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 .
Reopening of Prosecution After Appeal Brief
In view of the Appeal Brief filed on 09/08/2025, PROSECUTION IS HEREBY REOPENED. Grounds for rejection are set forth below.
To avoid abandonment, Appellant must exercise one of the following two options:
(1) file a reply under 37 CFR 1.111 (if this Office action is non-final); or,
(2) initiate a new appeal by filing a notice of appeal under 37 CFR 41.31 followed by an appeal brief under 37 CFR 41.37. The previously paid notice of appeal fee and appeal brief fee can be applied to the new appeal. If, however, the appeal fees set forth in 37 CFR 41.20 have been increased since they were paid previously, then Appellant must pay the difference.
A Supervisory Patent Examiner (SPE) has approved reopening by signing here:
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
Office Action Overview
Claim Status
Canceled:
2 and 16
Pending:
1 and 3-15
Withdrawn:
none
Examined:
1 and 3-15
Independent:
1 and 15
Amended:
1 and 15
New:
none
Allowable:
none
Objected to:
1
Rejections applied
Abbreviations
x
112/b Indefiniteness
PHOSITA
"a Person Having Ordinary Skill In The Art before the effective filing date of the claimed invention"
112/b "Means for"
BRI
Broadest Reasonable Interpretation
112/a Enablement,
Written description
CRM
"Computer-Readable Media" and equivalent language
112 Other
IDS
Information Disclosure Statement
x
102, 103
JE
Judicial Exception
x
101 JE(s)
112/a
35 USC 112(a) and similarly for 112/b, etc.
101 Other
N:N
page:line
Double Patenting
MM/DD/YYYY
date format
Priority
As detailed on the 4/8/2019 filing receipt, this application is a 371 of PCT/EP2017/061303 filed 05/11/2017 and claims benefit of priority to Foreign Application EP16001899.0, filed on 08/31/2016.
Overview of Withdrawal/Revision of Objections/Rejections
In view of the Appeal Brief received 09/08/2025:
• A new objection for claim 1 is asserted below.
• The rejections of claims 1 and 3-15 under 35 U.S.C § 112(b) in the Final Office Action mailed 04/08/2025 are withdrawn, as the clarity matters regarding "successful trajectories" have been resolved. However, additional issues have been identified necessitating new rejections under 112(b).
• The rejection of claims 1 and 3-14 under 35 U.S.C. § 101 in the Final Office Action mailed 04/08/2025 is withdrawn as discussed below.
• The rejection of claim 15 under 35 U.S.C. § 101 in the Final Office Action mailed 04/08/2025 is maintained with revision for clarity.
• The rejection of claims 1 and 3-15 under 35 U.S.C. § 103 is revised to rely on Sandor-2, instead of the previous Sandor reference.
Reference to Specification and Claims
Reference to the Specification in this Office Action refers to U.S. Patent App. Pub. No. US2019/0219992 A1, published 07/18/2019.
Reference to the Claims in this Office Action refers to the 07/08/2025 Claims.
Claim Interpretation
The following interpretations have been previously asserted and are maintained. (The first interpretation below, for "first set of process parameters," was revised to be more concise.):
The term, "first set of process parameters", recited in claims 3, 4, 7, 9, and 15, and the term, "first set of stored process parameters", recited in claim 4, are interpreted identically as "first set of process parameters."
Claims 1 and 15 recite: "wherein each of the plurality of stored sets of process parameters is associated with a successful trajectory of a respective one of the processes performed according to the respective set of process parameters", in which the stored sets of process parameters are interpreted as not requiring having been used to control a process.
Claim Objections
Claim 1 is objected to because of the following informalities: The preamble of claim 1 recites "to produce a biopharmaceutical product," while the body of the claim does not actually produce a biopharmaceutical product. The "providing a database" step of claim 1 does recite "to produce products," which does not recite "biopharmaceutical" and which is interpreted as intended use.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1 and 3-15 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claims depending from rejected claims are rejected similarly, unless otherwise noted, and any amendments in response to the following rejections should be applied throughout the claims, as appropriate.
In claim 1, regarding the recited "repeating the act of selecting..." (last step of method), the relationship is unclear between the step of "repeating..." and the preceding sub-list of steps, as to which step(s) must be repeated, e.g. as to whether "recording...," "determining a current...," "comparing...," "determining that a difference...," "querying..." and "controlling and monitoring the process using the different set of process parameters" must be repeated. Relatedly, the recited "the act of selecting..." requires but lacks clear antecedent. No such "act" has been recited. In one interpretation, only the "selecting" step is repeated. However, it is not clear that such an interpretation would be operable, since the preceding "recording...," "determining...," etc. also were presumably essential to the "selecting." It is not clear in what way the "repeating the act of selecting a different set of process parameters" would be accomplished when the preceding steps of the "identifying..." sub-list of steps are not repeated. Further, it is not clear in what way the subsequent step of "controlling and monitoring the process using the different set of process parameters" would be accomplished without repeating the preceding sub-list of steps. Possibly it is the earlier recited "identification of the different set of process parameters," comprising the entire sub-list of steps, which is intended to be repeated. Also, for better clarity, "the identification..." should be recited as "the identifying...," exactly as instantiated.
In claims 1 and 3-15, it is not clear which "process" is being controlled and monitored. The relationships are unclear among the variously recited instances of "process." For example, in the claim 1 "receiving a set... that characterize the process," it is unclear to which process this instance of the term "the process" is referring. It is not known whether this is a current process, one of a plurality of processes from the "providing a database" step, the "respective process," or some other process. Additionally, because the stored sets of process parameters correspond to different processes, it is not clear whether the culmination of claim 1 requires the (current) process to be changed to a new (or different) process. Different sets of process parameters correspond to a plurality of (different) processes (see the "providing a database…" and "wherein each of the plurality of stored sets…" steps of claim 1). Claim 15 is rejected similarly.
In the claim 1 step "querying the database to compare...," the relationship is unclear between comparing "current recorded measurements" and the "plurality of the stored sets of process parameters" in the recitation "querying the database to compare the current recorded measurements and the set of characterizing process parameters to the plurality of the stored sets of process parameters" (emphasis added). While it is understood that the characterizing process parameters are compared to the stored sets of process parameters, it is not clear what the current recorded measurements would be compared to. This rejection might be overcome by, for example, possibly amending to include what the current recorded measurements would specifically be compared to; possibly to the time-based profile of measurements representing successful trajectories, as the trajectories are associated with the stored sets of process parameters.
Claim 15, the final "wherein revising..." section, is indefinite in reciting three conditional expressions without a clear result for either, at least due to ambiguity in the punctuation, formatting, and language. The first instance relates to the recited "when a difference..." condition and the subsequent "querying..." step. The second relates to the recited "determining... when..." condition and the subsequent "controlling..." step. The third relates to the recited "when the different set…" condition and the "controlling and monitoring…" step.
In the first (the "when a difference" step), at least due to the intervening semi-colon, it is not clear how the subsequent "querying..." relates to the preceding condition. Possibly, the "when" should be amended to "determining," commas should be placed after "difference" and after "monitor the process" and the semi-colon after "criterion" should be replaced with a comma.
The second instance (the "determining, based on" step) also should be recited more clearly and concisely, possibly by deleting "when."
The third instance (the last step of claim 15, beginning with "when the different set of") extends the determining of the second conditional into a step for controlling and monitoring the process. However, possibly the full "controlling and monitoring" portion of the claim should be recited first in the step, and the phrase "when the different set of process parameters is" should be deleted.
Also, these recitations presently are formatted as a single list of four steps following the colon "wherein revising... comprises:..." However, this is improper given the apparent relationships among the list elements, e.g. what's recited appears actually to be a list of two pairs of condition-result clauses, such that the present conjunction "and" is misplaced and should occur before "determining..." For compact examination, it is assumed that the claim will be amended as suggested here.
35 USC § 101 analysis
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.
Patent eligible claims 1 and 3-14
Referring to 101 JE analysis as organized in MPEP 2106, no rejection applies to claims 1 and 3-14, at least by analogy to the analysis Step 2A, 2nd prong, 4th consideration, relating to a transformation integrating any possible judicial exceptions into a practical application, in that a transformation in this instance comprises at least the real world claim 1 step of controlling and monitoring a process using a different set of process parameters which is informed by the judicial exception of data analysis.
The Applicant's Appeal Brief, and remarks/arguments pp.13-18, filed 09/08/2025, have been fully considered, and they are persuasive in that claims 1 and 3-14 recite a practical application in the form of a transformation.
Independent claim 1 recites a practical application of a transformation at Step 2A Prong Two, in reciting "repeating the act of selecting a different set of process parameters and controlling and monitoring the process using the different set of process parameters until it is determined that a finishing condition is met," thereby reciting a real world step of controlling and monitoring a process using a different set of process parameters which is informed by the judicial exception of data analysis in repeatedly comparing current trajectories with successful trajectories, and selecting different parameters associated with successful trajectories based on similarity to current (characterizing) process parameters. Consideration was given to the instant 112(b) rejection for clarity of the claim 1 step for "repeating the act of selecting of different process parameters", and for 101 purposes it is considered that claim 1 does perform the repeating the use of different parameters to control and monitor the process, such that the practical application of a transformation is considered to be recited, and the 101 rejection for claims 1 and 3-14 is withdrawn with the expectation that Applicant will amend to correct the 112(b) issue regarding "repeating the act of selecting," possibly by amending to include all sub-steps which comprise the step for "identifying a different set of process parameters and controlling and monitoring the process using the different set of process parameters."
Patent ineligible claim 15
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more.
MPEP 2106 details the following framework for Subject Matter Eligibility analysis:
• Step 1: Are the claims directed to a category of statutory subject matter (a process, machine, manufacture, or composition of matter)? (see MPEP § 2106.03)
• Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. an abstract idea, a law of nature, or a natural phenomenon? (see MPEP § 2106.04(a)). Note, the MPEP at 2106.04(a)(2) & 2106.04(b) further explains that abstract ideas and laws of nature 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).
• laws of nature and natural phenomena are naturally occurring principles/ relations that
are naturally occurring or that do not have markedly different characteristics compared to
what occurs in nature.
• Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application? (see MPEP § 2106.04(d))
• Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept? (see MPEP § 2106.05)
Step 1 Analysis:
Step 1: Yes, claim 15 is directed to a computer system, and therefore to a category of statutory subject matter.
(Step 1: Yes)
Step 2A, Prong One Analysis:
The claims recite judicial exceptions of mathematical concepts and mental processes:
Note, for ease of examination in the Office Action, the following abbreviations have been used (it is noted these abbreviations are not used in the disclosure of the instant application):
• Process Parameter abbreviations:
1SPP = first set of process parameters, or first set of stored process parameters;
CPP = characterizing process parameters
DSPP = different set of process parameters
IdSPP = identified set of process parameters
SPP = sets of process parameters
SSPP = stored sets of process parameters
• Trajectory abbreviations:
1ST = first successful trajectory
ET = estimated trajectory
IdST = identified successful trajectory
ST = successful trajectory
• Miscellaneous abbreviations:
PCs = principal components
QA = quality attributes
RM = recorded measurements
Independent claim 15 recites mental processes of:
• Considering the data of the SSPP, of the STs and RM, of the CPP and current RM.
• Identifying a 1SPP.
• Determining a current ST.
• Comparing current ET and STs.
• Revising SPP.
• Confidence criterion (also considered a mathematical concept).
• Comparing RM and SCPP with SSPP.
• Determining a greater degree of similarity between DSPP and CPP/current RM than IdSPP and CPP/current RM (also considered a mathematical concept).
Step 2A Prong One Summary: The claims recite abstract ideas, characterized as mental processes and mathematical concepts. When considering the broadest reasonable interpretation (BRI) of the claims, there are mental processes recited in independent claim 15 (e.g., "identifying a first set of process parameters", "determining estimating a current estimated trajectory ", "comparing the current estimated trajectory with the identified successful trajectory", etc.) which in the simplest embodiment are directed to processes that may be performed in the human mind, or with pen and paper, as there are no particular limitations recited which would prevent the mental processes from being performed in the human mind or with pen and paper. The claims also recite an inherent mathematical concept in using a confidence criterion, the concept of which is discussed in Specification paragraph [0052] (refer to Pub. No. US2019/0219992). It should be noted that such analysis performed mentally, or with paper and pencil, may take considerable time and effort, and although a general-purpose computer can perform these calculations at a rate and accuracy that can far exceed the mental performance of a skilled artisan, the nature of the activity is essentially the same, and therefore constitutes an abstract idea. Therefore, the claims recite elements that constitute a judicial exception in the form of an abstract idea.
(Step 2A, Prong One: Yes)
Step 2A, Prong Two analysis:
In Step 2A, Prong One above, claim steps and/or elements were identified as part of one or more judicial exceptions (JEs). Here at Step 2A, Prong Two, any remaining steps and/or elements not identified as JEs are therefore in addition to the identified JE(s), and are considered additional elements. Because the claims have been interpreted as being directed to judicial exceptions (abstract ideas in this instance) then Step 2A, Prong Two provides that the claims be examined further to determine whether the judicial exception is integrated into a practical application [see 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
MPEP § 2106.04(d)(I) lists the following five example considerations for evaluating whether a judicial exception is integrated into a practical application:
(1) An improvement in the functioning of a computer or an improvement to other technology or another technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a).
(2) Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2).
(3) Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b).
(4) Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c).
(5) Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
Additional elements of controlling and monitoring a process: Claim 15 recites the additional elements of controlling and monitoring the process, and a control system. These additional elements do not recite an improvement to technology, or a particular transformation, because there are not clear sub-steps of revising the process parameters, specifically at least in the sub-steps beginning "when a difference between…" and "determining, based on the comparison, when…" As such, the additional elements of controlling and monitoring a process do not integrate the abstract idea into a practical application [see MPEP § 2106.05(a) and (c)].
Additional elements of data gathering: Claim 15 recite the additional elements of: (to) store data, receiving data, querying data, recording data. These steps are considered insignificant extra-solution activity, and are not sufficient to integrate an abstract idea into a practical application as they do not impose any meaningful limitation on the abstract idea or how it is performed, nor do they provide an improvement to technology [see MPEP § 2106.04(d)(I)].
Additional elements of computer components: Claim 15 recites the additional elements of a computer system, database, and a processor. The claims require only generic computer components, which do not improve technology, and do not integrate the recited judicial exception into a practical application (see MPEP § 2106.04(d)(1) and MPEP § 2106.05(f)).
Step 2A Prong Two summary: Referring to the Step 2A, Prong Two considerations listed above, none of (1) an improvement, (2) treatment, (3) a particular machine, or (4) a transformation is clear in the record, such that here in Step 2A, Prong Two, no additional step or element, alone or in combination, clearly demonstrates integration of the JE(s) into a practical application. The additional elements are further discussed below in Step 2B.
(Step 2A, Prong Two: No)
Step 2B analysis:
Because the additional claim elements do not integrate the abstract idea into a practical application, the claims are further examined under Step 2B, which evaluates whether the additional elements, individually and in combination, amount to significantly more than the judicial exception itself by providing an inventive concept. An inventive concept is furnished by an element or combination of elements that is recited in the claim in addition to the judicial exception, and is sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself (see MPEP § 2106.05).
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 are well-understood, routine, and conventional. Those additional elements are as follows:
Additional elements of controlling and monitoring a process: The additional elements of claim 15 for controlling and monitoring the process and a control system, are shown to be routine, well known, and conventional as follows:
Kakes (Practical Fermentation Technology, pages 289-322 (2008); cited on the PTO-892 mailed 07/19/2023), reports on computer-based monitoring and control systems for bioreactors (p.296 and entire document) and discusses comparison of timed measurements to a "golden batch", and importing data from previous cultures, used in controlling batches (p.306-307, and fig.10.11).
Bartee, (U.S. Patent Pub No. US 2012/0003623, published 01/05/2012; cited on the PTO-892 mailed 07/19/2023), discloses a method and system for control and monitoring of batch processes (abstract, and throughout entire document, esp. at fig.4D, fig.5, [0048]).
Largoni, (Journal of biotechnology, vol. 211, pages 87-96 (2015); cited on the PTO-892 mailed 07/19/2023), shows a method and system for monitoring and control of operations of industrial batch bioreactor processes (p.88-93, esp. at p.90, col.1-2; fig.7).
In this way, the additional element of controlling and monitoring of processes is shown to be routine, well-known, and conventional, and does not amount to significantly more than the judicial exception; an inventive concept is not shown.
Additional elements of data gathering: The additional elements of data gathering (store data, receiving data, querying data, recording data) of claim 15 do not cause the claims to rise to the level of significantly more than the judicial exception. The courts have recognized receiving or transmitting data over a network; and storing and retrieving information in memory; [see MPEP§2106.05(d)(II)], as well-understood, routine, conventional activity when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. Therefore, the data gathering steps are shown to be routine, well-understood, and conventional, and as a result, the additional element of data gathering steps does not provide an inventive concept by amounting to significantly more than the judicial exception.
Additional elements of computer components: The additional elements of a computer system comprising a database and a processor of claim 15, do not cause the claims to rise to the level of significantly more than the judicial exception; these are conventional computer components.
Further regarding the conventionality of additional elements, the MPEP at 2106.05(b) and 2106.05(d) presents several points relevant to conventional computers and data gathering steps in regards to Step 2A Prong 2 and Step 2B, including:
• A general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions, does not qualify as a particular machine (see 2106.05(b)(I)), as in the case of claim 15, which is interpreted to recite conventional computer components.
• Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not integrate a judicial exception or provide significantly more (see 2106.05(b)(III). The computer system of claim 15 used in performing data analysis and process control and monitoring does not impose meaningful limitations on the claims.
• The courts have recognized "receiving or transmitting data over a network", "performing repetitive calculations", and "storing and retrieving information in memory", as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d)(II)). The gathering of data in claim 15 is recited in a generic manner.
All the limitations of claim 15 have been analyzed with respect to Step 2B, and none of these claims provide a specific inventive concept, as they all fail to rise to the level of significantly more than the identified judicial exception, and thus do not transform the judicial exception into a patent eligible application of the exceptions.
(Step2B: NO)
Conclusion of 101 analysis
Therefore, claim 15, when the limitations are considered individually and as a whole, is rejected under 35 U.S.C. § 101 as being directed to non-patent-eligible subject matter.
Response to Applicant Arguments and Declaration- 35 USC § 101
The Applicant's Appeal brief, and remarks/arguments p.13-18, filed 09/08/2025, have been fully and respectfully considered, but they are not yet persuasive regarding claim 15.
Regarding Step 2A Prong One and claim 15: The Applicant asserts, p.13-16 of the Appeal Brief:
• The claims introduce limitations that cannot practically be performed in
the human mind and therefore do not recite a mental process under Step
2A, Prong 1 (p.13).
• …the human mind simply is not capable of achieving anything close to the totality of the invention recited in claims 1 and 15 (p.14).
• … it is incorrect to characterize the steps and structure of claims 1 and 15 as simply inputting, collecting, and outputting data; rather, claims 1 and 15 recite specific limitations that cannot practically be performed in the human mind (p.15).
The arguments regarding Step 2A Prong One are not persuasive. The limitations identified as abstract ideas in claim 15 include, e.g., data analysis steps of identifying process parameters, determining current estimated trajectories based on recorded measurements, comparing trajectories, measurements, and process parameters, revising process parameters, using a confidence criterion, determining degrees of similarly, etc. These data analysis steps as recited can be performed in the mind or with paper or pencil. Judicial exceptions, including abstract ideas of mental processes and mathematical concepts) are identified at Step 2A Prong One of the 101 analysis (see MPEP 2106.04(a)). Data gathering steps (receiving and recording measurements) and the physical step of controlling and monitoring the process are additional elements, not abstract ideas. Additional elements are identified and analyzed under Step 2A Prong Two (see MPEP 2106.04(d)).
Regarding Step 2A Prong Two and Step 2B and claim 15: The Applicant asserts, p.16-17 of the Appeal Brief:
• …even if claims 1 and 15 can be considered to be directed to an abstract idea… the claims readily pass Prong 2 of Step 2A because they use those concepts…that materially improve bioprocess production (p.16).
• … claims 1 and 15 provide concrete, technological advancements with many benefits, including: overcoming technical problem of failed processes, overcoming technical problem of inefficiencies in scaling up, and providing finder control… (p.16).
• The claims are also patent eligible under Step 2B because they recite additional elements that contribute an "inventive concept"… the claims do not simply recite generic data gathering or post-solution activity… claims 1 and 15 effect a technical improvement in process control for the industrial processes of those claims (p.17).
The arguments regarding Step 2A Prong Two and Step 2B are not yet persuasive. There has not yet been shown an improvement to technology in the claims at Step 2A Prong Two, nor is there significantly more needed, as the additional elements of data gathering and controlling and monitoring a process are shown to be conventional at Step 2B. Additionally, there is not yet a transformation recited in claim 15, in contrast to claims 1 and 3-14, because there are not clear sub-steps of revising the process parameters, specifically at least in the sub-steps beginning "when a difference between…" and "determining, based on the comparison, when…" Due to ambiguity of what these sub-steps perform, there is not a transformation recited in claim 15, and this issue is mirrored in the 112(b) rejections of claim 15. However, it appears that claim 15, if amended properly, may likely recite a transformation at Step 2A Prong Two of the 101 analysis.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
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 and 3-15 are rejected under 35 U.S.C. 103 as being unpatentable over Largoni (Journal of biotechnology vol.211, pages 87-96 (2015); cited on the PTO-892 mailed 07/19/2023), in view of Bartee, (U.S. Patent Pub No. US 2012/0003623, published 01/05/2012; cited on the PTO-892 mailed 07/19/2023), in view of Sandor-2, (BioProcess Int, vol. 11(8), 7 pages (2013); cited on the attached PTO-892); referred to as Sandor-2 to avoid confusion with the different Sandor reference used in the previous rejection.).
Note, for ease of examination in the Office Action, the following abbreviations have been used (it is noted these abbreviations are not used in the disclosure of the instant application):
• Process Parameter abbreviations:
1SPP = first set of process parameters, or first set of stored process parameters;
2SPP = second set of process parameters
CPP = characterizing process parameters
DSPP = different set of process parameters
FPP = further process parameter
IdSPP = identified set of process parameters
PP = process parameters
SPP = sets of process parameters
stPP = stored process parameters
SSPP = stored sets of process parameters
• Trajectory abbreviations:
1ST = first successful trajectory
ET = estimated trajectory
IdST = identified successful trajectory
ST = successful trajectory
• Miscellaneous abbreviations:
CV = corresponding value
PCs = principal components
QA = quality attributes
RM = recorded measurements
Summary of Claims:
Independent claim 1 recites a computer implemented method for controlling and monitoring an industrial process to produce a biopharmaceutical product by: providing a database for storing stored sets of process parameters (SSPP); each set of which is associated with a successful trajectory (ST) of a process, where the ST is a profile of timed process measurements; receiving a set of characterizing process parameters (CPP) to characterize the process; querying the database to identify a set of process parameters (SPP), of the SSPP, the identified set of process parameters (IdSPP) having a specified degree of similarity to the CPP, and the IdSPP is associated with an identified successful trajectory (IdST); controlling and monitoring the process using the IdSPP associated with an IdST; identifying a different set of process parameters (DSPP) by recording measurements continually during the process to obtain current measurements; determining a current estimated trajectory (ET) based on the current recorded measurements (RM); comparing the current ET with the IdST associated with the set of PP currently being used; determining a difference between the current estimated trajectory and the IdST associated with the set of PP currently being used fails a predetermined confidence criterion, querying the database to compare current RM and CPP to the SSPP; selecting a set of PP from the plurality of SSPP which is different from the set of PP currently being used, and which has a greater degree of similarity to the CPP and the RM than the set of PP currently being used; controlling and monitoring the process using the DSPP; and repeating the act of selecting a DSPP and using the DSPP to control and monitor the process until it is determined that a finishing condition is met.
Independent claim 15 recites a computer system to control and monitor a process similar to that recited in independent claim 1.
Dependent claim 3 further recites the CPP and the SSPP include numerical and text values; and identifying the (one) SSPP by identifying a 1SPP by comparing the numerical values of the SSPP and the CPP via multivariate data analysis.
Dependent claim 4 further recites identifying the first set of process parameters (1SPP) by: determining, via multivariate analysis, stPP (stored process parameters) that have an effect on quality attributes (QA); included in the CPP; determining the ranking of stPP by significant effect on QA; that the determined process parameters are not included in the CPP; but are included in the 1SPP.
Dependent claim 5 further recites the QA include misincorporation, glycosylation, recovery, misfolds, aggregation, product concentration, protein concentration, moisture, foreign particles, total mass, drug release rate, and total drug content.
Dependent claim 6 further recites the QA include titer, power consumption, target process duration, cell density, or volumetric productivity; and where volumetric productivity is volume yield of product over time.
Dependent claim 7 further recites determining principal components (PCs) from the CPP and the RM; calculating a characterizing numerical description of the process as a function of the PC; identifying a 1SPP and a 2SPP; the 1SPP and the 2SPP respectively include first and second numerical descriptions of their respective process calculated as a function of a plurality of PC derived from the 1SPP and the 2SPP; determining that the characterizing numerical description is closer to the second numerical description than the first, and that each principal component may be a linear combination of process parameters.
Dependent claim 8 further recites the identified ST includes a 1ST; the 1ST is associated with a standard deviation, of which the confidence criterion is a function.
Dependent claim 9 further recites identifying a 1SPP which includes a further process parameter (FPP) and a corresponding value (CV); the FPP is included in the CPP; the CV is not included with the CPP; controlling and monitoring the process using the FPP and the CV; and the FPP may be a control set point.
Dependent claim 10 further recites the CPP and/or the stored process parameters include: a description of the process equipment; a scale of the process; a type of the process; a name of the product; a biological system of the process; quality attributes to measure the quality of the product; and/or a configuration of the equipment.
Dependent claim 11 further recites the configuration of the equipment includes: a target process duration; a target temperature; a stirrer/agitator speed; a target pH level; a feed rate; a target substrate level; and/or a target dissolved oxygen level.
Dependent claim 12 further recites the RM comprise: a current duration of the process; a partial pressure of carbon dioxide; a cell density; a cell viability; a substrate concentration; a metabolite concentration; a time of infection; and/or a current temperature.
Dependent claim 13 further recites when the product is a biopharmaceutical product, the product is one of the following: a recombinant protein, a non-recombinant protein, a vaccine, a gene vector, DNA, RNA, an antibiotic, a secondary metabolite, cells for cell therapy or regenerative medicine, an artificial organ
Dependent claim 14 further recites a computer program product to run the computer method of claim 1.
(End of Summary of Claims)
Regarding claims 1 and 15, Largoni shows a method for monitoring a batch bioreactor process for producing an avian vaccine, using multivariate statistical models, built from historical databases which comprise on-line process measurements as well as end-point quality measurements for 38 batches, among which 33 batches were classified as "normal" (i.e., successful batches with successful trajectories) (p.89, col.1; p.90, col.2). Largoni shows when a set of measurements (a new observation) becomes available for a new batch at a given time instant, the observation is projected onto the control charts, and a fault alarm is generated if the projections (i.e., trajectories) lie above the T2 confidence limit or the squared prediction error (SPE) confidence limit (p.90, col.1). Largoni shows the bioreactor is run following an assigned recipe with fixed batch length of 61 hours (i.e., a finishing condition) (p.89, col.1). Largoni shows different sets of plant measurements trajectory combinations (i.e., sets of process parameters and trajectories) that correspond to the same final viral titer, and according to the partial least squares model, correspond to a final product that is exactly on specification; in this way a batch can be classified (i.e., monitored) as it is progressing into as predicted to end up with an on-spec or an off-spec product (p.90, cols.1-2). Largoni shows by tracking how the score projections move across the two subspaces as time progresses, one can predict whether the batch is expected to end up with an on-spec product or with an off-spec one (p.90, col.2) (showing monitoring the process using the identified set of process parameters which are associated with an identified successful trajectory of claims 1 and 15). Largoni further shows when a new observation (i.e., CPP from a progressing batch) becomes available from the plant, it is projected onto the PLS model space, and the relevant scores are calculated (p.90, col.2; p.93, col.1-2 & fig.8a/b), (i.e., identifying a IdSPP having similarity to the CPP, where the IdSPP is associated with a 1ST; and comparing estimating a trajectory of the process based on recorded measurement).
Regarding claims 3 and 4, Largoni shows the operation of a running batch can be monitored effectively using the measurements the plant makes available on line (i.e., numerical values of CPP), and analyzing these measurements altogether through a multivariate statistical model (i.e., ranking measurements) (p.95, col.1). Largoni shows by using available historical data (i.e., stored process parameters), different multivariate statistical models were built to perform process monitoring, including determining in real time whether a batch is evolving to an on-spec or to an off-spec product ("batch quality classification") (p.90. col.1).
Regarding claim 7, Largoni shows using principal component analysis (PCA) in their process monitoring method for detecting batch contamination (a typical abnormality). The PCA model was built on a matrix X; and the Hotelling T2 and squared prediction error (SPE) limits were calculated. When a set of measurements (a new observation) became available for a new batch at a given time instant, the observation was projected onto the control charts (can be considered first and second numerical descriptions) and a fault alarm was generated if the projections were above the T2 confidence limit or the SPE confidence limit (i.e., determining if the first or second numerical description is closer) (p.90, col.1; p.91, col.1 and fig.4).
Regarding claim 8, Largoni shows after autoscaling on the mean and standard deviation of the calibration dataset, and batch-wise unfolding, a new batch xnew can be checked for conformity to the observations of the calibration dataset by comparing the statistics T2new (Hotelling T squared) and SPEnew (squared prediction error) to the respective confidence limit (i.e., confidence criterion) (p.95, col.2).
Regarding claim 9, Largoni shows a list of variables measured (i.e., sets of process parameters) from the bioreactor, which include on-line process measurements as well as end-point quality measurements; several setpoint (SP) (i.e., a control set point) measurements are shown in table 1. (p.89, cols.1-2). Largoni shows a profile of a contaminated batch with 95% confidence limits (i.e., a corresponding value), using the PCA model (p.90, col.1, and p.92, fig.5).
Regarding claims 10, 11, 12, and 13, Largoni states the infection process takes place in a 600-liter jacketed batch bioreactor (i.e., description of equipment) under controlled (i.e., target) pH, temperature, dissolved oxygen and pressure (p.88, col.2); a current reactor temperature is measured in real time (i.e., recorded measurements) (p.89, table 1); and the product is an avian vaccine (i.e., a biopharmaceutical product) (p.88, col.2).
While Largoni shows monitoring the process using the identified set of process parameters which are associated with an identified successful trajectory (p.90), Largoni does not specifically show: controlling the process using the identified set of process parameters which are associated with an identified successful trajectory of claims 1 and 15.
What Largoni does not show:
• Largoni does not show identifying a different set of process parameters and controlling and monitoring the process using the different set of process parameters of claims 1 and 15.
• Largoni does not specifically show: controlling of a process based on a different ST if a different SPP is more similar than a IdSPP to the CPP of claims 1 and 15.
• Largoni does not show repeating the act of selecting process parameters of claim 1 (revising in claim 15).
• Largoni does not specifically show: the determined process parameters are not included in the CPP of claim 4.
• Largoni does not show the quality attributes recited in claims 5 and 6, nor the computer readable medium of claim 14.
Regarding the identifying a different set of process parameters and controlling and monitoring the process using the different set of process parameters; and controlling of a process based on a different ST if a different SPP is more similar than a IdSPP to the CPP of claims 1 and 15, Bartee at [0035] states "FIG. 4D illustrates control of a batch reaction process to an optimized target trajectory for a controlled variable of the batch (e.g., biofuel concentration), and the actual trajectory achieved by adjusting values for the manipulated variables during the batch reaction process. Bartee also shows the hybrid or parametric constrained training of empirical modeling … may be implemented based on historic plant data and limited plant testing data [0073], and the hybrid model may use model equations to calculate various coefficients with available data to fit a best model, within measured and/or historic performance [0074]. Bartee shows their parametric hybrid model is used to generate continuous trajectories (i.e., current and identified trajectories) for "derived" measures (e.g., stored sets of process parameters) of batch reaction operation over the course of the batch reaction progression, and is then used to calculate an optimal dynamic trajectory or batch reaction path based on the critical quality parameters. The dynamically-generated optimal trajectory and the parametric hybrid model may be incorporated into a real-time, model-based control system that corrects batch progression as closely as possible, following the optimal quality parameter trajectory within equipment constraints [0129].
Regarding the repeating the act of selecting process parameters and controlling and monitoring the process using the different set of process parameters of claim 1, Bartee shows their method (for controlling batch reaction processes) may be repeated, e.g., at a specified frequency, or in response to specified events, so that the batch reaction process may be monitored and controlled throughout a production process, or throughout a series of production processes (Bartee, [0048] and fig. 5.).
Further regarding the controlling and monitoring the process using the identified set of process parameters which are associated with an identified successful trajectory of claims 1 and 15, Bartee shows execution of the nonlinear multivariate predictive model 705 to determine a desired batch trajectory (i.e., identified successful trajectory) over the temporal control horizon in accordance with the end-of-batch objective, and provides the desired batch trajectory to the nonlinear control model 715 as a control objective, receive process information for the batch reaction process; and execute the nonlinear control model 715 in accordance with the determined desired batch trajectory (i.e., the identified successful trajectory) using the received process information (i.e., process parameters) as input, thereby generating model output (i.e., controlling the process with identified successful batch trajectory) (Bartee, [0062]).
Further regarding the controlling and monitoring the process using the identified set of process parameters which are associated with an identified successful trajectory and querying sets of process parameters associated with successful trajectories of claims 1 and 15, Sandor-2 presents a method using Near-Infrared Spectroscopy (NIRS) data to generate Batch Evolution Models in bioprocess monitoring and control (pp. 1-3 of 7 of the document as it appears in the instant record), and discusses generation of the batch evolution model from high performance batches (i.e., successful trajectories). Sandor-2 states "adjusting process parameters is made possible by real-time overview of processes" (p.6 of 7, top of col.1; p.7 of 7, col.1). Sandor-2 also shows three fed batches were performed with optimal process parameter settings to evaluate process repeatability, and using spectra from those batches for golden batch modeling in MSPC (multivariate statistical process control) (p.3 of 7, col.1). Sandor-2 further shows a BEM (batch evolution model) based on a third principal component; the model (dashed lines, lower panel of fig.2, p.3 of 7) is generated from high performance batches (i.e., golden batches [which have successful trajectories]) (p.6 of 7, col.1, and p.3 of 7,fig.2). These points show controlling and monitoring a process using an identified set of process parameters which are associated with an identified successful trajectory and querying sets of process parameters associated with successful trajectories of claims 1 and 15.
Regarding the "determined process parameters are not included in the CPP"; and the "determined process parameters that have a significant effect on the QA" limitations of claim 4, and all limitations of claims 5 and 6, Bartee shows constraints may be incorporated as trajectory function, including both real-time and end-of-batch limits (e.g. maximum/minimum utility consumption, temperatures within equipment or reaction limits, and maximum/minimum co-product or contaminant concentrations in the end-of-batch volume) [0124] (i.e., stored process parameters that have an effect on QA). Bartee teaches quality parameters (i.e., QA) that are closely related to, but not identical to, end-of-batch objectives during the progression of a batch reaction process, and using these quality parameters to correct the batch trajectory while the batch is still progressing (i.e., not included in the CPP, but are included in the 1SPP) [0127]. Bartee shows high fidelity models of end-of-batch quality measurements may be generated using measured variables during the batch. For example, in a pharmaceutical production process, total feed, maximum variations in the content of poison in the broth, broth pH levels, maximum rate of change in the batch pH level, and so forth, may be used to predict end-of-batch quality measurements, such as titer concentrations (i.e., product concentration and titer) [0120].
Regarding claim 14, Bartee discloses a memory medium that stores program instructions [0049], and the software program(s) may perform various aspects of modeling, prediction, optimization, and/or control of the fermentation process [0054].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the methods of monitoring batch bioreactors using PCA and historic data of Largoni; with the method of controlling batch reaction processes of successful trajectories of Bartee; with the Golden batch model and high performance batch modeling of Sandor-2, to come to a method of monitoring and controlling a process for producing a biopharmaceutical product. This is because Largoni shows that by analyzing process measurements altogether through a multivariate statistical model, faults could be detected more promptly than currently done (p.95), as well as the end-point product quality can be predicted in real time while the batch is running (p.94); and because Bartee states their various systems and methods use nonlinear models to perform model predictive control to improve the yield, throughput, and/or energy efficiency of the batch reaction process, in accordance with specified objectives [0058]. Sandor-2 adds motivation to combine by discussing adjusting process parameters is made possible by real-time overview of processes, which can help to keep them within required specifications; that could lower the number of failed batches (p.7 of 7, col.1). One would have had a reasonable expectation of success in doing so because Largoni, Bartee, and Sandor-2 are generally drawn to related teaching of controlling and monitoring batch processes, and one of ordinary skill in the art would have understood how to and would have been motivated to apply the teaching of Bartee, and Sandor-2 to the related teachings of Largoni, and as such, the combination would have been obvious.
Response to Applicant Arguments - 35 USC § 103
The Applicant's arguments filed in the 09/08/2025 Appeal Brief have been fully considered but they are not persuasive.
The Applicant asserts, at p. 10-11 of the Appeal Brief, that Largoni does not teach or suggest storing sets of process parameters associated with successful trajectories and re-matching to a different successful trajectory.
The Applicant further asserts, at p. 11 of the Appeal Brief, that Bartee also does not teach or suggest storing sets of process parameters associated with successful trajectories and re-matching to a different successful trajectory; …and that Bartee operates with a parametric hybrid model whose coefficients are computed once from historical data.
The arguments are not persuasive because Largoni is relied upon for teaching "storing sets of process parameters associated with successful trajectories", and Bartee is relied upon for teaching "repeating the act of selecting a different set of process parameters," as follows:
Largoni shows: monitoring a batch bioreactor process for producing an avian vaccine, using multivariate statistical models, built from historical databases which comprise on-line process measurements as well as end-point quality measurements for 38 batches, among which 33 batches were classified as "normal" (i.e., showing stored sets of successful batches with successful trajectories) (p.89, col.1; p.90, col.2).
Bartee shows their method (for controlling batch reaction processes) may be repeated, e.g., at a specified frequency, or in response to specified events, so that the batch reaction process may be monitored and controlled throughout a production process, or throughout a series of production processes (Bartee, [0048] and fig. 5.).
The Applicant asserts, at p. 11 of the Appeal Brief, that that the "desired batch trajectory" of Bartee is not a "successful trajectory" of the type recited in claims 1 and 15, and that the "successful trajectories" of claims 1 and 15 correspond to trajectories of processes that have been successfully completed (i.e., trajectories that resulted in products meeting the quality attributes for the product).
The argument is not persuasive because Bartee teaches execution of the nonlinear multivariate predictive model 705 to determine a desired batch trajectory (i.e., identified successful trajectory) over the temporal control horizon in accordance with the end-of-batch objective, and provides the desired batch trajectory to the nonlinear control model 715 as a control objective [0062]. As the desired batch trajectory of Bartee is provided to the control model, this is a successful trajectory used in control of the batch process.
While Applicant has asserted that the "successful trajectories" of claims 1 and 15 correspond to trajectories of processes that have been successfully completed (i.e., trajectories that resulted in products meeting the quality attributes for the product), neither trajectories of successfully completed processes, nor trajectories resulting in products meeting quality attributes, is recited or required by the claims.
It is noted the following claim interpretation relates somewhat (this interpretation has been provided above as well as in the past three Office actions): "Claims 1 and 15 recite: "wherein each of the plurality of stored sets of process parameters is associated with a successful trajectory of a respective one of the processes performed according to the respective set of process parameters", in which the stored sets of process parameters are interpreted as not requiring having been used to control a process."(Emphasis added.)
The Applicant asserts at p. 12-13 of the Appeal Brief, that Sandor does not remedy the deficiencies of Largoni and Bartee because it also does not teach or suggest storing sets of process parameters associated with successful trajectories and re-matching to a different successful trajectory.
The arguments are not persuasive because a new reference, Sandor-2 has replaced the Sandor reference from the last rejection. Sandor-2 presents a method using Near-Infrared Spectroscopy (NIRS) data to generate Batch Evolution Models in bioprocess monitoring and control (pp.1-3 of 7), and discusses generation of the batch evolution model from high performance batches (i.e., successful trajectories). Sandor-2 states "adjusting process parameters is made possible by real-time overview of processes", (p.6 of 7, top of col.1; p.7 of 7, col.1). Sandor-2 also shows three fed batches were performed with optimal process parameter settings to evaluate process repeatability, and using spectra from those batches for golden batch modeling in MSPC (multivariate statistical process control) (p.3 of 7, col.1). Sandor-2 further shows a BEM (batch evolution model) based on a third principal component; the model (dashed lines, lower panel of fig.2, p.3 of 7) is generated from high performance batches (i.e., golden batches [which have successful trajectories]) (p.6 of 7, col.1, and p.3 of 7,fig.2). These points show controlling and monitoring a process using an identified set of process parameters which are associated with an identified successful trajectory and querying sets of process parameters associated with successful trajectories of claims 1 and 15.
Note about relevant prior art not relied upon
The following prior art made of record and not relied upon in this Office Action is considered relevant to Applicant’s disclosure:
• Li, March 2016. A feasibility research on the monitoring of traditional Chinese medicine production process using NIR-based multivariate process trajectories. Sensors and Actuators B: Chemical, vol. 231, pages 313-323; cited on the PTO-892 mailed 04/08/2025.
• Lopez-Montero, 2015. Trajectory tracking of batch product quality using intermittent measurements and moving window estimation. Journal of Process Control, vol. 25, pages 115-128; cited on the attached PTO-892.
• Sandor, 2013, December. NIR-spectroscopy for bioprocess monitoring & control. In BMC proceedings, Vol. 7, pages 1-3, BioMed Central; cited on the PTO-892 mailed 04/08/2025.
• Simutis, 2015. Bioreactor control improves bioprocess performance. Biotechnology journal, vol. 10(8), pages 1115-1130; cited on the PTO-892 mailed 04/08/2025.
Conclusion
No claim is allowed.
This Office action is a Non-Final action. A shortened statutory period for reply to this action is set to expire THREE MONTHS from the mailing date of this action.
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/M.A.V./Examiner, Art Unit 1687
/G. STEVEN VANNI/Primary patents examiner, Art Unit 1686