DETAILED ACTION
The Applicant’s response, received 20 July 2026, has been fully considered. 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 .
Status of the Claims
Claims 1-15 are pending.
Claims 1-15 are rejected.
Priority
This application is a 371 of PCT/EP2021/063867, filed 25 May 2021, and claims benefit of priority to foreign application EUROPEAN PATENT OFFICE (EPO) 20176466.9, filed 26 May 2020.
Claim Interpretation
The claim interpretations under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, in the Office action mailed 20 April 2026 have been maintained in view of the amendment received 20 July 2026.
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitation(s) are:
at least one communication interface, in claim 14;
at least one processing unit, in claim 14; and
at least one output device, in claim 14.
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
The written description discloses a corresponding structure for the following generic placeholders:
at least one communication interface, in claim 14 (Specification at page 16, lines 11-13, e.g., a network or internet port, a USB-port and a disk drive, or a web interface);
at least one processing unit, in claim 14 (Specification at page 16, lines 15-27, e.g., a processor); and
at least one output device, in claim 14 (Specification at page 25, lines 10-13, e.g., a display device).
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Objections
The objection to claim 13 in the Office action mailed 20 April 2026 has been withdrawn in view of the amendment received 20 July 2026.
Claim Rejections - 35 USC § 112
The rejection of claim 3 under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, in the Office action mailed 20 April 2026 has been withdrawn in view of the amendment received 20 July 2026.
Claim Rejections - 35 USC § 101
The rejection of claims 12 and 13 at Step 1 under 35 U.S.C. 101 (because the claimed invention is directed to non-statutory subject matter) in the Office action mailed 20 April 2026 has been withdrawn in view of the amendment received 20 July 2026.
The Applicant’s amendment received 20 July 2026 has been fully considered, however after further consideration, the rejection of claims 1-15 under 35 U.S.C. 101 (because the claimed invention is directed to an abstract idea without significantly more) in the Office action mailed 20 April 2026 has been maintained with modification in view of the amendment, as noted below.
The rejection has been modified to incorporate the newly amended limitations.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106.
Eligibility Step 1: Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter?
Claims 1-11 recite a computer-implemented method (i.e., a process); claim 12 recites a computer program stored on a non-transitory computer-readable storage medium (i.e., a process and/or a machine and/or a manufacture); claims 13 recites a non-transitory computer-readable storage medium comprising instructions (i.e., a process and/or a machine and/or a manufacture); and claims 14-15 recite a control system (i.e., a machine and/or a manufacture).
Therefore, these claims are encompassed by the categories of statutory subject matter, and thus, satisfy the subject matter eligibility requirements under step 1.
[Step 1: YES]
Eligibility Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A Prong One: In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
the method is a self-learning method (i.e., mental processes);
at step (b) training of at least one machine-learning model based on the process variable (i.e., mental processes and mathematical concepts);
at step (c) determining the target parameter set by applying an optimizing algorithm in terms of at least one optimization target on the trained machine-learning model (i.e., mental processes and mathematical concepts); and
at step (d) considering the determined target parameter set for evaluating a flow chemistry setup and/or for evaluating at least one flow chemistry product (i.e., mental processes).
Independent claim 12 recites a program stored on a non-transitory computer-readable storage medium and configured for causing a computer or a computer network to fully or partially perform the abstract ideas recited by independent claim 1, as noted above.
Independent claim 13 recites a non-transitory computer-readable storage medium comprising instructions which, when executed by a computer or computer network, cause the computer or computer network to perform the abstract ideas recited by independent claim 1, as noted above.
Independent claim 14 recites an automated control system configured to perform the abstract ideas recited by independent claim 1, as noted above.
Dependent claims 2-4, 6, 9-11 and 15 further recite the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas, as noted below.
Dependent claim 2 further recites:
the determined target parameter set is used as starting point for a next optimization (i.e., mental processes).
Dependent claim 3 further recites:
steps (b), (c), and (d) are repeated until the process variable measured by the sensor fits to a previously defined target value within a pre-defined accuracy (i.e., mental processes and mathematical concepts).
Dependent claim 4 further recites:
the target parameter set comprises at least one parameter selected from the group consisting of:
flow rate of at least one pump; temperature; reaction time; at least one parameter from online analytics of an educt; and an amount of seed particles (i.e., mental processes).
Dependent claim 6 further recites:
the process variable comprises at least one spectral information; at least one intensity information; at least one brightness information; at least one turbidity information, or at least one colorfulness information (i.e., mental processes).
Dependent claim 9 further recites:
at least one validation step (i.e., mental processes),
wherein at least one measurement value of the determined process variable is validated (i.e., mental processes),
wherein the validation comprises comparing the measurement value with at least one predefined criterion (i.e., mental processes and mathematical concepts).
Dependent claim 10 further recites:
the method comprises at least one anomaly detection step (i.e., mental processes),
wherein at least one algorithm monitors at least one measurement signal of the sensor (i.e., mental processes),
wherein the algorithm is configured for determining at least one anomaly (i.e., mental processes).
Dependent claim 11 further recites:
the optimization target is at least one user's specification (i.e., mental processes),
wherein the optimization target is a concentration of at least one produced fluid (i.e., mental processes).
Dependent claim 15 further recites:
performing the method according to steps (b), (c), and (d) of claim 1.
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pen and paper (e.g., considering the determined target parameter set for evaluating a flow chemistry setup and/or for evaluating at least one flow chemistry product), and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas (e.g., training of at least one machine-learning model based on the process variable) are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1-15 recite an abstract idea.
[Step 2A Prong One: YES]
Eligibility Step 2A Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below.
In the instant application, the independent claims provide additional elements to obtain ‘at least one process variable’, however once the data is received, the subsequent steps only perform steps of training a machine learning model based on the process variable and using the trained machine learning model to determine a ‘target parameter set.’ However, once the ‘target parameter set’ has been determined, the subsequent step only recites ‘providing’ the ‘determined target parameter set’, and thus, the claims do not recite any limitations (i.e., additional elements) to which the ‘determined target parameter set’ (i.e., the result of the data analysis) is practically applied.
Dependent claims 2, 4, 6, and 11 do not further recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
The additional elements in independent claim 1 include:
a computer;
at step (a) determining at least one process variable by using at least one sensor of a flow chemistry setup (i.e., gathering data); and
at step (d) providing the determined target parameter set (i.e., outputting data).
The additional elements in independent claim 12 include:
a non-transitory computer-readable storage medium with stored instructions;
a computer or a computer network;
at step (a) determining at least one process variable by using at least one sensor of a flow chemistry setup (i.e., gathering data); and
at step (d) providing the determined target parameter set (i.e., outputting data).
The additional elements in independent claim 13 include:
a non-transitory computer-readable storage medium with stored instructions;
a computer or a computer network;
at step (a) determining at least one process variable by using at least one sensor of a flow chemistry setup (i.e., gathering data); and
at step (d) providing the determined target parameter set (i.e., outputting data).
The additional elements in independent claim 14 include:
at least one communication interface configured for receiving at least one process variable determined by at least one sensor of at least one flow chemistry setup;
at least one processing unit; and
at least one output device configured for providing the determined target parameter set.
The additional elements in dependent claims 3, 5, 7, 8, 9, 10, and 15 include:
at step (a) determining at least one process variable by using at least one sensor of a flow chemistry setup (i.e., gathering data) (claim 3);
at step (d) providing the determined target parameter set (i.e., outputting data) (claim 3);
the process variable is determined by measuring of one or more quantities of slugs flowing through at least one tubular reactor (claim 5);
determining of the process variable comprises one or more of: ultraviolet and visible spectroscopy (UV-VIS) spectroscopy, Raman spectroscopy, infrared (IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, optical detection, fluorescence spectroscopy, mass spectrometry (MS), high performance liquid chromatography (HPLC), gas chromatography (GC), conductometry and pH- determination, calorimetry, viscosity determination, powder X-ray diffraction (PXRD), or automated titration (claim 7);
the sensor comprises one or more of at least one spectrometer, at least one light barrier, at least one chromatograph, a viscometer, at least one titration device, or at least one calorimeter (claim 8);
step a) is repeated in case the measurement value of the determined process variable is not validated (claim 9);
step a) is repeated in case an anomaly is detected (claim 10); and
at step a) determine at least one process variable by using at least one sensor of a flow chemistry setup (i.e., gather data) (claim 15); and at step d) provide the determined target parameter set (i.e., output data) (claim 15).
The additional elements of a computer (claim 1); a non-transitory computer-readable storage medium with stored instructions (claims 12 and 13); a computer or a computer network (claims 12 and 13); at least one communication interface configured for receiving at least one process variable determined by at least one sensor of at least one flow chemistry setup (claim 14); at least one processing unit (claim 14); and at least one output device configured for providing the determined target parameter set (claim 14); invoke a computer and/or computer-related components merely as tools for use in the claimed process, and therefore are not an improvement to computer functionality itself, or an improvement to any other technology or technical field, and thus, do not integrate the judicial exceptions into a practical application (MPEP 2106.04(d)(1)).
The additional element at step (a) of determining at least one process variable by using at least one sensor of a flow chemistry setup (claims 1, 3, 9, 10, 12, 13, and 15); is merely a pre-solution activity of gathering data for use in the claimed process – a nominal or tangential addition to the claims that does not meaningfully limit the claims, and therefore does not add more than insignificant extra-solution activity to the judicial exceptions (MPEP 2106.05(g)).
The additional element at step (d) of providing the determined target parameter set (claims 1, 3, 12, 13, and 15); is merely a post-solution activity of outputting data that is used in the claimed process – a nominal or tangential addition to the claims that does not meaningfully limit the claims, and therefore does not add more than insignificant extra-solution activity to the judicial exceptions (MPEP 2106.05(g)).
The additional elements of the process variable is determined by measuring of one or more quantities of slugs flowing through at least one tubular reactor (claim 5); determining of the process variable comprises one or more of: ultraviolet and visible spectroscopy (UV-VIS) spectroscopy, Raman spectroscopy, infrared (IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, optical detection, fluorescence spectroscopy, mass spectrometry (MS), high performance liquid chromatography (HPLC), gas chromatography (GC), conductometry and pH- determination, calorimetry, viscosity determination, powder X-ray diffraction (PXRD), or automated titration (claim 7); and the sensor comprises one or more of at least one spectrometer, at least one light barrier, at least one chromatograph, a viscometer, at least one titration device, or at least one calorimeter (claim 8); are limitations that further define the additional element at step a) of determining at least one process variable by using at least one sensor of a flow chemistry setup, and therefore are merely components of the pre-solution activity of gathering data for use in the claimed process – nominal or tangential additions to the claims that do not meaningfully limit the claims, and therefore do not add more than insignificant extra-solution activity to the judicial exceptions (MPEP 2106.05(g)).
Thus, the additionally recited elements merely invoke a computer and/or computer related components as tools; and/or amount to insignificant extra-solution activity; and as such, when all limitations in claims 1-15 have been considered as a whole (i.e., the analysis takes into consideration all the claim limitations and how those limitations interact and impact each other when evaluating whether the exception is integrated into a practical application), the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-15 are directed to an abstract idea (MPEP 2106.04(d)).
[Step 2A Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
Dependent claims 2, 4, 6, and 11 do not further recite any elements in addition to the judicial exception(s).
The additional elements recited in independent claims 1, 12, 13, and 14 and dependent claims 3, 5, 7, 8, 9, 10, and 15 are identified above, and carried over from Step 2A Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional elements of a computer (claim 1); a non-transitory computer-readable storage medium with stored instructions (claims 12 and 13); a computer or a computer network (claims 12 and 13); at least one communication interface configured for receiving data (claim 14); at least one processing unit (claim 14); at least one output device configured for outputting data (claim 14); and outputting data (claims 1, 3, 12, 13, and 15); are conventional computer components and/or functions (see MPEP at 2106.05(b) and 2106.05(d)(II) regarding conventionality of computer components and computer processes).
The additional elements at step (a) of: determining at least one process variable by using at least one sensor of a flow chemistry setup (claims 1, 3, 9, 10, 12, 13, and 15); the process variable is determined by measuring of one or more quantities of slugs flowing through at least one tubular reactor (claim 5); determining of the process variable comprises one or more of: ultraviolet and visible spectroscopy (UV-VIS) spectroscopy, Raman spectroscopy, infrared (IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, optical detection, fluorescence spectroscopy, mass spectrometry (MS), high performance liquid chromatography (HPLC), gas chromatography (GC), conductometry and pH- determination, calorimetry, viscosity determination, powder X-ray diffraction (PXRD), or automated titration (claim 7); and the sensor comprises one or more of at least one spectrometer, at least one light barrier, at least one chromatograph, a viscometer, at least one titration device, or at least one calorimeter (claim 8); are conventional. Evidence of conventionality is shown by:
Plutschack et al. (“The Hitchhiker’s Guide to Flow Chemistry.” Chemical Reviews, 2017, vol. 117, pp. 11796-11893, as cited in the Office action mailed 20 April 2026); and
Sans et al. (“Towards dial-a-molecule by integrating continuous flow, analytics and self-optimization.” Chemical Society Reviews, 2016, vol. 45, pp. 2032-2043, as cited in the Office action mailed 20 April 2026).
Plutschack et al. reviews the basic principles and fundamentals of flow chemistry, which involves the use of channels or tubing to conduct a reaction in a continuous stream rather than in a flask, and provides chemists with unique control over reaction parameters enhancing reactivity (Abstract). Plutschack et al. shows that many different flow regimes can exist for liquid-liquid mixtures, however, laminar and slug flow are most commonly described for reactions in microchips and tube reactions (page 11798, col. 1, bottom; and Figure 3). Plutschack et al. further shows that online or inline analysis techniques may be useful if extensive optimization of reaction parameters, the kinetics/mechanism of the transformation, permanent quality control of a continuous process, or the generation and downline processing of reactive and toxic intermediates is of interest (page 11812, col. 1, Section 3.8.1., para 1); and that online analysis means that the rection mixture is periodically analyzed without manual transfer via systems which automatically sample aliquots and transfer them to the respective analytical instrument, allowing for the utilization of the vast majority of analytical techniques such as HPLC, GC, mass spectroscopy, fluorescence spectroscopy, and X-ray spectroscopy, and if the analytical method is (i) non-destructive and (ii) allows for “real-time analysis as in FTIR, Raman, UV-vis, and NMR spectroscopy, such integration of the analysis unit in the flow process (inline) via an analytical flow-through cell is feasible (page 11812, col. 1, Section 3.8.1., para 2).
Sans et al. reviews the field of continuous-flow chemistry and how integrating analytics in-line enables obtaining a large amount of information in real-time about the reaction progress, and to subsequently influence the reaction progress via automated feedback optimization (Abstract). Sans et al. shows that it is possible to develop algorithms that influence, control and explore complex reaction landscapes in an autonomous and automated way, thus closing the gap between discovery and application (page 2033, col. 2, para. 2); and further shows various examples of in-line reaction monitoring devices and techniques, e.g., UV-Vis spectroscopy (page 2033, col. 2, bottom); Raman spectroscopy (page 2034, col. 2); IR spectroscopy (page 2035, col. 2); mass spectrometry (page 2037, col. 1); and nuclear magnetic resonance (page 2038, col. 1).
Therefore, when taken alone (i.e., individually), all additional elements in claims 1-15 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as an ordered combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-15 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
Response to Arguments
The Applicant’s arguments/remarks received 20 July 2026 have been fully considered, but are not persuasive.
The Applicant states on page 5 (as filed) of the Remarks that the Applicant traverses the rejection of claims 1-15 under 35 U.S.C. 101. The Applicant provides a summary of the test for determining whether a claim is directed to patent-eligible subject matter on pages 5-6, and further states on page 6 (para. 3) that pursuant to the subject matter eligibility analysis under the PEG, the claims are not directed to a judicial exception and are patent eligible. The Applicant further states (page 6, bottom, and page 7, top) that claims 1-15 do not recite concepts that explicitly fall into the abstract idea exception categories of (a) mathematical concepts, (b) certain methods of organizing human activity, or (c) mental processes, and therefore, for at least this reason, the eligibility analysis should end at the first prong of Revised Step 2A.
These arguments/remarks are not persuasive, because at Eligibility Step 2A Prong One, examiners evaluate whether a claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. As noted in the above rejection, at least independent claim 1 has been determined to recite a judicial exception at least at step (b), i.e., “training of at least one machine-learning model based on the process variable,” and therefore the eligibility analysis does not end at the first prong of Revised Step 2A, and must proceed to the second prong of the analysis (i.e., does the claim recite additional elements that integrate the judicial exception into a practical application?).
The Applicant states on page 7 (para. 2) of the Remarks that even assuming arguendo that it could be determined that the clams somehow do explicitly recite a judicial exception, each of the claims integrates such recitation into a practical application and, therefore, should be deemed to be not directed to the patent-ineligible judicial exception in accordance with the second prong of the Revised Step 2A. The Applicant further states that specifically, the practical application of the claims lies in the automated, self-learning optimization of a physical flow chemistry setup operating in slug flow. The Applicant further states that the techniques described in the specification enable a physical flow chemistry setup to be optimized in an automated, self-learning manner by determining at least on process variable using at least one sensor of the flow chemistry setup, training at least one machine-learning model based on the measured process variable, determining a target parameter set by applying an optimizing algorithm to the trained machine-learning model, and providing the determined target parameter set for evaluating the flow chemistry setup and/or at least one flow chemistry product. The Applicant further states that thus, the claimed method does not recite an abstract idea in the abstract, but applies it in a concrete, technical manner to control and improve the operation of a tangible flow chemistry system, e.g., by adjusting physical process parameters such as the flow rate of at least one pump, temperature and reaction time, and that this constitutes a technical improvement to the operation of the physical flow chemistry setup itself and a particular, practical application of any purported judicial exception.
These arguments/remarks are not persuasive, because first, a claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception (MPEP 2106.04(d)). Second, as discussed in the above rejection, the independent claims provide additional elements to obtain ‘at least one process variable’, however once the data is received, the subsequent limitations only perform steps of training a machine learning model based on the process variable and using the trained machine learning model to determine a ‘target parameter set.’ However, once the ‘target parameter set’ has been determined, the subsequent step only recites ‘providing’ the ‘determined target parameter set’, and thus, the claims do not recite any limitations (i.e., additional elements) to which the ‘determined target parameter set’ (i.e., the result of the data analysis) is practically applied. Therefore, when all limitations in claims 1-15 have been considered as a whole (i.e., the analysis takes into consideration all the claim limitations and how those limitations interact and impact each other when evaluating whether the exception is integrated into a practical application), the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-15 are directed to an abstract idea (MPEP 2106.04(d)).
The Applicant states on page 8 (para. 2) of the Remarks that even assuming arguendo that it could be determined that the claims somehow are not integrated into a practical application under the second prong of Step 2A, the claims add significantly more than the judicial exception under Step 2B. The Applicant further states that in particular, the claims recite a specific, non-conventional ordered combination of elements: determining at least one process variable using at least one sensor of a physical flow chemistry setup, training at least one machine-learning model on that process variable, applying an optimizing algorithm to the trained model to determine a target parameter set, and providing the determined target parameter set for evaluating the flow chemistry setup and/or at least one flow chemistry product, that, when considered as a whole, amounts to significantly more than any purported abstract idea and provides a concrete technical improvement to the operation of a flow chemistry setup operating in slug flow. The Applicant further states that accordingly, the rejection of claims 1-15 under 35 U.S.C. 101 should be withdrawn.
These arguments/remarks are not persuasive, because first, at Step 2B of the eligibility analysis, only the additional elements identified at Step 2A Prong Two are carried over for further evaluation. Second, regarding the Applicant’s argument that “the claims recite a specific, non-conventional ordered combination of elements,” it is noted that the Applicant’s argument of a non-conventional ordered combination of elements mixes judicial exceptions (e.g., at least the limitations “training at least one machine-learning model on that process variable” and “applying an optimizing algorithm to the trained model to determine a target parameter set”) with additional elements, and as previously discussed, only additional elements are used in the evaluation at Step 2B to determine whether a claim amounts to significantly more than the judicial exceptions (i.e., whether the additional elements contribute an inventive concept). Third, as noted and discussed in the above rejection, when taken alone (i.e., individually), all additional elements in claims 1-15 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as an ordered combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-15 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
Claim Rejections - 35 USC § 103
The Applicant’s amendment received 20 July 2026 has been fully considered, however after further consideration, the rejection of claims 1-15 under 35 U.S.C. 103 as being unpatentable over Jensen in view of Schweidtmann et al. in the Office action mailed 20 April 2026 has been maintained in view of the amendment.
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.
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 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Jensen (“Flow Chemistry – Microreaction Technology Comes of Age.” American Institute of Chemical Engineers, 2017, vol. 63, no. 3, pp. 858-869, as cited in the Information Disclosure Statement (IDS) received 02 December 2022, and as cited in the Office action mailed 20 April 2026) in view of Schweidtmann et al. (“Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives.” Chemical Engineering Journal, 2018, vol. 352, pp. 277-282, as cited in the Office action mailed 20 April 2026).
Independent claims 1, 12, 13, and 14 encompass a system, CRM, and method for using a machine learning model for the self-optimization of a process variable in a continuous flow chemical reactor.
Dependent claims 2-11 and 15 further define the optimization method and/or equipment used in the continuous flow process and equipment.
Jensen teaches the current state-of-the-art of continuous flow technology in organic chemistry, and provides a highlight of the automation and optimization continuous flow microreaction technology.
Schweidtmann et al. teaches the use of multi-objective machine learning optimization algorithms for self-optimization of a continuous flow chemical reactor.
Regarding independent claims 1, 12, 13, and 14, and dependent claim 15, Jensen shows that automation and optimization are particularly promising applications of microreactor technology and shows examples of the use of segmented flow (i.e., slugs) to optimize process performance with respect to continuous variables (e.g., temperature, pressure, composition) and discrete parameters (e.g., solvents and catalysts) (page 858, col. 2, bottom, and page 859, col. 1, top); and further shows a continuous flow system for on-demand droplet preparation, reaction, analysis, and feedback in an automated reaction flow screening system that incorporates a computer with an optimization algorithm for in-line analysis and feedback optimization of discrete (e.g., catalyst, ligand, and solvent choices) and continuous variables (e.g., temperature, pressure, flow rate, and concentration) (Figure 2 and Figure 3); and further shows obtaining temperature and pressure measurements and controlling reagent flows for automated optimization in microreactor systems is a straightforward process, and that necessary auxiliary components such as valves, pumps, temperature and pressure sensors, and liquid handlers for reagents/products can be integrated with laboratory instrumentation software (page 861, col. 2, para. 3).
Regarding independent claims 1, 12, 13, and 14 and dependent claim 15, Jensen does not show training of at least one machine-learning model based on the process variable; or determining the target parameter set by applying an optimizing algorithm in terms of at least one optimization target on the trained machine-learning model.
Regarding independent claims 1, 12, 13, and 14 and dependent claim 15, Schweidtmann et al. shows methods for using a multi-objective machine learning algorithm applied to the self-optimization of a flow reactor that simultaneously targets reactor productivity and environmental objectives (Highlights; and Abstract); and the training of models within the algorithm (page 278, col. 2, para. 5).
Regarding dependent claims 2-11, Jensen further shows optimization with feedback of process information (e.g., reactant flows, reaction temperature, and outlet chemical composition) enables the iterative selection of experimental conditions where the most information is gained (claims 2 and 3) (page 861, col. 2, bottom); optimization of process conditions, and use of segmented flow to optimize process performance with respect to continuous variables (e.g., temperature, pressure, composition) and discrete parameters (e.g., solvents and catalysts) (claim 4) (page 859, col. 1, para. 1); a schematic diagram for on-demand droplet (i.e., slug of reagents) preparation, reaction, analysis, and feedback in an automated reaction flow screening system (Figure 2(b)) (claim 5); automated optimization with fast and accurate determination of chemical composition using, e.g., UV-visible spectroscopy, Raman spectroscopy, Fourier Transform InfraRed (FTIR) spectroscopy, mass spectrometry, benchtop NMR, on-line HPLC sampling and/or ultra performance liquid chromatography (UPLC) (861, col. 2, para. 3) (claims 6, 7, and 8); a reconfigurable system for on-demand continuous production and formulation of pharmaceutical compounds utilizing process control technology, i.e., automatic, real-time regulation of operating variables (temperature, pressure, flow rates) to maintain the system at an optimal state by using feedback loops and sensors to adjust parameters instantly to meet desired targets (Figure 3) (claims 9 and 10); and optimization of process parameters that can be varied continuously, such as temperature, pressure, flow rate, and concentration (page 862, col. 2, para. 2) (claim 11).
Therefore, 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 have modified the method shown by Jensen by incorporating methods for automated optimization of continuous flow reactor technology by using machine learning algorithms, as shown by Schweidtmann et al. and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Jensen with the methods of Schweidtmann et al., because Schweidtmann et al. shows methods for using a multi-objective machine learning algorithm applied to the self-optimization of a flow reactor that simultaneously targeted reactor productivity and environmental objectives. This modification would have had a reasonable expectation of success given that both Jensen and Schweidtmann et al. disclose methods for automation and optimization of continuous flow microreaction technology.
Response to Arguments
The Applicant’s arguments/remarks received 20 July 2026 have been fully considered, but are not persuasive.
The Applicant states on page 8 (bottom) that the Applicant traverses the rejection of claims 1-15 under 35 U.S.C. 103 as allegedly being obvious over Jensen in view of Schweidtmann, and further states that Jensen in view of Schweidtmann fails to teach or suggest at least a flow chemistry setup “for flow chemistry in slugs” and the automated, self-learning optimization thereof. The Applicant further states that Jensen is directed to continuous flow technology in organic chemistry and provides a highlight of the automation and optimization of continuous flow microreaction technology. The Applicant further states that the Office action admits that Jensen does not teach or suggest “training of at least on machine-learning model based on the process variable” or determining the target parameter set by applying an optimizing algorithm in terms of at least one optimization target on the trained machine-learning model. The Applicant further states on page 9 (para. 1) that the Office action relies on Schweidtmann to cure this deficiency, and further states that the Applicant disagrees. The Applicant further states (para. 2) that Schweidtmann is directed to the use of multi-objective machine-learning optimization algorithms for the self-optimization of a continuous flow chemical reactor, however the automated flow reactor setup used by Schweidtmann for applying its designed machine learning algorithm is not based on a slug flow chemistry setup. The Applicant further states that in fact, Schweidtmann fails to teach or suggest that the machine learning algorithm would work with flow chemistry in slugs, and accordingly, even if one of skill in the art were to combine Jensen with Schweidtmann as alleged in the Office action, they would not arrive at an algorithm to optimize a slug flow chemistry setup because slugs were not even considered when developing the Schweidtmann algorithm, and thus, the combination of Jensen and Schweidtmann fail to teach or suggest the claimed invention. The Applicant further states (para. 3) that furthermore, there would have been no reasonable expectation of success in arriving at the claimed invention from the proposed combination, and further states that as understood by one of skill in the art, there are unique challenges associated with slug flow chemistry that are neither recognized nor identified in the cited prior art, and as the present application explains, known slug flow setups were not configured for self-learning from data or for proposing new experiments. The Applicant further states that because neither Jensen nor Schweidtmann teaches or suggests flow chemistry in slugs, and neither addresses the unique challenges associated with slug flow, one of ordinary skill in the art would not have had a reasonable expectation of success in modifying or combining the cited references to achieve the automated, self-learning optimization of a slug flow chemistry setup as claimed, and similar reasoning can be applied to independent claim 14. Finally, the Applicant states (para. 4) that for at least these reasons, Jensen in view of Schweidtmann does not teach or suggest each and every limitation of the claimed invention and there is no reasonable expectation of success at arriving at the claimed invention based on their teachings.
These arguments/remarks are not persuasive, because first, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Second, as discussed in the above rejection, Jensen shows that automation and optimization are particularly promising applications of microreactor technology and shows examples of the use of segmented flow (i.e., slugs) to optimize process performance with respect to continuous variables (e.g., temperature, pressure, composition) and discrete parameters, and Schweidtmann shows the application of a machine learning global multi-objective optimization algorithm for the self-optimization of reaction conditions in a continuous flow chemistry reactor. Thus, 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 have modified the method shown by Jensen by incorporating methods for automated optimization of continuous flow reactor technology by using machine learning algorithms, as shown by Schweidtmann et al. and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Jensen with the methods of Schweidtmann et al., because Schweidtmann et al. shows methods for using a multi-objective machine learning algorithm applied to the self-optimization of a flow reactor that simultaneously targeted reactor productivity and environmental objectives. This modification would have had a reasonable expectation of success given that both Jensen and Schweidtmann et al. disclose methods for automation and optimization of continuous flow microreaction technology.
Conclusion
No claims are allowed.
THIS ACTION IS MADE FINAL. 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.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEVEN W. BAILEY whose telephone number is (571)272-8170. The examiner can normally be reached Mon - Fri. 1000 - 1800.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, KARLHEINZ SKOWRONEK can be reached at (571) 272-9047. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/S.W.B./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
