office Action are withdrawn.
Information Disclosure Statement
The information disclosure statements (IDS) filed on Nov 3 2025 and Nov 12 2025 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.
Claim Objections
The outstanding objections to the claims are withdrawn in view of the amendments submitted herein.
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, 7-8, 10-11, 13, 15-16, 19, 21, 25, 27, 30, 32-34, 36-37, 42-43, 45, 51, 56, 65, 67, and 69 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more. Any newly cited portions are necessitated by claim amendment.
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 a method and a 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 and 36: computing/compute… new values of the process variables during a simulated time period, at least in part by generating a plurality of constraints on flux rates of metabolic fluxes describing the virtual cellular biomass by modeling one or more effects of at least some of the current values of the process variables on metabolic reaction kinetics, computing the flux rates of the metabolic fluxes by performing flux balance analysis subject to a metabolic objective and the generated plurality of the constraints on the flux rates, computing rates of change of at least some of the process variables based at least in part on the computed flux rates, and updating one or more of the current values of the process variables at least in part by integrating one or more of the computed rates of change for a virtual time step within the simulated time period;
computing… a metric of the (computationally; claim 1 only) modeled bioreactor based at least in part on the computed new values of the process variables; and
generating… based on the metric of the modeled bioreactor one or more of i) information displayed to a user via a user interface, ii) a control setting for a real-world bioreactor, or iii) a training set for an artificial intelligence model of a bioreactor.
Dependent claims 2, 7-8, 10-11, 13, 15-16, 19, 21, 25, 27, 32-34, 37, 42-43, 45, 51, 56, 67, and 69 recite further steps that limit the judicial exceptions in independent claims 1 and 36 or add new judicial exceptions and, as such, also recite those abstract ideas. For example, claims 2, 7, 37, and 42 further limit the process variables to include specific types of data; claims 8 and 43 further limit the plurality of constraints to include specific data; claims 10-11, 13, and 45 further limit the effects of at least some of the current values of the process variables being modeled; claim 15 further limits the modeling to include calibrating the modeled effects with experimental data; claims 16, 19, and 51 further limit the metabolic objective; claims 21 and 56 further limit the updating and further includes a step for computing compositions of one or more virtual output streams from at least one portion of the plurality of portions of the modeled bioreactor using the properties of the virtual output filter; claim 25 further limits the metric of the modeled bioreactor; claim 27 further limits the generating to generating the control setting; claims 32 and 67 further limit the modeled bioreactor and the process variables and further includes a step for computing the new values of the first process variables during the simulated time period is based in part on the received plurality of the current values of the second process variables, which is further limited by claim 33; and claims 34 and 69 further add a step for determining one or more velocities associated with the virtual contents of the first portion of the modeled bioreactor.
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind and/or by mathematical operation because the method only requires a user to manually model a bioreactor and generate an output. Without further detail as to the methodology involved in “computing”, “generating”, “updating”, and “determining”, under the BRI, one may simply, for example, use pen and paper to compute new values of process variables during a simulation, generate constraints on the model, compute flux rates subject to the constraints, compute rates of change of the process variables based on the computed flux rates, update the current values of the process variables based on the computed rates of change, compute a metric of the modeled bioreactor, and generate an output to describe the model. The steps directed toward “computing the flux rates of the metabolic fluxes by performing flux balance analysis subject to a metabolic objective”, “computing rates of change”, “updating one or more of the current values of the process variables at least in part by integrating…”, and “computing… a metric of the computationally modeled bioreactor” in claims 1 and 36, and those recited in the dependent claims require mathematical techniques as the only supported embodiments, as is disclosed in the specification at: [0028] regarding calculating flux rates or velocities as changes in concentrations; [0030-0036; 0049-0060; Table 1] regarding a kinetics model based on mathematical formulas; [0038-0041; 0063-0067; Table 4] regarding flux balance analysis and metabolic objectives which maximize or minimize various mathematical relationships; and [0043; 0046; 0069-0078] regarding rate integration.
Therefore, claims 1 and 36 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 claims 1 and 36: receiving/receive a plurality of current values of process variables, the process variables describing virtual contents of a plurality of portions of the modeled bioreactor, and the virtual contents including virtual cellular biomass in a virtual extracellular solution.
Dependent claims 21 and 56: 1) receiving/receive one or more variables indicative of flow rates and compositions of one or more virtual input streams into at least one portion of the plurality of portions of the modeled bioreactor;
2) receiving/receive one or more variables indicative of properties of a virtual output filter;
3) receiving/receive one or more control variables.
Dependent claim 27: controlling an input to a real-world bioreactor based on the generated control setting.
Dependent claims 32 and 67: receiving/receive a plurality of current values of second process variables, the second process variables describing second virtual contents of the second portion of the modeled bioreactor.
Dependent claims 30 and 65 recite steps that further limit the recited additional elements in the claims by limiting receiving the plurality of current values to include certain data.
The claims also include non-abstract computing elements. For example, independent claim 1 includes processing hardware of a computing system and independent claim 36 includes a non-transitory computer-readable medium storing instructions that when executed by one or more processors, cause the one or more processors to perform the method.
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 “receiving”, 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)).
The step of “controlling an input to a real-world bioreactor based on the generated control setting” in claim 27 merely recites the application of the judicial exception to the technical field of bioreactors. The control is only based on the generated control setting, and the claim recites no limits for that basis. The limitation does not integrate the recited judicial exceptions into a practical application because the claim recites only the idea of a solution or outcome, without reciting details of how the solution to the problem is accomplished (see MPEP 2106.05(f)).
Further steps directed to additional non-abstract computing elements of 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 specification as published discloses that the method is directed to in silico modeling of bioreactors and the associated biological processes for improving bioprocess design and/or operation at [0001], but does not provide a clear explanation for how the additional elements provide these improvements. Therefore, the additional elements do not clearly improve the functioning of a computer, or comprise an improvement to any other technical field. Further, the additional elements do not clearly affect a particular treatment; they do not clearly require or set forth a particular machine; they do not clearly effect a transformation of matter; nor do they clearly provide a nonconventional or unconventional step (MPEP2106.04(d)).
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 prior art review to Simutis et al. (Biotechnology Journal, 2015, 10:1115-1130; newly cited) discloses that controlling a bioreactor through feedback and modeling is an “apply it” additional element that is routine, well-understood and conventional in the art. Said portions of the prior art are, for example, the abstract, although the entire document is relevant. Further, 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 and 36 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 (Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)). The specification as published also notes that computer processors and systems, as example, are commercially available or widely used at [0084-0092]. 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).
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.
Response to Applicant Arguments
At p. 14-16, section V, Applicant submits that the specification provides details regarding an improvement which should be considered at Step 2A, Prong 2. Applicant submits that the specification describes techniques improving the computational analysis of the bioreactor by spatially discretizing the modeled bioreactor and that the claims reflect the disclosed improvement. Applicant submits that this improvement is consistent with the “Notice” (Ex Parte Desjardins), which describes that an improvement to computer functionality based upon adjustments to parameters of a machine learning model provided a practical application. Applicant submits that the instant claims similarly spatially discretize a model to provide similar improvements to the modeling performance of a computer.
It is respectfully submitted that this is not persuasive. First, “computational analysis of the bioreactor”, as asserted by Applicant, is considered to include those limitations which recite a judicial exception at Step 2A, Prong 1 (“computing… new values of the process variable”, “computing… a metric of the computationally modeled bioreactor”, and “generating… i) information… ii) a control setting… or “a training set”). Judicial exceptions cannot be a practical application of the judicial exception. The courts have made clear that a judicial exception is not eligible subject matter (Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)) if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself."). For a claim reciting a judicial exception to be eligible, it is the additional elements (if any) in the claim that must "transform the nature of the claim" into a patent-eligible application of the judicial exception, Alice Corp., 573 U.S. at 217, 110 USPQ2d at 1981, either at Prong Two or in Step 2B. If there are no additional elements in the claim, then it cannot be eligible. It is submitted here that the instant claims do not include any additional elements that provide for a practical application. Rather, the “additional element” in the instant claims (see exemplary claim 1) includes only the step of “receiving” data and generic computer elements. As set forth above, said steps operate in the claim as data gathering steps or instructions to apply the judicial exception to a computer, and do not integrate any of the recited judicial exceptions into a practical application, nor do the claims as a whole include any inventive concept beyond well-understood, routine and conventional steps.
Regarding the “Notice”, the instant claims are not analogous to those discussed in the Notice. The instant claims do not recite adjustments of parameters of a machine learning model and are therefore not analyzed in a similar manner as outlined in the Notice. As discussed above, those steps for “discretizing a model” pointed to by Applicant recite the judicial exception, and cannot provide an improvement. Neither does the performance of the model, spatially discretized or not, alter the functioning of the computer. The model does not improve computer functionality, but is merely applied to the computer environment.
Claim Rejections - 35 USC § 102
The outstanding rejections from the previous Office Action are withdrawn in view of the amendments submitted herein. Specifically, the prior art to Famili does not teach modeling a bioreactor to account for spatial inhomogeneity as recited in amended claims 1 and 36, and as submitted by Applicant at p. 13-14, section IV.
Claim Rejections - 35 USC § 103
The outstanding rejections from the previous Office Action are withdrawn in view of the amendments submitted herein. Specifically, the prior art to Famili does not teach modeling a bioreactor to account for spatial inhomogeneity as recited in amended claims 1 and 36, and as submitted by Applicant at p. 13-14, section IV.
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.
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.
Claims 1-2, 7-8, 10-11, 13, 15-16, 19, 21, 25, 27, 30, 32-34, 36-37, 42-43, 45, 51, 56, 65, 67, and 69 are rejected under 35 U.S.C. 103 as being unpatentable over Famili et al. (US 2016/0364,520; cited on the Nov 14 2022 IDS) in view of Lapin et al. (Chemical Engineering Science, 2006, 43:4783-4797; cited on the Sep 29 2021 IDS). The instant rejection is newly stated and is necessitated by claim amendment.
The prior art to Famili discloses models and methods useful for optimizing cell lines (abstract). Famili, indicated by the open circles, teaches the instant features, indicated by the closed circles, as follows. Instantly claimed elements which are considered to be equivalent to the prior art teachings are described in bold for all claims.
Claim 1 discloses a method of computationally modeling a bioreactor to account for spatial inhomogeneity. Claim 36 discloses a non-transitory computer-readable medium storing instructions for computationally modeling a bioreactor to account for spatial inhomogeneity, wherein the instructions, when executed by one or more processors, cause the one or more processors to perform a method. Famili teaches methods and computer readable medium or media comprising commands or instructions for a processor to carry out models and methods useful for optimizing cell lines by modelling improved characteristics of the cell lines [0007; 0167-0168]. See below for teachings by Lapin regarding spatial inhomogeneity.
The method of claims 1 and 36 comprise:
receiving a plurality of current values of process variables, the process variables describing virtual contents of a plurality of portions of the modeled bioreactor, and the virtual contents including virtual cellular biomass in a virtual extracellular solution;
Famili teaches that the models are based on a data structure relating a plurality of reactants to a plurality of reactions wherein each of the reactions includes a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating the substrate and the product (i.e., process variables) [0050]. Famili teaches that the data structure can be stored on a computer readable medium or media and accessed (i.e., received) to provide the data structure for use with a method of the invention [0080]. Famili teaches that the term “reaction” means a conversion that consumes a substrate or forms a product that occurs in or by a cell, where the “reactant” is a chemical that is a substrate or a product of a reaction that occurs in or by a cell, which, in an in silico model or data structure, is a representation of a chemical that is a substrate or a product of a reaction that occurs in or by a cell (i.e., virtual contents of the modeled bioreactor) [0051-0055]. As Famili teaches examining or predicting biomass production (i.e., virtual cellular biomass) [0085; 0120; 0173-0174; 0180] in culture media where a nutrient is provided in the extracellular environment [0047; 0049; 0079; 0082; 0084; 0213-0242], it is considered that the model must include information about virtual cellular biomass in a virtual extracellular solution as instantly claimed.
Famili does not teach a plurality of portions of the modeled bioreactor. See below for teachings by Lapin.
computing, by processing hardware of a computing system, new values of the process variables during a simulated time period, at least in part by generating a plurality of constraints on flux rates of metabolic fluxes describing the virtual cellular biomass by modeling one or more effects of at least some of the current values of the process variables on metabolic reaction kinetics, computing the flux rates of the metabolic fluxes by performing flux balance analysis subject to a metabolic objective and the generated plurality of the constraints on the flux rates, computing rates of change of at least some of the process variables based at least in part on the computed flux rates, and updating one or more of the current values of the process variables at least in part by integrating one or more of the computed rates of change for a virtual time step within the simulated time period;
Famili teaches performing the method on a computer [0080] to produce an in silico model (i.e. simulations) of a cell culture [0083]. Famili teaches that the models are based on a data structure relating a plurality of reactants to a plurality of reactions (i.e. metabolic fluxes), wherein each of the reactions includes a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating the substrate and the product (i.e., process variables) [0050]. Famili teaches that information included in the data structure can include a constraint placed on a reaction, where a constraint is an upper or lower boundary for a reaction [0058]. Famili teaches providing an objective function, wherein the objective function is uptake rate of two or more nutrients (i.e., metabolic objective), and determining at least one flux distribution (i.e., rates of metabolic fluxes) that minimizes or maximizes an objective function when the constraint set is applied to the data structure, wherein the at least one flux distribution is predictive of a physiological function of the cell [0074; 0078; 0126]. Famili teaches performing flux balance analysis to determine flux distributions over a period of time [0125-0126]. Famili teaches that the flux balance analysis links the calculated steady state rates from metabolic flux analysis to dynamic changes in metabolite concentrations (i.e., changes in the process variables) in cell culture during the simulation [0010]. As Famili teaches displaying these changes [0087; 0213-0242], it is considered that Famili fairly teaches updating the process variables as instantly claimed. Famili also teaches that the optimal flux distribution can be calculated from a reaction network data structure and a set of constraints as set forth above for all points in this plane by repeatedly solving the linear programming problem while adjusting (i.e., updating) the exchange fluxes defining the two-dimensional space [0181].
computing, by the processing hardware, a metric of the computationally modeled bioreactor based at least in part on the computed new values of the process variables; and
Famili teaches determining predicted total cell and glucose concentrations for cell culture simulations over a time profile [0009; 0126], which reads on a metric as instantly claimed because claim 25 (see below) further limits the metric of the modeled bioreactor to include values of at least one of the process variables at different virtual times within the simulated time period.
generating, by the processing hardware, and based on the metric of the modeled bioreactor one or more of i) information displayed to a user via a user interface, ii) a control setting for a real-world bioreactor, or iii) a training set for an artificial intelligence model of a bioreactor.
Famili teaches predicting a culture condition for a eukaryotic cell (i.e., a control setting) [0087; 0213-0242] which is then graphically displayed [0126] on a graphical user interface [0167; 0176].
Famili does not teach modeling a bioreactor to account for spatial inhomogeneity or a plurality of portions of the modeled bioreactor.
However, the prior art to Lapin discloses an Euler–Lagrange modeling approach to characterize the behavior of a heterogeneous cell population in a stirred tank bioreactor with non-ideal mixing that accounts for the heterogeneity present in real reactors in both the biotic and abiotic phases (abstract). Lapin teaches that the simulation model comprises a set of intracellular balance equations which are divided based upon discretization of the bioreactor (p. 4786, col. 1 through p. 4790, col. 1, par. 3), which reads on first and second portions of the bioreactor with first and second current and new process variables as instantly claimed.
Regarding claims 1 and 36, 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, in the course of routine experimentation and with a reasonable expectation of success, the method of Famili and Lapin because both references disclose methods for simulation modeling of cells growing in a bioreactor. The motivation to include the Euler-Lagrange approach to characterize the behavior of a heterogeneous cell population in a stirred-tank bioreactor of Lapin would have been to account for the dynamic spatial and temporal variations of the extracellular environment in the bioreactor which the living cells are exposed to, as taught by Lapin (p. 4784, col. 1, par. 1 through col. 2, par. 2).
Regarding claims 2 and 37, Famili in view of Lapin teaches the method of claim 1 and the non-transitory computer-readable medium of claim 36 as described above. Claims 2 and 37 further add that the process variables include at least one of: (i) temperature, (ii) acidity, (iii) one or more variables indicative of total osmolarity of the virtual contents, or (iv) one or more variables indicative of concentration of the virtual cellular biomass and one or more variables indicative of extracellular metabolite concentrations in the virtual extracellular solution, wherein the one or more variables indicative of the extracellular metabolite concentrations in the virtual extracellular solution include one or more variables indicative of concentrations of at least one of: oxygen, carbon dioxide, ammonia, glucose, asparagine, glutamine, glycine, or at least one target metabolic product.
Famili teaches that the models are based on a data structure relating a plurality of reactants to a plurality of reactions wherein each of the reactions includes a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating the substrate and the product (i.e., process variables) [0050]. Famili teaches determining flux through a reaction by accounting for a regulatory event with a modifier, where the modifier can include a change in pH (i.e. acidity), temperature [0158; 0165]. Famili also teaches that osmolarity can affect culture conditions [0257; 0306; 0394]. Famili teaches examining total cell concentrations (i.e. virtual cell biomass) [0009] and metabolite concentrations in cell culture [0010] based on uptake and secretion of the metabolites to determine the concentration of metabolites in the bioreactor media (i.e., virtual extracellular solution) [0126]. Famili teaches examining oxygenation, glucose, glutamine, carbon, nitrogen, sulfur, phosphate, hydrogen, lactate, ammonia, amino acids including asparagine, glutamine, and glycine (i.e. target metabolic products) in the media ([0086; 0180-0181; 0223; 0296; 0366] and Table 1).
Regarding claims 7 and 42, Famili in view of Lapin teaches the method of claims 1-2 and the non-transitory computer-readable medium of claim 36-37 as described above. Claims 7 and 42 further add that the process variables additionally include one or more variables indicative of one or more intracellular metabolite concentrations in the virtual cellular biomass.
Famili teaches examining metabolite concentrations in the cell (i.e., intracellular metabolite concentrations), including glucose [0009].
Regarding claims 8 and 43, Famili in view of Lapin teaches the method of claim 1 and the non-transitory computer-readable medium of claim 36 as described above. Claims 8 and 43 further add that the plurality of the constraints on the flux rates includes an upper limit on at least one of i) glucose uptake, ii) glutamine uptake, iii) asparagine uptake, or iv) oxygen uptake or a lower limit on an energy consumption rate for cellular maintenance.
Famili teaches that a constraint is an upper or lower boundary for a reaction, where a boundary can specify a minimum or maximum flow of mass, electrons or energy through a reaction [0058]. Famili teaches a constraint set for the plurality of reactions examined [0108], including constraining the upper limits of glucose, oxygen, asparagine, and glutamine uptake to experimental levels and constraining the minimum growth rate and biomass production (i.e., an energy consumption rate for cellular maintenance) ([0070; 0215]; Tables 21-23).
Regarding claims 10 and 45, Famili in view of Lapin teaches the method of claim 1 and the non-transitory computer-readable medium of claim 36 as described above. Claims 10 and 45 further add that the one or more effects of at least some of the current values of the process variables on the metabolic reaction kinetics includes 1) an effect of a value of at least one of: i) temperature, ii) acidity, or iii) osmolarity on an upper limit of a metabolite uptake rate; 2) an effect of stress on a lower limit of energy consumption rate for cellular maintenance; or 3) an effect of concentration of at least one of metabolic byproducts.
Famili teaches a constraint set for the plurality of reactions examined [0108], including constraining the upper limits of glucose, oxygen, asparagine, and glutamine uptake to experimental levels ([0070; 0215]; Tables 21-23). Famili teaches determining flux through a reaction by accounting for a regulatory event with a modifier, where the modifier can include a change in pH (i.e. acidity), temperature [0158; 0165]. Famili teaches that a function included in the term can also correlate a boundary value with an environmental condition such as pH or temperature (i.e., 1) i) and ii)) [0059]. Famili teaches models to reduce byproduct formation (i.e., 3)) [0047-0048; 0227-0242; 0272-0274].
Regarding claim 11, Famili in view of Lapin teaches the method of claims 1 and 10 as described above. Claim 11 further adds that modeling the one or more effects of at least some of the current values of the process variables on the metabolic reaction kinetics includes computing the effect of the value of at least one of: i) temperature, ii) acidity, or iii) osmolarity on the upper limit of the metabolite uptake rate by multiplying the upper limit with a correction factor indicative of a reduction in the uptake rate due to non-ideal conditions.
Famili teaches that a function included in the term can also correlate a boundary value with an environmental condition such as pH or temperature [0059] by modifying a change in the presence, absence, or amount of an enzyme that performs a reaction [0158]. Famili teaches that models are used to simulate the phenotypic behavior of an organism under changing genetic circumstances and environmental conditions [0129]. Famili teaches that the regulatory structure includes a general control stating that a reaction is inhibited by a particular environmental condition like pH or temperature [0164-0165]. Famili teaches that a reaction constraint placed on a reaction can be incorporated into the model by multiplying the maximum flux value of a reaction (aj) by a term representing the regulatory reaction [0161; 0188].
Regarding claim 13, Famili in view of Lapin teaches the method of claims 1 and 10 as described above. Claim 13 further adds that modeling the effect of stress includes computing the effect based at least in part on a cumulative effect of a temperature shift on the virtual cellular biomass. Claim 13 is interpreted to further limit option 2) of claim 10. As only one option of claim 10 is required, and Famili teaches at least options 1) and 3) as described above, option 2) and, therefore, the limitations of claim 13 are not required.
Regarding claim 15, Famili in view of Lapin teaches the method of claim 1 as described above. Claim 15 further adds that modeling the one or more effects includes calibrating the modeled effects with experimental data from a real-world cell culture.
Famili teaches performing experiments to verify the models [0020; 0028; 0044-0048] and constraining or choosing the reactions based on experimental data [0063-0064; 0070; 0116; 0128; 0145; 0151; 0173-0174], both of which read on “calibrating” as instantly claimed. Famili also teaches estimating nutrient uptake and byproduct secretion rates will be estimated using bioreactor data, and importing bioreactor data to reconcile the elemental balance of the input and output metabolites, to estimate experimental error [0398].
Regarding claims 16 and 51, Famili in view of Lapin teaches the method of claim 1 and the non-transitory computer-readable medium of claim 36 as described above. Claims 16 and 51 further add that the metabolic objective includes minimizing a ratio of linear combinations of the at least some of the flux rates and squares of flux rates in the flux balance analysis or minimizing a linear combination of at least some of the flux rates in the flux balance analysis.
Famili teaches that the data structure can comprise a set of linear algebraic equations [0090; 0130]. Famili teaches that a time profile of metabolite concentrations is calculated by the transient flux balance analysis in an iterative two-step process, where uptake and secretion rate of metabolites are determined using a metabolic network and linear optimization [0126; 0153; 0172]. Famili teaches that an optimal solution within the set of all solutions can be determined using mathematical optimization methods when provided with a stated objective and a constraint set [0172], by minimizing the linear combination of metabolic fluxes (i.e., minimizing a linear combination of at least some of the flux rates in the flux balance analysis) [0175].
Regarding claim 19, Famili in view of Lapin teaches the method of claim 1 as described above. Claim 19 further adds that the metabolic objective includes maximizing energy consumption rate for cellular maintenance or maximizing a rate of growth of the virtual cellular biomass.
Famili teaches examining objective functions to maximize growth and nutrient uptake (i.e., energy consumption) [0070; 0087; 0093; 0174].
Regarding claims 21 and 56, Famili in view of Lapin teaches the method of claim 1 and the non-transitory computer-readable medium of claim 36 as described above. Claims 16 and 51 further add: 1) receiving one or more variables indicative of flow rates and compositions of one or more virtual input streams into at least one portion of the plurality of portions of the modeled bioreactor, and wherein updating the at least some of the current values of the process variables includes accounting for the flow rates and the compositions of the one or more virtual input streams; 2) receiving one or more variables indicative of properties of a virtual output filter, and computing compositions of one or more virtual output streams from at least one portion of the plurality of portions of the modeled bioreactor using the properties of the virtual output filter, and wherein updating the at least some of the current values of the process variables includes accounting for the compositions of the one or more virtual output streams; or 3) receiving one or more control variables and updating an affected set of the current values of the process variables at least in part based on the received control variables.
Famili teaches adjusting reaction variables based on temperature and pH information [0161; 0164-0165; 0188], which reads on option 3) and a control variable based on the instant specification as published, which discloses that control variables may include temperature settings, acidity settings or any other suitable variables that may represent virtual control settings of the bioreactor [0037].
Regarding claim 25, Famili in view of Lapin teaches the method of claim 1 as described above. Claim 25 further adds that the metric of the modeled bioreactor includes values of at least one of the process variables at different virtual times within the simulated time period.
Famili teaches determining predicted total cell and glucose concentrations for cell culture simulations over a time profile [0009; 0126].
Regarding claim 27, Famili in view of Lapin teaches the method of claim 1 as described above. Claim 27 further adds generating the control setting, and wherein the method further comprises controlling an input to a real-world bioreactor based on the generated control setting.
Famili teaches an integrated computational and experimental platform allowing for the development of metabolic models of mammalian cells, media and process optimization and development, understanding metabolism under different genetic and environmental conditions, engineering cell lines, and developing novel selection systems in a bioreactor [0043-0048; 0073], which reads on developing and applying control settings as instantly claimed.
Regarding claim 30, Famili in view of Lapin teaches the method of claim 1 as described above. Claim 30 further adds that receiving the plurality of the current values includes at least one of i) receiving values from a user via a graphical user interface; ii) receiving values based on measurements of a real bioreactor; iii) loading values from computer memory and based on previously computed values; or iv) loading predetermined default values from computer storage.
Regarding claims 32 and 67, Famili in view of Lapin teaches the method of claim 1 and the non-transitory computer-readable medium of claim 36 as described above. Claims 37 and 67 further add that the plurality of portions of the modeled bioreactor include a first portion of the modeled bioreactor and a second portion of the modeled bioreactor; the process variables include first process variables describing first virtual contents of the first portion of the modeled bioreactor; the method further includes receiving a plurality of current values of second process variables, the second process variables describing second virtual contents of a second portion of the modeled bioreactor; and computing the new values of the first process variables during the simulated time period is based in part on the received plurality of the current values of the second process variables.
Famili teaches that at least one reactant in the plurality of reactants or at least one reaction in the plurality of reactions (i.e., virtual contents of the bioreactor) can be annotated with an assignment to a subsystem or compartment, a first substrate or product in the plurality of reactions can be assigned to a first compartment and a second substrate or product in the plurality of reactions can be assigned to a second compartment, and at least a first substrate or product, or more substrates or products, in the plurality of reactions can be assigned to a first compartment and at least a second substrate or product, or more substrates or products, in the plurality of reactions can be assigned to a second compartment [0090]. Famili does not teach a first portion of the modeled bioreactor and a second portion of the modeled bioreactor as instantly claimed.
However, the prior art to Lapin discloses an Euler–Lagrange modeling approach to characterize the behavior of a heterogeneous cell population in a stirred tank bioreactor with non-ideal mixing that accounts for the heterogeneity present in real reactors in both the biotic and abiotic phases (abstract). Lapin teaches that the simulation model comprises a set of intracellular balance equations which are divided based upon discretization of the bioreactor (p. 4786, col. 1 through p. 4790, col. 1, par. 3), which reads on first and second portions of the bioreactor with first and second current and new process variables as instantly claimed.
Regarding claim 33, Famili in view of Lapin teaches the method of claims 1 and 32 as described above. Claim 33 further adds computing the new values of the first process variables during the simulated time period includes computing a gradient of at least one of the first process variables based on a value of a corresponding one of the second process variables, which Famili does not teach.
However, Lapin teaches determining concentration and velocity gradients in bioreactors (p. 4787, col. 1, par. 5 and col. 2, par. 3; p. 4788, col. 2, par. 2; p. 4792, col. 2, par. 3-4).
Regarding claims 34 and 69, Famili in view of Lapin teaches the method of claims 1 and 32 and the non-transitory computer-readable medium of claim 36 as described above. Claims 34 and 69 further add determining one or more velocities associated with the virtual contents of the first portion of the modeled bioreactor, which Famili does not teach.
However, Lapin teaches representing the flow throughout the bioreactor by a velocity field composed of velocity vectors (p. 4785, col. 1, par. 3 through col. 2, par. 1; p. 4787, col. 1, par. 3 through p. 4790, col. 1, par. 3).
Regarding claim 65, Famili in view of Lapin teaches the non-transitory computer-readable medium of claim 36 as described above. Claim 65 further adds that receiving the plurality of the current values includes at least one of: i) receiving values from a user via a graphical user interface; ii) receiving values based on measurements of a real bioreactor; iii) loading values from computer memory and based on previously computed values; or iv) loading predetermined default values from computer storage.
Famili teaches a graphic user interface of the invention can also be capable of sending at least one command for modifying the data structure, the constraint set or the commands for applying the constraint set to the data representation, or a combination thereof (i.e., i)) [0176]. Famili teaches performing experiments to verify the models [0020; 0028; 0044-0048] and constraining or choosing the reactions based on experimental data (i.e., ii)) [0063-0064; 0070; 0116; 0128; 0145; 0151; 0173-0174; 0398]. Famili teaches that reactants to be used in a reaction network data structure of the invention can be obtained from or stored in a compound database (i.e., iii) and iv)) (see at least [0110].
Response to Applicant Arguments
At p. 13-14, Applicant submits that the teachings of Lapin apply to the cell population rather than discretization of the bioreactor, pointing particularly to p. 4785, col. 1, par. 3.
It is respectfully submitted that this is not persuasive. At p. 4785, col. 1, par. 3, Lapin clearly states that “CFD simulations of stirred tanks in bioreaction engineering…”, indicating that segregated description of the cell population corresponds with the continuum representations of the fluid phases, resulting in a model of spatial inhomogeneity as instantly claimed. It is noted that at other locations of Lapin, there are clear teaching of spatial discretization (see at least p. 4786, col. 1, par. 4 through col. 2, par. 1), as is indicated in the above rejection.
Conclusion
No claims are allowed.
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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/J.N.S./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685