DETAILED ACTION - RTP
Notice to Applicant
1. The following is a NON-FINAL Office action upon examination of application number 18/622,159 filed on 03/29/2024. Claims 1-20 are pending in this application and have been examined on the merits discussed below.
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
3. The information disclosure statement (IDS) filed on 04/25/2024 has been acknowledged. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112
4. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
5. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
6. Claims 1 and 11 recite “wherein the one set, among the multiple sets, of microbial test results is obtained...” The limitation “the one set” lacks antecedent basis and therefore renders the claim indefinite. While claims 1/11 introduce “multiple sets,” claims 1/11 do not introduce “one set.” Appropriate correction is required.
7. Claims 1 and 11 recite “wherein the test attributes include: key information.” The phrase “key information” is ambiguous because “key” is a relative term. There is no objective basis or standard provided for determining whether the information is key information. Therefore, the claims are rendered indefinite. Appropriate correction is required.
8. Claims 13-18 recite “The method according to claim 11...” However, claim 11 is a system claim. Claims 13-18 (method claims) depend on claim 11 (a system claim). Accordingly, claims 13-18 are in improper dependent form. It is unclear whether claim 13-18 intend to recite “The method according to claim 1” or “The system according to claim 11,” thus rendering the claims indefinite. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements. Appropriate correction is required.
9. All claims dependent from above rejected claims are also rejected due to dependency.
Claim Rejections - 35 USC § 101
10. 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.
11. Claims 1-20 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without significantly more. The eligibility analysis in support of these findings is provided below, in accordance with MPEP 2106.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the claimed method (claims 1-10, 13-20) and system (claims 11-12) are directed to at least one of the eligible categories of subject matter under §101 (process and machine, respectively). Accordingly, claims 1-20 satisfy Step 1 of the eligibility inquiry.
With respect to Step 2A Prong One, it is next noted that the claims recite an abstract idea that falls into the “Certain Methods of Organizing Human Activity” abstract idea set forth in MPEP 2106 because the claims recite steps that can be performed in the human mind (including observation, evaluation, judgment, opinion), and therefore fall under the “Mental Processes” abstract idea grouping. With respect to independent claim 1, the limitations reciting the abstract idea are indicated in bold below: receiving multiple sets of microbial test results and test attributes related to the multiple sets of microbial test results, wherein the one set, among the multiple sets, of microbial test results is obtained from at least one testing device that each performs a different microbial testing method on samples collected at process points of interest in a microbial process; grouping the multiple sets of microbial test results to prepare fingerprints that each represent a different group of microbial test results, wherein the test attributes include: key information that identifies a fingerprint; a manufacturing line ID that identifies the microbial process; a process ID that identifies a purpose of each microbial test; and a test property that identifies a type of each test; in association with the key information of a particular fingerprint, storing the particular fingerprint in a fingerprint library created in a database; and in response to a request to retrieve the particular fingerprint stored in a database that contains other fingerprints, searching the fingerprint library in the database for the particular fingerprint using the key information contained in the request. These steps can be accomplished mentally via human evaluation or judgment even if aided with pen and paper, and thus fits within the “Mental Processes” abstract idea grouping. The claim recites limitations related to collecting, categorizing, storing, and retrieving information based on identifying attributes, which are steps that can be performed by a person using mental judgment or with pen and paper. Therefore, because the limitations above set forth activities falling within the “Mental Processes” abstract idea grouping described in MPEP 2106, the additional elements recited in the claims are further evaluated, individually and in combination, under Step 2A Prong Two and Step 2B below.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The additional elements are: at least one testing device and a database (claim 1), the computer system, at least one testing device, and a database (claim 11). These additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or computer-executable instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment. See MPEP 2106.05(f) and 2106.05(h). Furthermore, these additional elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.”). Even if the step for receiving and extracting steps are evaluated as additional elements, these activities encompass, at most, insignificant extra-solution activity, which is not indicative of a practical application, as noted in MPEP 2106.05(g), and is not enough to add significantly more since it is well-understood and conventional activity, as noted in MPEP 2106.05(d)
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements are: at least one testing device and a database (claim 1), the computer system, at least one testing device, and a database (claim 11). The additional elements have been fully considered, but fail to add significantly more because they merely serve to tie the invention to a particular operating environment (i.e., computer-based implementation) by describing the use of generic computing elements to implement the claimed invention, though at a very high level of generality and without imposing meaningful limitation on the scope of the claim, similar to simply saying "apply it” or “apply it using a general purpose computer,” which is not enough to transform an abstract idea into eligible subject matter. Notably, Applicant’s Specification describes generic off-the-shelf computing elements for implementing the claimed invention and suggests that virtually any generic computing devices could be used to implement the invention (See, e.g., Specification paragraph [0092]). Therefore, these additional elements describe generic computing elements that merely serve to tie the abstract idea to a particular operating environment, which does not add significantly more to the abstract idea. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976. Even if the receiving step is not deemed part of the abstract idea, this step is at most directed to insignificant extra-solution activity, which has been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
With respect to the “extracting” step, even if considered as an additional element, when evaluated under Step 2A Prong Two and Step 2B, amounts to insignificant extra-solution activity, which does not amount to a practical application (MPEP 2106.05(g)), nor add significantly more because such activity has been recognized as well-understood, routine, and conventional and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d). “The courts have recognized the following computer functions 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: iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; v. Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition).” See MPEP 2106.05(d).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
Dependent claims 2-10 and 12-20 recite the same abstract idea as recited in the independent claims, and when evaluated under Step 2A Prong One of the eligibility inquiry, merely recite further details of the same abstract idea recited in the independent claims accompanied by, at most, the involvement of the same generic computing elements as the independent claims which, as noted above, are not sufficient to amount to a practical application or significantly more than the abstract idea itself. In particular, dependent claims 2-10 recite “wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to batches of products produced by the microbial process, wherein the key information comprises different key information for each of the batches of the products,” “wherein grouping the multiple sets of microbial test results comprises grouping two sets of microbial test results differently where the two sets of microbial test results are obtained from two different microbial processes, respectively, wherein the key information comprises different key information for the two sets of microbial test results,” “wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to lots of products produced by the microbial process, wherein the key information comprises different key information for each of the lots of the products,” “wherein the fingerprint uniquely identifies a product produced by the microbial process with at least one of (i) a batch number of the product, (ii) a lot number of the product or (iii) a production year of the product,” “wherein the fingerprint includes chronological information representative of a timeline of a plurality of tests performed at different points in time during a single step of interest in the microbial process,” “wherein the manufacturing line ID includes at least one of (i) an industry standard description related to the microbial process, (ii) a process location where the microbial process is performed, or (iii) a facility where the microbial process is performed,” “wherein the fingerprint is associated with auxiliary information that includes at least one of (i) a quality of a product produced by the microbial process, (ii) conditions under which the microbial process is performed or (iii) a process adjustment that includes at least one of a process control, a process optimization or a troubleshooting that is taken during the microbial process,” “wherein the multiple sets of microbial test results include results of tests performed in the microbial process for producing one of a wine product, a beer product or a spirit product,” “wherein the multiple sets of microbial test results include results of tests performed in the microbial process for wastewater treatment,” “wherein grouping the multiple sets of microbial test results comprises grouping two sets of microbial test results differently where the two sets of microbial test results are obtained from two different microbial processes, respectively, wherein the key information comprises different key information for the two sets of microbial test results,” “wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to lots of products produced by the microbial process, wherein the key information comprises different key information for each of the lots of the products,” “wherein the fingerprint uniquely identifies a product produced by the microbial process with at least one of (i) a batch number of the product, (ii) a lot number of the product or (iii) a production year of the product,” “wherein the fingerprint includes chronological information representative of a timeline of a plurality of tests performed at different points in time during a single step of interest in the microbial process,” “wherein the manufacturing line ID includes at least one of (i) an industry standard description related to the microbial process, (ii) a process location where the microbial process is performed, or (iii) a facility where the microbial process is performed,” “wherein the fingerprint is associated with auxiliary information that includes at least one of (i) a quality of a product produced by the microbial process, (ii) conditions under which the microbial process is performed or (iii) a process adjustment that includes at least one of a process control, a process optimization or a troubleshooting that is taken during the microbial process,” “wherein the multiple sets of microbial test results include results of tests performed in the microbial process for producing one of a wine product, a beer product or a spirit product,” “wherein the multiple sets of microbial test results include results of tests performed in the microbial process for wastewater treatment,” however, these claims also set forth steps falling within the same Mental Processes abstract idea grouping recited in the independent claim. The additional elements recited in the dependent claims are recited at a high level of generality and fails to yield any discernible improvement to the computer or to any technology, nor set forth any additional function or result that provided meaningful limitation beyond linking the abstract idea to a particular technological environment (i.e., automated/computing environment), and thus fail to integrate the abstract idea into a practical application. When evaluated under Step 2A Prong Two and Step 2B, the additional elements do not amount to a practical application or significantly more since they merely require generic computing devices (or computer-implemented instructions/code) which as noted in the discussion of the independent claims above is not enough to render the claims as eligible.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself.
For more information, see MPEP 2106.
Claim Rejections - 35 USC § 103
12. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
13. 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.
14. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
15. Claims 1, 3, 6-11, 13, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wilkes et al. Pub. No.: US 2002/0138210 A1, [hereinafter Wilkes], in view of Dillon et al., Pub. No.: WO 2015/171834 A1, [hereinafter Dillon].
As per claim 1, Wilkas teaches a method for preparing a quality assurance and quality control report on microbial process, the method (paragraphs 0002, 0068) comprising:
receiving multiple sets of microbial test results and test attributes related to the multiple sets of microbial test results, wherein the one set, among the multiple sets, of microbial test results is obtained from at least one testing device that each performs a different microbial testing method on samples collected (paragraph 0031: “Consider a data set comprised of 30 samples, 3 each from ten groups (such as ten different bacterial strains), in which each sample is represented by 800 original measurement variables; paragraph 0160, discussing that a FAME (Fatty Acid Methyl Ester) chromatogram (or a plurality of chromatograms averaged together) is obtained and the individual FAMEs are identified, quantified, and recorded as the database session for each species or strain of microorganism. A second set of authentic samples are grown on another growth medium, such as a selective growth medium, and the results of the FAME analysis on each of the strains or species are recorded as the sampling session. All of the sampling session data is transformed to the database session...Principal component analysis (PCA) or another similar multivariate analysis is performed, treating the database and sampling session microorganisms as two different species. Those species or strains that have similar vectors between the sampling and database session results are grouped together to form a set of metabolically similar microorganisms (metabolic similarity group). One representative of each of these metabolic similarity groups is then cultured on the same growth medium as the unknown and analyzed concurrently with the unknown to yield a set of chromatographic data; paragraphs 0052, 0053, 0118);
grouping the multiple sets of microbial test results to prepare fingerprints that each represent a different group of microbial test results, wherein the test attributes include: key information that identifies a fingerprint; and a test property that identifies a type of each test (paragraph 0032, discussing that CVs (Canonical variate) reflect the identity of separate groups of samples in the data set. The first CV vector is calculated as a linear combination of selected PCs that maximizes the variance between distinct groups of data. The 2nd CV, orthogonal to the first, is based on residual variance not incorporated into the 1st CV. In a particular data set, the maximum number of CVs is one less than the number of distinct groups. Each sample in a data set will have a co-ordinate (called a score) associated with each CV. Therefore, the sample can be located on a 2-dimensional CV Score Plot using the two co-ordinates of the two selected CVs. Samples having similar scores appear near each other on the CV score plot. Samples from different groups may have similar scores in the first two CVs but different scores in the higher number CV space. Therefore, in using CV vectors to identify metabolically similar microorganisms, the number of groups of microorganisms examined on a single plot may be three to six, rather than ten to twenty, to enable visual examination while incorporating most of the significant available variance; paragraph 0160, discussing that the unknown microorganism's chromatographic data may be transformed to its expected library equivalent using a transformation algorithm derived for the representative of a metabolic similarity group that exhibits sampling session chromatographic data that falls closest to the unknown's sampling session chromatographic data in canonical variate or principal component space. The transformation algorithm would be derived from the closest representative's sampling session and library database chromatographic data by dividing the library database chromatographic data by the sampling session chromatographic data to yield a set of ratios);
in association with the key information of a particular fingerprint, storing the particular fingerprint in a fingerprint library created in a database (paragraph 0065, discussing that the discovery that corrections used to transform one microorganism's fingerprint spectrum can be applied to metabolically similar microorganisms makes it possible to construct a coherent library database of fingerprint spectra (i.e., a database where fingerprint spectra of microorganisms can be used to identify microorganisms and additional fingerprint spectra of microorganisms may be added to the database, even though they are not measured under identical instrumental and environmental conditions). For example, fingerprint spectra of new strains of E. coli that are cultured on a particular growth medium may be added to the database (established using a different growth medium) at any time; paragraph 0066, discussing that the discovery also makes it possible to measure fingerprint spectra of unknown microorganisms concurrently with only a few reference microorganisms (genus, species or strains) rather than a reference for each of the microorganisms that may be found in a particular sample. For example, by choosing sets of reference microorganisms that include representatives of each of the groups of metabolically similar microorganisms that presumably may be found in a particular sample, the need to concurrently measure fingerprint spectra of all the microorganisms that might possibly be within the particular sample is obviated and time and effort are saved. Alternatively, including only the major anticipated pathogenic strains as references may reduce the number of reference species required for spectral transformation. In this case, when an unknown microorganism does not appear to have an appropriate, metabolically similar reference on which to base a transformation it is probably not toxicologically significant. Once one or more appropriate, metabolically similar reference microorganism are identified, their spectra may be used to generate transformation algorithms that may then be applied to the fingerprint spectra of metabolically similar unknown microorganisms to generate expected fingerprint spectra for the unknown microorganisms. Such transformed fingerprint spectra represent fingerprint spectra the unknowns would be expected to exhibit if the unknowns had actually been grown on the library database growth medium. Such transformed fingerprint spectra may then be directly compared to database fingerprint spectra for identification of the unknown microorganisms; paragraph 0075, discussing that a quantitative measure of vector similarity may be based on the quality of the result: an identification using transformed spectra correctly assigns the highest probability of class identity to the proper library bacterium. For any database, a standard of performance is that the unknown spectrum be most similar to that of the correct bacterium...; paragraph 0077, discussing that during construction of the database, a large batch of non-selective growth medium such as TSA would typically be purchased and preserved for future use as the library database growth medium so that as new microorganisms are isolated and become available they may be cultured and have their library database fingerprint spectra determined. By using the same batch of growth medium for all database fingerprint spectra, variations in the fingerprint spectra due to differences in the nutrient profile between batches is eliminated. However, before entering each fingerprint spectrum into the database, fingerprint spectra using the standard TSA, even if obtained on different instruments or on the same, re-tuned instrument, are transformed to an expected spectrum under arbitrarily specified standard conditions using a spectral compensation algorithm based upon an appropriate reference microorganism; paragraph 0079, discussing that the disclosed methods may also be used to add new microorganisms to the library database even after the preserved batch of library database growth medium is exhausted. In this situation, compensation to the database conditions may be performed based on the fingerprint spectra of metabolically similar microorganisms already in the database as follows. The new microorganism and a representative microorganism from each of the metabolically similar groups identified in the library database are grown both on a selective growth medium and the new batch of library database growth medium. Fingerprint spectra are measured for each microorganism grown on the two growth media. The fingerprint spectra are analyzed by pattern recognition to generate principal components and canonical variates. Vectors are determined between the fingerprint spectra of each microorganism grown on the two growth media. The representative of a metabolically similar group within the library database with a vector that is most similar to the vector determined for the new microorganism is chosen to serve as the basis of compensation for the new microorganism. Once the most similar representative of a metabolically similar group of microorganisms is determined, its fingerprint spectrum from the new batch of library database growth medium is compared to its fingerprint spectrum from the preserved batch of library database growth medium that is now exhausted. The differences between these two fingerprint spectra are used to transform the fingerprint spectrum of the new microorganism into an expected fingerprint spectrum of the new microorganism. The expected fingerprint spectrum represents how the new microorganism's fingerprint spectrum might have looked if it had been measured after growth on the preserved, but now exhausted, library database growth medium. This transformed fingerprint spectrum then is entered into the library database as the new microorganism's library fingerprint spectrum); and
searching the fingerprint library in the database for the particular fingerprint using the key information contained in the request (paragraph 0066, discussing that the discovery also makes it possible to measure fingerprint spectra of unknown microorganisms concurrently with only a few reference microorganisms (genus, species or strains) rather than a reference for each of the microorganisms that may be found in a particular sample. For example, by choosing sets of reference microorganisms that include representatives of each of the groups of metabolically similar microorganisms that presumably may be found in a particular sample, the need to concurrently measure fingerprint spectra of all the microorganisms that might possibly be within the particular sample is obviated and time and effort are saved. Alternatively, including only the major anticipated pathogenic strains as references may reduce the number of reference species required for spectral transformation. In this case, when an unknown microorganism does not appear to have an appropriate, metabolically similar reference on which to base a transformation it is probably not toxicologically significant. Once one or more appropriate, metabolically similar reference microorganism are identified, their spectra may be used to generate transformation algorithms that may then be applied to the fingerprint spectra of metabolically similar unknown microorganisms to generate expected fingerprint spectra for the unknown microorganisms. Such transformed fingerprint spectra represent fingerprint spectra the unknowns would be expected to exhibit if the unknowns had actually been grown on the library database growth medium. Such transformed fingerprint spectra may then be directly compared to database fingerprint spectra for identification of the unknown microorganisms; paragraph 0085, discussing that the transformed fingerprint spectrum for the unknown may then be compared to spectra in the library database to identify the microorganism. This step can be done using RESolve, Statistica, Pirouette, or any other pattern recognition program, including an artificial neural network. The program makes a comparison between the pattern exhibited by the transformed fingerprint spectrum of the unknown and the patterns exhibited by fingerprint spectra for known microorganisms that are stored in the library. The unknown microorganism may be identified as being of the same type as the known microorganism exhibiting the most similar database fingerprint spectrum…; paragraph 0106, discussing that the operator of the fingerprint spectral instrument would run all the references for the day and then transform his complete reference library to a database-for-the-day (or the subset likely needed). Once a clinical sample arrives for analysis, the operator measures a fingerprint spectrum, compares its raw spectrum to the library spectra to determine the rough class to which it belongs, transforms it with the appropriate transform vector, and compares this spectrum to database-for-the-day to identify the microorganism).
While Wilkes teaches collecting samples, Wilkes does not explicitly teach samples collected at process points of interest in a microbial process; wherein the test attributes include: a manufacturing line ID that identifies the microbial process; and a process ID that identifies a purpose of each microbial test; and in response to a request to retrieve the particular fingerprint stored in a database that contains other fingerprints, searching the fingerprint library in the database for the particular fingerprint using the key information contained in the request. However, Dillon in the analogous art of systems for monitoring and managing a facility microbiome
teaches these concepts. Dillon teaches:
samples collected at process points of interest in a microbial process (paragraph 0059, discussing that change in the facility's microbiome is determined by comparing results from multiple samples obtained during a sampling period from the same facility (same or different locations) or from similar or selected diverse facilities. In many embodiments, samples are collected two or more times over the course of a sampling period. The frequency of sample collection may be hourly, daily, monthly, yearly, or any combination thereof and will vary depending on the facility and the intended purpose of the monitoring; paragraph 0074, discussing that following the sampling period, the passive samplers are collected and the target molecules are collected from the sampling devices…; paragraph 0082, discussing that once samples are obtained, they are analyzed in accordance with the instant invention to provide a characterization of the microbiome; paragraph 0096, discussing that in some instance, up to 10 million samples per hour are screened; paragraph 0097, discussing that in at least one embodiment, microbiome samples are collected and initially analyzed via a high-throughput screening system. After a period of time, microbiome samples are again collected and analyzed via the high-throughput screening system. The microbiome sample data is then processed by the high-throughput screening system to detect changes in the microbiome…; paragraph 0146);
wherein the test attributes include: a manufacturing line ID that identifies the microbial process; and a process ID that identifies a purpose of each microbial test (paragraph 0059, discussing that change in the facility's microbiome is determined by comparing results from multiple samples obtained during a sampling period from the same facility (same or different locations) or from similar or selected diverse facilities. In many embodiments, samples are collected two or more times over the course of a sampling period. The frequency of sample collection may be hourly, daily, monthly, yearly, or any combination thereof and will vary depending on the facility and the intended purpose of the monitoring; paragraph 0061, discussing that carious sampling methods may be used to collect target molecules. In some instances, a sampling method is selected based upon the specific characteristics of the facility from which the target molecules are being collected…More disruptive sampling methods, such as high- volume vacuum pump air collection, are more appropriate in manufacturing facilities where excessive noise is acceptable; paragraph 0062, discussing that in some instances, a sampling method is selected based upon desired data or analysis parameters. For example, tracking known pathogens on hospital surfaces can be accomplished by collecting surface swabs, while monitoring airborne microbiome dynamics in an office environment requires air sampling, which may be continuous or intermittent, depending on the application. As another example, identifying allergens in the airborne microbiome requires collecting dry microbes, as on a dry vacuum filter, because microbial viability is not necessary for allergenicity. On the other hand, collecting data on live pathogens in an operating room requires information about microbial viability, and thus collection, at least for certain embodiments, must preserve cells in their current form, as in a preservative liquid. Additionally, when indoor air quality is being considered, simultaneous collection of non-biological environmental parameters may be important, such as particulate matter, VOC concentration and content; paragraph 0083, discussing that sequencing of RNA can be used as an indicator of viability of the cells and so to determine cell viability at the time of sampling, as well as determining which biochemical activities are present at the sample location; paragraph 0132, discussing that the data collected regarding performance indicators is correlated with the facility microbiome and changes in the facility microbiome in accordance with certain aspects of the invention. This correlation can be within a given facility, across facility types, or across all facilities of a particular user. The correlation can be used in accordance with the invention to alter facility operation parameters in a way that increases facility performance; paragraph 0153); and
in response to a request to retrieve the particular fingerprint stored in a database that contains other fingerprints, searching the fingerprint library in the database for the particular fingerprint using the key information contained in the request (paragraph 0098, discussing that in some instances, a microbial profile of a microbiome, a form of microbiome characterization, is determined and monitored over time through sampling and DNA typing or profiling. Sampling may be accomplished by any known method in the art. For example, and as described in detail above, in some instances sampling is achieved by swabbing one or more surfaces of the microbiome with sterile cotton swabs. In other instances, sampling is achieved through the use of various sensors strategically placed within the facility and configured to detect or collect one or more indicator taxa. Further, in some instances sampling is achieved through the collection of product samples, water samples, air samples, soil samples and/or biological samples that may comprise one or more indicator taxa. In some instances using mobile sequencing, the sequence data is transmitted to a server location where the sequence data is compared to a reference database; paragraph 0099, discussing that under conditions where a certain gene or genetic signature pattern observed by the mobile sequencing device matches a predetermined pattern in the database, an instruction or set of instructions on altering one or more facility operating parameters may be sent to the facility; paragraph 0102, discussing that his is the first generation of such near-real-time sequencing technology and anticipated improvements will simply make the methods of the present invention easier and more cost efficient to implement. As an example, a wall-mounted device can be programmed in accordance with the invention to detect a suite of indoor microbial agents or biochemical activities (as determined by comparison of samples to a set of predetermined sequences in a reference database)).
Wilkes is directed towards database methods for identifying microorganisms. Dillon is directed towards systems for monitoring and managing a facility microbiome. Therefore they are deemed to be analogous as they both are directed towards microbiome monitoring systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wilkes with Dillon because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying Wilkes to include Dillon’s features for including samples collected at process points of interest in a microbial process, wherein the test attributes include: a manufacturing line ID that identifies the microbial process and a process ID that identifies a purpose of each microbial test, and in response to a request to retrieve the particular fingerprint stored in a database that contains other fingerprints, searching the fingerprint library in the database for the particular fingerprint using the key information contained in the request, in the manner claimed, would serve the motivation of allowing facilities operations to be conducted more safely, efficiently, and cost-effectively by monitoring changes in the facility microbiome and intervening when those changes indicate the likelihood of a deleterious effect therefrom (Dillon, abstract); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 3, the Wilkes-Dillon combination teaches the method according to claim 1. Wilkes further teaches wherein grouping the multiple sets of microbial test results comprises grouping two sets of microbial test results differently where the two sets of microbial test results are obtained from two different microbial processes, respectively, wherein the key information comprises different key information for the two sets of microbial test results (paragraph 0006, discussing hypothetical fingerprint spectra for three different microorganisms cultured on two different growth media. Also shown are transformed fingerprint spectra for each microorganism that were produced using a correction algorithm derived from the relationship between the fingerprint spectra of the reference microorganism grown on the two different growth media; paragraph 0054, discussing application of a relationship between two fingerprint spectra (or portions thereof) measured under two different sets of conditions (environmental and/or instrumental), in order to convert one fingerprint spectrum to the other, is referred to as the act of transformation. Transformation also includes the act of applying a relationship derived between two fingerprint spectra of one microorganism to fingerprint spectra of other microorganisms; paragraph 0065, discussing that the discovery that corrections used to transform one microorganism's fingerprint spectrum can be applied to metabolically similar microorganisms makes it possible to construct a coherent library database of fingerprint spectra (i.e., a database where fingerprint spectra of microorganisms can be used to identify microorganisms and additional fingerprint spectra of microorganisms may be added to the database, even though they are not measured under identical instrumental and environmental conditions). For example, fingerprint spectra of new strains of E. coli that are cultured on a particular growth medium may be added to the database (established using a different growth medium) at any time; paragraph 0077).
As per claim 6, the Wilkes-Dillon combination teaches the method according to claim 1. Although not explicitly taught by Wilkes, Dillon in the analogous art of systems for monitoring and managing a facility microbiome teaches wherein the fingerprint includes chronological information representative of a timeline of a plurality of tests performed at different points in time during a single step of interest in the microbial process (paragraph 0004, discussing methods for correlating a facility microbiome with one or more facility operation parameters, said method comprising (i) characterizing the facility microbiome over a period of time; (ii) characterizing a facility operating parameter over said period of time and comparing it to the characterization of the facility microbiome; and (iii) identifying any changes in said facility microbiome that correlate with changes in the facility operating parameter; paragraph 0058, discussing that the microbiome of a facility is characterized at a point in time or during a period of time or monitored for changes over time or monitored with changes intended to alter the microbiome being implemented contemporaneously. In some instances, the microbiome is monitored for a period of time lasting from minutes to more than a year. In one embodiment, a microbiome is monitored for 24 hours. In one embodiment, a microbiome is monitored for three to seven days. In one embodiment, a microbiome is monitored for one to three months. In one embodiment, a microbiome is monitored for an extended period of time, such as for a period exceeding a year…; paragraph 0059, discussing that change in the facility's microbiome is determined by comparing results from multiple samples obtained during a sampling period from the same facility (same or different locations) or from similar or selected diverse facilities. In many embodiments, samples are collected two or more times over the course of a sampling period. The frequency of sample collection may be hourly, daily, monthly, yearly, or any combination thereof and will vary depending on the facility and the intended purpose of the monitoring; paragraphs 0096, 0175).
Wilkes is directed towards database methods for identifying microorganisms. Dillon is directed towards systems for monitoring and managing a facility microbiome. Therefore they are deemed to be analogous as they both are directed towards microbiome monitoring systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wilkes with Dillon because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying Wilkes to include Dillon’s feature for including wherein the fingerprint includes chronological information representative of a timeline of a plurality of tests performed at different points in time during a single step of interest in the microbial process, in the manner claimed, would serve the motivation of allowing facilities operations to be conducted more safely, efficiently, and cost-effectively by monitoring changes in the facility microbiome and intervening when those changes indicate the likelihood of a deleterious effect therefrom (Dillon, abstract); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 7, the Wilkes-Dillon combination teaches the method according to claim 1. Although not explicitly taught by Wilkes, Dillon in the analogous art of systems for monitoring and managing a facility microbiome teaches wherein the manufacturing line ID includes at least one of (i) an industry standard description related to the microbial process, (ii) a process location where the microbial process is performed, or (iii) a facility where the microbial process is performed (paragraph 0003, discussing methods for characterizing a facility microbiome, said method comprising: (i) collecting samples from a variety of locations in said facility; paragraph 0032, discussing that the food processing facility may be characterized based on various physical aspects of the facility; paragraph 0059, discussing that change in the facility's microbiome is determined by comparing results from multiple samples obtained during a sampling period from the same facility (same or different locations) or from similar or selected diverse facilities. In many embodiments, samples are collected two or more times over the course of a sampling period. The frequency of sample collection may be hourly, daily, monthly, yearly, or any combination thereof and will vary depending on the facility and the intended purpose of the monitoring; paragraph 0061, discussing that carious sampling methods may be used to collect target molecules. In some instances, a sampling method is selected based upon the specific characteristics of the facility from which the target molecules are being collected…More disruptive sampling methods, such as high- volume vacuum pump air collection, are more appropriate in manufacturing facilities where excessive noise is acceptable; paragraph 0062, discussing that in some instances, a sampling method is selected based upon desired data or analysis parameters…; paragraph 0083, discussing determining which biochemical activities are present at the sample location; paragraph 0132, discussing that the data collected regarding performance indicators is correlated with the facility microbiome and changes in the facility microbiome in accordance with certain aspects of the invention. This correlation can be within a given facility, across facility types, or across all facilities of a particular user. The correlation can be used in accordance with the invention to alter facility operation parameters in a way that increases facility performance).
Wilkes is directed towards database methods for identifying microorganisms. Dillon is directed towards systems for monitoring and managing a facility microbiome. Therefore they are deemed to be analogous as they both are directed towards microbiome monitoring systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wilkes with Dillon because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying Wilkes to include Dillon’s feature for including wherein the manufacturing line ID includes at least one of (i) an industry standard description related to the microbial process, (ii) a process location where the microbial process is performed, or (iii) a facility where the microbial process is performed, in the manner claimed, would serve the motivation of allowing facilities operations to be conducted more safely, efficiently, and cost-effectively by monitoring changes in the facility microbiome and intervening when those changes indicate the likelihood of a deleterious effect therefrom (Dillon, abstract); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 8, the Wilkes-Dillon combination teaches the method according to claim 1. Although not explicitly taught by Wilkes, Dillon in the analogous art of systems for monitoring and managing a facility microbiome teaches wherein the fingerprint is associated with auxiliary information that includes at least one of (i) a quality of a product produced by the microbial process, (ii) conditions under which the microbial process is performed or (iii) a process adjustment that includes at least one of a process control, a process optimization or a troubleshooting that is taken during the microbial process (paragraph 0030, discussing data analysis methodology and data analytics that can quantify system performance by characterizing the microbiome of a built environment (BE) to produce actionable information that enables the owner/operator to optimize system design and operations and so improve system performance; paragraph 0032, discussing that the characterization data is used to determine one or more optimization steps that may be employed to improve the performance and characterization of the microbiome of the food processing BE; paragraph 0064, discussing that surfaces can be sampled to assess the quality, type, identity, metabolic profile, allergenicity, and gene content of various target molecules, such as, for instance, microbial cells. Surface samples may be obtained from any surface having a surface area of sufficient size from which to collect the sample; claim 19: “wherein the facility operation parameters are modified to optimize facility performance on an ongoing basis as sequence data is obtained from the samples”; paragraph 0191).
Wilkes is directed towards database methods for identifying microorganisms. Dillon is directed towards systems for monitoring and managing a facility microbiome. Therefore they are deemed to be analogous as they both are directed towards microbiome monitoring systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wilkes with Dillon because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying Wilkes to include Dillon’s feature for including wherein the fingerprint is associated with auxiliary information that includes at least one of (i) a quality of a product produced by the microbial process, (ii) conditions under which the microbial process is performed or (iii) a process adjustment that includes at least one of a process control, a process optimization or a troubleshooting that is taken during the microbial process, in the manner claimed, would serve the motivation of allowing facilities operations to be conducted more safely, efficiently, and cost-effectively by monitoring changes in the facility microbiome and intervening when those changes indicate the likelihood of a deleterious effect therefrom (Dillon, abstract); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 9, the Wilkes-Dillon combination teaches the method according to claim 1. Although not explicitly taught by Wilkes, Dillon in the analogous art of systems for monitoring and managing a facility microbiome teaches wherein the multiple sets of microbial test results include results of tests performed in the microbial process for producing one of a wine product, a beer product or a spirit product (paragraph 0049, discussing that breweries and wineries are beverage processing factory facilities that perform controlled microbial fermentation to manufacture beer, wine, distilled spirits, and/or herbal or tea-based drinks such as kombucha. These types of factory facilities are also susceptible to microbial contaminations and reductions in performance. For example, in some instances microbial contaminations result in the production of product that fails to meet desired or legally required specifications. These batches are thus unusable and result in lost profits. Non-limiting examples of performance reducing microbes include those identified above, as well as naturally occurring microbes present within the produced food or beverage).
Wilkes is directed towards database methods for identifying microorganisms. Dillon is directed towards a systems for monitoring and managing a facility microbiome. Therefore they are deemed to be analogous as they both are directed towards microbiome monitoring systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wilkes with Dillon because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying Wilkes to include Dillon’s feature for including wherein the multiple sets of microbial test results include results of tests performed in the microbial process for producing one of a wine product, a beer product or a spirit product, in the manner claimed, would serve the motivation of allowing facilities operations to be conducted more safely, efficiently, and cost-effectively by monitoring changes in the facility microbiome and intervening when those changes indicate the likelihood of a deleterious effect therefrom (Dillon, abstract); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 10, the Wilkes-Dillon combination teaches the method according to claim 1. Although not explicitly taught by Wilkes, Dillon in the analogous art of systems for monitoring and managing a facility microbiome teaches wherein the multiple sets of microbial test results include results of tests performed in the microbial process for wastewater treatment (paragraph 0001: “The present invention provides methods and materials for monitoring and managing the microbiome of a facility and so relates to the fields of microbiology, molecular biology, indoor air quality, occupant health, and facilities management.”; paragraph 0019, discussing that the term "facility," as used herein, refers to a non-naturally occurring structure. In many embodiments, the facility will provide an area for human activity. Facilities therefore include, without limitation, buildings, and vehicles. Buildings include factories, residential structures and hospitals. Vehicles include airplanes, buses, cars, ships, trucks, and vans. A facility can also be a municipality, such as a city or urban area containing a collection of man-made structures that host a microbiome in different areas such as sewers, water supplies, and air in public areas).
Wilkes is directed towards database methods for identifying microorganisms. Dillon is directed towards a systems for monitoring and managing a facility microbiome. Therefore they are deemed to be analogous as they both are directed towards microbiome monitoring systems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wilkes with Dillon because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying Wilkes to include Dillon’s feature for including wherein the multiple sets of microbial test results include results of tests performed in the microbial process for wastewater treatment, in the manner claimed, would serve the motivation of allowing facilities operations to be conducted more safely, efficiently, and cost-effectively by monitoring changes in the facility microbiome and intervening when those changes indicate the likelihood of a deleterious effect therefrom (Dillon, abstract); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 11 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 1, as discussed above. Further, as per claim 11 the Wilkes-Dillon combination teaches a computer system for preparing a quality assurance and quality control report on microbial process, the computer system being programed to (Wilkes, paragraph 0021: “a computer system that can be used to implement the disclosed methods.”; paragraph 0178).
Claim 13 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 3, as discussed above.
Claim 16 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 6, as discussed above.
Claim 17 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 7, as discussed above.
Claim 18 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 8, as discussed above.
Claim 19 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 9, as discussed above.
Claim 20 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 10, as discussed above.
16. Claims 2, 4, 12, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Wilkes et in view of Dillon, in further view of Zhao et al., Pub. No.: US 2024/0004355 A1, [hereinafter Zhao].
As per claim 2, the Wilkes-Dillon combination teaches the method according to claim 1, but it does not explicitly teach wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to batches of products produced by the microbial process, wherein the key information comprises different key information for each of the batches of the products. However, Zhao in the analogous art of quality monitoring systems teaches this concept. Zhao teaches:
wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to batches of products produced by the microbial process, wherein the key information comprises different key information for each of the batches of the products (paragraph 0070, discussing that determining the corrective actions by using the trained KNN model to look in a historical database to find a small group of “similar” batch runs to the batch run being analyzed (based on signatures up to the current point in time). The small group of identified “similar” batches is split into two groups: “good” and “bad” batch groups according to whether each batch run end-product quality is acceptable or not acceptable; paragraph 0091, discussing finding common feature values and differences between the two group of batches, specifically those differences in signatures over the remaining batch process; paragraph 0093, discussing a plot of historical batch data showing different batch families with defined EFs (engineering features) in a PCA model. In this example of batch production data, batch feature values are represented by PCA scores, where each point represents a batch. Batches with similar “signatures” form the closed groups (clusters). The shading represents batch labels, for example, the black shading represents “in-spec” batches and the lighter shading represents “out-of-spec” batches…Such an embodiment performs an analysis on the sibling batch data, and compares the sibling batch data with a group of batches from amongst the “in-spec” batches to identify significant differences in features between the two groups (siblings and in-spec batches). Based on these identified differences, an embodiment provides recommendations of corrective actions).
The Wilkes-Dillon combination describes features related to facility monitoring and quality control. Zhao is directed towards batch production processes. Therefore they are deemed to be analogous as they both are directed towards monitoring systems. 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 Wilkes-Dillon combination with Zhao because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying the Wilkes-Dillon combination to include Zhao’s feature for including wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to batches of products produced by the microbial process, wherein the key information comprises different key information for each of the batches of the products, in the manner claimed, would serve the motivation of improving the monitoring and control of batch production processes (Zhao, paragraph 0051); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 4, the Wilkes-Dillon combination teaches the method according to claim 1, but it does not explicitly teach wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to lots of products produced by the microbial process, wherein the key information comprises different key information for each of the lots of the products. However, Zhao in the analogous art of quality monitoring systems teaches this concept. Zhao teaches:
wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to lots of products produced by the microbial process, wherein the key information comprises different key information for each of the lots of the products (paragraph 0070, discussing that determining the corrective actions by using the trained KNN model to look in a historical database to find a small group of “similar” batch runs to the batch run being analyzed (based on signatures up to the current point in time). The small group of identified “similar” batches is split into two groups: “good” and “bad” batch groups according to whether each batch run end-product quality is acceptable or not acceptable; paragraph 0091, discussing finding common feature values and differences between the two group of batches, specifically those differences in signatures over the remaining batch process; paragraph 0093, discussing a plot of historical batch data showing different batch families with defined EFs (engineering features) in a PCA model. In this example of batch production data, batch feature values are represented by PCA scores, where each point represents a batch. Batches with similar “signatures” form the closed groups (clusters). The shading represents batch labels, for example, the black shading represents “in-spec” batches and the lighter shading represents “out-of-spec” batches…Such an embodiment performs an analysis on the sibling batch data, and compares the sibling batch data with a group of batches from amongst the “in-spec” batches to identify significant differences in features between the two groups (siblings and in-spec batches). Based on these identified differences, an embodiment provides recommendations of corrective actions).
The Wilkes-Dillon combination describes features related to facility monitoring and quality control. Zhao is directed towards batch production processes. Therefore they are deemed to be analogous as they both are directed towards monitoring systems. 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 Wilkes-Dillon combination with Zhao because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying the Wilkes-Dillon combination to include Zhao’s feature for including wherein grouping the multiple sets of microbial test results comprises grouping the multiple sets of microbial test results according to lots of products produced by the microbial process, wherein the key information comprises different key information for each of the lots of the products, in the manner claimed, would serve the motivation of improving the monitoring and control of batch production processes (Zhao, paragraph 0051); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 12 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 2, as discussed above.
Claim 14 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 4, as discussed above.
16. Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Wilkes et in view of Dillon, in further view of Long, Pub. No.: US 2010/0235205 A1, [hereinafter Long].
As per claim 5, the Wilkes-Dillon combination teaches the method according to claim 1, but it does not explicitly teach wherein the fingerprint uniquely identifies a product produced by the microbial process with at least one of (i) a batch number of the product, (ii) a lot number of the product or (iii) a production year of the product. However, Long in the analogous art of quality monitoring systems teaches this concept. Long teaches:
wherein the fingerprint uniquely identifies a product produced by the microbial process with at least one of (i) a batch number of the product, (ii) a lot number of the product or (iii) a production year of the product (paragraph 0004, discussing a method comprising: assigning a unique batch number to a batch of food processed in a processing facility; obtaining a first sample and a second sample from the batch of food and storing at least the second sample; testing the first sample with a safety test to obtain a first test result; making the first test result available in association with the unique batch number to a downstream user who receives from the processing facility food from the batch of food in association with the unique batch number; paragraph 0022, discussing that the downstream user has access to the test results, which may contain proof of contamination or non-contamination, enabling the downstream user to make an informed decision on whether to continue normally or regard the shipment as questionable or unusable. This is efficient because it can prevent a larger scale recall of contaminated product at a later date. An advantage in using an internet system for conveying or providing access to the test results is that the results may be obtained by the downstream user, for example upon request, almost instantaneously upon upload from the laboratory. Any request made may contain the unique batch number. This instant transfer of microbial test data is crucial to the "just in time" inventory management schedules of typical downstream users in the perishable food industry. Further, this system allows product testing to take place immediately after production while the products are for example still in transit or in cold storage awaiting shipping. In some embodiments, the first sample(s) is tested as soon as possible after being taken. For a downsteam user, quality control may be simplified somewhat to monitoring the hcost website for lab results. In some embodiments, the downstream user refrains from using the food prior to receipt of the first test result).
The Wilkes-Dillon combination describes features related to facility monitoring and quality control. Long is directed towards monitoring safety of product in a processing facility. Therefore they are deemed to be analogous as they both are directed towards monitoring systems. 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 Wilkes-Dillon combination with Long because the references are analogous art because they are both directed to solutions for monitoring and sampling, which falls within applicant’s field of endeavor (system and a method for preparing quality assurance and quality control report on microbial production process), and because modifying the Wilkes-Dillon combination to include Long‘s feature for including wherein the fingerprint uniquely identifies a product produced by the microbial process with at least one of (i) a batch number of the product, (ii) a lot number of the product or (iii) a production year of the product, in the manner claimed, would serve the motivation of improving safety by eliminating products including entire production runs which have been tested and proven to contain harmful pathogens or bacteria (Long, paragraph 0003); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 15 recites substantially similar limitations that stand rejected via the art citations and rationale applied to claim 5, as discussed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Crabtree et al., Pub. No.: US 2025/0258152 A1 – describes a comprehensive chemical fingerprinting system that provides detailed chemical analysis for quality control and authenticity verification.
Pilkington et al., Pub. No.: US 2003/0153059 A1 – describes that samples are collected for analysis at 2, 24, and 48 hours. A sample was also taken directly from the bioreactor and analyzed immediately in order to assess the state of the fermentation within the bioreactor at the time of the protocol.
Knight et al., Pub. No.: US 2021/0371938 A1 – describes that microbiome information that is collected or obtained at a particular industrial setting during an industrial activity.
Jacxsens, Liesbeth, et al. "A microbial assessment scheme to measure microbial performance of food safety management systems." International Journal of Food Microbiology 134.1-2 (2009): 113-125 – explains the development of a Microbial Assessment Scheme (MAS) as a tool for a systematic analysis of microbial counts in order to assess the current microbial performance of an implemented Food Safety Management System.
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/Darlene Garcia-Guerra/
Primary Examiner, Art Unit 3625
Prosecution Insights