DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 120 as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 16/142,319 filed on Sep 26, 2018, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application.
Claims 1-21 of the instant application recite a computer system for generating early warnings/alerts for cyanotoxin production in source water. The claims further recite the use of various processors and graphical interfaces in the computer system for analyzing the collected data, detecting trends, and generating alerts when thresholds are exceeded. However, there are no mentions of any computer systems, processors, or graphical interface within the disclosure of the prior-filed application, that would allow one of ordinary skill in the art to understand the invention of the instant application. Therefore, the prior-filed application fails to provide adequate support and/or enablement under 35 U.S.C. 112(a) for the invention of the instant application.
Claims 22-24 of the instant application recite a method for generating alerts for cyanotoxin production in a single body of water. The disclosure of the prior-filed application does provide adequate support for these claims. Specifically in Fig. 8 and paragraph [060] – [061] of the Specification, the prior-filed application demonstrates how the gene copies number measured by qPCR could be correlated with the cyanotoxin concentration on a logarithmic scale with a 95% confidence interval (claims 23 and 24). And it seems to be implied that warnings may be generated when gene copy levels exceed a threshold in para [047] of the Specification (claim 22).
Accordingly, claims 22-24 are entitled to the benefit of the prior application, and the effective filing date of claims 22-24 is Sep 26th, 2018. However, claims 1-21 are not entitled to the benefit of the prior application, and thus the effective filing date of claims 1-21 is June 22nd, 2022.
Claim Status
Claims 1-24 are currently pending and under exam herein.
Claims 1-24 are rejected.
Claims 1-19, 22, and 24 are objected to.
Information Disclosure Statement
There was no Information Disclosure Statement (IDS) filed with the instant application.
Nucleotide and/or Amino Acid Sequence Disclosures
REQUIREMENTS FOR PATENT APPLICATIONS CONTAINING NUCLEOTIDE AND/OR AMINO ACID SEQUENCE DISCLOSURES
Items 1) and 2) provide general guidance related to requirements for sequence disclosures.
37 CFR 1.821(c) requires that patent applications which contain disclosures of nucleotide and/or amino acid sequences that fall within the definitions of 37 CFR 1.821(a) must contain a "Sequence Listing," as a separate part of the disclosure, which presents the nucleotide and/or amino acid sequences and associated information using the symbols and format in accordance with the requirements of 37 CFR 1.821 - 1.825. This "Sequence Listing" part of the disclosure may be submitted:
In accordance with 37 CFR 1.821(c)(1) via the USPTO patent electronic filing system (see Section I.1 of the Legal Framework for Patent Electronic System (https://www.uspto.gov/PatentLegalFramework), hereinafter "Legal Framework") as an ASCII text file, together with an incorporation-by-reference of the material in the ASCII text file in a separate paragraph of the specification as required by 37 CFR 1.823(b)(1) identifying:
the name of the ASCII text file;
ii) the date of creation; and
iii) the size of the ASCII text file in bytes;
In accordance with 37 CFR 1.821(c)(1) on read-only optical disc(s) as permitted by 37 CFR 1.52(e)(1)(ii), labeled according to 37 CFR 1.52(e)(5), with an incorporation-by-reference of the material in the ASCII text file according to 37 CFR 1.52(e)(8) and 37 CFR 1.823(b)(1) in a separate paragraph of the specification identifying:
the name of the ASCII text file;
the date of creation; and
the size of the ASCII text file in bytes;
In accordance with 37 CFR 1.821(c)(2) via the USPTO patent electronic filing system as a PDF file (not recommended); or
In accordance with 37 CFR 1.821(c)(3) on physical sheets of paper (not recommended).
When a “Sequence Listing” has been submitted as a PDF file as in 1(c) above (37 CFR 1.821(c)(2)) or on physical sheets of paper as in 1(d) above (37 CFR 1.821(c)(3)), 37 CFR 1.821(e)(1) requires a computer readable form (CRF) of the “Sequence Listing” in accordance with the requirements of 37 CFR 1.824.
If the "Sequence Listing" required by 37 CFR 1.821(c) is filed via the USPTO patent electronic filing system as a PDF, then 37 CFR 1.821(e)(1)(ii) or 1.821(e)(2)(ii) requires submission of a statement that the "Sequence Listing" content of the PDF copy and the CRF copy (the ASCII text file copy) are identical.
If the "Sequence Listing" required by 37 CFR 1.821(c) is filed on paper or read-only optical disc, then 37 CFR 1.821(e)(1)(ii) or 1.821(e)(2)(ii) requires submission of a statement that the "Sequence Listing" content of the paper or read-only optical disc copy and the CRF are identical.
Specific deficiencies and the required response to this Office Action are as follows:
Specific deficiency - This application fails to comply with the requirements of 37 CFR 1.821 - 1.825 because it does not contain a "Sequence Listing" as a separate part of the disclosure or a CRF of the “Sequence Listing.”.
Required response - Applicant must provide:
A "Sequence Listing" part of the disclosure; together with
An amendment specifically directing its entry into the application in accordance with 37 CFR 1.825(a)(2);
A statement that the "Sequence Listing" includes no new matter as required by 37 CFR 1.821(a)(4); and
A statement that indicates support for the amendment in the application, as filed, as required by 37 CFR 1.825(a)(3).
If the "Sequence Listing" part of the disclosure is submitted according to item 1) a) or b) above, Applicant must also provide:
A substitute specification in compliance with 37 CFR 1.52, 1.121(b)(3) and 1.125 inserting the required incorporation-by-reference paragraph, consisting of:
A copy of the previously-submitted specification, with deletions shown with strikethrough or brackets and insertions shown with underlining (marked-up version);
A copy of the amended specification without markings (clean version); and
A statement that the substitute specification contains no new matter.
If the "Sequence Listing" part of the disclosure is submitted according to item 1) c) or d) above, applicant must also provide:
A CRF in accordance with 37 CFR 1.821(e)(1) or 1.821(e)(2) as required by 1.825(a)(5); and
A statement according to item 2) a) or b) above.
Specific deficiency – Nucleotide and/or amino acid sequences appearing in the drawings are not identified by sequence identifiers in accordance with 37 CFR 1.821(d). Sequence identifiers for nucleotide and/or amino acid sequences must appear either in the drawings or in the Brief Description of the Drawings. Specifically, Fig. 2, Fig. 3, Fig. 4, and Fig. 5 all contain nucleotide sequences with 10 or more residues, that are not identified with sequence identifiers.
Required response – Applicant must provide:
Replacement and annotated drawings in accordance with 37 CFR 1.121(d) inserting the required sequence identifiers;
AND/OR
A substitute specification in compliance with 37 CFR 1.52, 1.121(b)(3) and 1.125 inserting the required sequence identifiers into the Brief Description of the Drawings, consisting of:
A copy of the previously-submitted specification, with deletions shown with strikethrough or brackets and insertions shown with underlining (marked-up version);
A copy of the amended specification without markings (clean version); and
A statement that the substitute specification contains no new matter.
Drawings
The drawings are objected to because of the inclusion of amino acid sequences in Fig. 2, Fig. 3, Fig. 4, and Fig. 5 without proper sequence listing. Please see above.
The drawings are objected to under 37 CFR 1.83(a) because they fail to show CTP Assay Panel 100 and CTP Assay Panel 200, as described in the Specification. Any structural detail that is essential for a proper understanding of the disclosed invention should be shown in the drawing. MPEP § 608.02(d).
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “Method 300” has been used to designate both the method for using the CTP Assay Panel in Fig. 6 and the method to estimate cyanotoxin production in Fig. 10.
The drawings are objected to because there is an overlap in text on Fig. 9 in the title of Method 100 Early Warning, and there are incomplete letters in the triangles on Fig. 10.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
The abstract of the disclosure is objected to because the inclusion of legal phraseology (“said”) and minor grammatical errors (“the a processor”). A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
The disclosure is objected to because of the following informalities:
CLAIM OF PRIORITY section needs to be corrected as U.S. Application No. 16/142,319 was filed on September 26, 2018, not August 29, 2018.
BRIEF DESCRIPTION OF THE DRAWINGS section needs to be corrected, as there are no descriptions for Figures 1-8, and the numbering of current figure descriptions is inconsistent with the drawings.
DETAILED DESCRIPTION OF THE INVENTION sections needs further explanation for Fig. 9, Fig. 10, and Fig. 11 with regards to how the method steps are conducted, and descriptions refer to CTP Assay Panel 100 and CTP Assay Panel 200 that are not present in the Drawings.
Numerous grammatical and spelling errors throughout the Specification, examiner only list a few below, applicant is requested to read through and correcting all errors:
[002]: “relates to a an early alert”
[007] and [008]: “U.S. Patent Application No Application No. 16/142319”
[007]: “election” instead of “detection”
[011]: “study, a . one-week”
[014]: “of the a processor”
Acronyms need to be spelled out:
[010]: MC-ADDA
[025]: SOP
Appropriate correction is required.
35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, requires the specification to be written in “full, clear, concise, and exact terms.” The specification is replete with terms which are not clear, concise and exact. The specification should be revised carefully in order to comply with 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112. Examples of some unclear, inexact or verbose terms used in the specification are:
[010]: spp.
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claims 1-19, 22, and 24 are objected to because of the following informalities:
Claim 1: comma after “A computer system” and comma after “in source water” to clarify that the “comprised of” is being applied to the computer system and not the source water, the acronym “RT-qPCR” needs to be spelled out, “measurement dates” should be singular or “a detection value” should be plural
Claim 2: delete “the number of” and “level”, should read “a value that reflects toxin gene expression”, singular “detection value is a value” instead of “detection values is a value”
Claim 3: “said toxin gene expression” instead of “said gene expression”, insert “genes involved in” after “group consisting of” to read “copies of a gene selected from a group consisting of genes involved in production of microcystin, anatoxin…” to clarify that the group is made up of genes, needs a period at the end of the claim
Claim 4: “at least one trend processor” instead of “at least trend processor”, “to the detection values of one or more ordered pairs” instead of “to the detection values of the ordered pairs”, needs a period at the end of the claim
Claim 5: needs a period at the end of the claim
Claim 6: colon after “following”, comma after “decreasing”
Claim 7: “which further includes an/at least one alert processor configured to” instead of “which includes wherein said alert processor is configured to”
Claim 8: “perform” instead of “performs”
Claim 9: “processor is further configured to perform” instead of “processor performs a trend direction”, “said toxin gene expression values” instead of “said gene expression values”
Claim 10: “growth rate of a dominant toxin-producing cyanobacteria” instead of “growth rate of dominant toxin-producing cyanobacteria”, clarify plurality if needed
Claim 11: delete repetitive “base”
Claim 12: “further configured to perform” instead of “configured perform”
Claim 13: “toxin gene copies” instead of “gene copies”
Claim 14: “which is a processor that performs functions…” instead of “which is a processor which performs functions”
Claim 15: delete “test”, should read “configured to process user-defined testing intervals”
Claim 16: “the user-defined testing intervals range from…” instead of “the user-defined testing is from”, need a period at the end of the claim
Claim 17: “which is further configured to” instead of “which further configured to”, delete “all”, comma after alert instead of period, “elected” should be “selected”, acronym of “MC” needs to be spelled out, insert “or” before “a value obtained from…”, needs a period at the end of the claim
Claim 18: “to predict an estimated cyanotoxin concentration level based on…” instead of “predict cyanotoxin level estimated based on”, acronym of “qPCR”, “ELISA”, and “EPA” needs to be spelled out, comma after “ELISA-based cyanotoxin concentrations”, delete “can be compared”, insert “an EPA guideline level”
Claim 19: comma instead of period after “claim 1”, delete second “on” after the “one or more”, “previous year’s datasets”
Claim 22: spell out the acronym “qPCR”, “predicting” instead of “predict”, delete “the steps of”, “from” instead of “form”, delete “and” before generating, “a group consisting of genes associated with microcystin, anatoxin…” instead of “a group consisting of microcystin, anatoxin” to clarify that the group is made up of genes and not toxins
Claim 24: needs a period at the end of the claim
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-21 and 23 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites a computer system for generating early warnings and prediction of cyanotoxin production in source water, that falls under the statutory category of a machine, which is a “concrete thing, consisting of parts or of certain devices and combination of devices” (MPEP 2106.3). However, the claim goes on to describe a method of initiating RT-qPCR test data objects without describing the structure of the computer system that does this step. It seems more like the method is describing how to utilize the claimed computer system. A single claim which claims both an apparatus and the method steps of using the claimed apparatus is indefinite, as it is unclear what the metes and bounds of the claim are and creates confusion as to when direct infringement might occur. Please see MPEP 2173.05 (p) II. Product and Process in the Same Claim for more details and explanation.
Claim 2 recites the limitation "The apparatus of claim 1". There is insufficient antecedent basis for this limitation in the claim. Suggested amendment to change “apparatus” to “computer system”.
Claim 3-21 recites the limitation "the apparatus ". There is insufficient antecedent basis for this limitation in the claims. Suggested amendment to change “apparatus” to “computer system”.
Claim 10 recites the limitation "the trend ". There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "the trend ". There is insufficient antecedent basis for this limitation in the claim.
Where applicant acts as his or her own lexicographer to specifically define a term of a claim contrary to its ordinary meaning, the written description must clearly redefine the claim term and set forth the uncommon definition so as to put one reasonably skilled in the art on notice that the applicant intended to so redefine that claim term. Process Control Corp. v. HydReclaim Corp., 190 F.3d 1350, 1357, 52 USPQ2d 1029, 1033 (Fed. Cir. 1999). The term “a graphical interface” is recited in claim 14, and has an accepted meaning in the art as “a type of user interface that allows users to interact with electronic devices”. However, the applicant seems to take it to mean “a processor” based on the wording of the claim. The claim is indefinite for two reasons. One, the term “graphical interface” is indefinite because the specification does not clearly redefine the term. Two, it is unclear whether the applicant intends to include an actual graphical interface and a graphical processor or just a processor as claim.
Claim 16 recites the limitation "the user-defined testing". There is insufficient antecedent basis for this limitation in the claim.
Claim 20 recites the limitation "the apparatus of claim 20". There is insufficient antecedent basis for this limitation in the claim.
Claim 20 recites the limitation "said predictive modeling processor". There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation "said nutrient parameters". There is insufficient antecedent basis for this limitation in the claim.
Claim 23 recites the limitation "the method of claim 23". There is insufficient antecedent basis for this limitation in the claim.
Claim 23 recites the limitation "the toxin level". There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1- 24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claim 1 recites generating an alert when one of a detection value exceeds a certain level (abstract idea: mental process). The process of comparing a detection value to a known threshold before generating an alert based on the comparison is a mental process that can be done by the human mind; hence this limitation constitutes a mental process under abstract ideas. In addition, the process of comparing the values utilizes mathematical relations that might also fall under mathematical concepts in abstract ideas.
Claim 4 recites performing a trend function that compares the detection values having current measurement dates to detection values having prior measurement dates to identify a trend state (Abstract idea: mental process and/or mathematical concept). The process of comparing values associated with time points against one another to identified a trend (increasing, peak, decreasing, end) is a process that can be done in the human mind, making this limitation a mental process. In addition, the process utilizes mathematical relations to compare the values and determine a trend, which also constitutes a mathematical concept.
Claim 5 recites that the trend state is calculated based on detection values reflecting the number of cyanotoxin gene copies (Abstract idea; mathematical concept). The claim explicitly states that calculation of the trend state is based on values that represent numbers, making it a mathematical concept.
Claim 6 recites selecting the trend state from a group consisting of: increasing, peak, decreasing, and end (Abstract idea; mental process). The task of choosing one of the options based on the comparison of detection values, is a task that can be practically performed in the human mind.
Claim 7 recites performing an alert function and generating an alert when there is a change in the trend state (Abstract idea; mental process). The analysis of the trend state for changes and the reporting of these changes is a process that can be practically done in the human mind.
Claim 8 recites performing the trend function using moving average calculations and a comparison operation (Abstract idea; mental process and/or mathematical concepts). The limitation of analyzing the data for trends using comparison and mathematical operations, is a process that can be practically performed in the human mind. In addition, the moving average calculation constitutes a mathematical relation under mathematical concepts.
Claim 9 recites performing a trend direction function to calculate the rate at which the gene expression values are changing (Abstract idea; mental process and/or mathematical concept). The limitation of calculating the rate of change for the gene expression values is in the broadest sense a mathematical calculation, making the limitation a mathematical concept under abstract ideas. In addition, in the simplest sense, the calculation for a rate of change based on known values is a process that can be practically done in the human mind. Hence, the limitation also falls under a mental process.
Claim 10 recites determining the trend based on the growth rate of a dominant toxin-producing cyanobacteria. While the claim further limits the type of data utilized in the trend calculation, it does not change the fact that the trend calculation is a mathematical concept/mental process.
Claim 11 recites calculating a trend based on a running average of detection values on successive sampling dates (Abstract idea; mental process and/or mathematical concept). The limitation of identifying a trend through running average calculation is based on mathematical relations, making it a mathematical concept. Furthermore, the calculation of running averages over time is a process that can be practically performed in the human mind. Therefore, this limitation also constitutes a mental process.
Claim 12 recites performing a rate of change function to identify the rate of change of the trend status (Abstract idea; mental process and/or mathematical concepts). Similar to above, the limitation of calculating a rate of change based on known data is a mathematical concept. In addition, in the simplest sense, the process of calculating a rate of change can also be practically performed in the human mind. Hence, this limitation is also a mental process.
Claim 13 recites identifying the rate of change of trend status based on the number of gene copies. While the claim further limits the type of data utilized in the trend calculation, it does not change the fact that the trend calculation again, is a mathematical concept and/or a mental process.
Claim 14 recites converting the data stored in the multi-dimensional array objections into a graphical representation of measurement dates and detection values to graphically illustrate a trend (Abstract idea; mental process). The process of graphing data points in ordered pairs, say for example, with the date on the x-axis and value on the y-axis, is a process that can be practically performed by the human mind with the assistance of a paper and pen. Therefore, this limitation would constitute a mental process under abstract ideas.
Claim 15 recites being able to process user-defined testing intervals (Abstract idea; mental process and/or mathematical concepts). The limitation of being able to process data intervals, for example 7-10 days, within the calculation for trend analysis, is a limitation that can be done in the human mind. In addition, processing the data interval for mathematical relation would also make this limitation a mathematical concept.
Claim 16 recites that the user-defined testing interval is from seven to ten days. While the claim further limits the length of data utilized in the trend calculation, it does not change the fact that the trend calculation is a mathematical concept/mental process.
Claim 17 recites selecting user parameter and values for generating an alert (Abstract idea; mental process). The limitation is essentially picking the threshold values for different variable that would warrant an alert by the system. The process of picking and processing these thresholds is a limitation that can be practically achieved by the human mind. In addition, these threshold values would also be utilized in mathematical comparison with the detection values to determine whether an alert should be generated. Hence, this limitation might also constitute a mathematical concept.
Claim 18 recites predicting cyanotoxin concentration levels based on correlation between qPCR-based gene copies and ELISA-based cyanotoxin concentration measurements, and then comparing the predicted concentration levels to EPA guidelines to determine if an alert needs to be made (Abstract idea; mental process and/or mathematical concept). The limitation of correlating the qPCR derived gene copy number to the ELISA derived cyanotoxin concentration measurement is process that utilizes mathematical relations to derive a prediction, which would be a mathematical concept. And perhaps in the simplest sense, could also be practically performed in the human mind. In addition, the limitation of comparing the predicted cyanotoxin concentration to a known EPA guideline to determine if the threshold is exceeded to generate an alert, is also a process that can be practically done in the human mind.
Claim 19 recites using modeling calculations based on previous years’ datasets and current year’s water parameters in order to determine the probability of the types, level, and duration of cyanotoxin production for the current year (Abstract idea; mental process and/or mathematical concept). These limitations of the modeling and probability function utilize mathematical relations and correlations to predict results based on currently known variable, constitutes a mathematical concept. In addition, in the simplest sense, this process could also be performed by the human mind with assistance of paper and pen or even with a computer.
Claim 22 recites a method for processing qPCR test data and predicting cyanotoxin levels for a single body of water, extracting data from the qPCR test results, filling in an array with the data extracted, generating an alert if the aggregate number of gene copies is greater than a certain threshold, and identifying the genes as genes that produce microcystin, anatoxin, saxitoxin, and cylindrospermopsin (Abstract idea; mental process). The limitation of extracting data from qPCR test results and filling in an array with the data extracted is a process that can be practically performed by the human mind. In addition, the process of comparing the total number of gene copies to a threshold and generating an alert if threshold is exceeded, is also a process that can be practically performed in the human mind. Lastly, the process of identifying the genes to see if they are genes that produce microcystin, anatoxin, saxitoxin, and cylindrospermopsin, is also a limitation that is achievable by the human mind in a practical sense. Therefore, the above limitations are all mental processes. Additionally, due to the use of mathematical relations of comparison within the method, it may also constitute a mathematical concept.
Claim 23 recites performing a nonlinear regression analysis function to predict the toxin level (Abstract idea; mental process and/or mathematical concept). The limitation of a nonlinear regression analysis to predict toxin levels is a mathematical concept. And in the simplest sense, it could also be practically performed by the human mind. Hence, the limitation is both a mental process and a mathematical concept under abstract ideas.
Claim 24 recites performing the nonlinear regression with a 95% confidence interval (Abstract idea; mental process and/or mathematical concept). The limitation of a nonlinear regression analysis is a mathematical concept. And in the simplest sense, it could also be practically performed by the human mind. Hence, the limitation is both a mental process and a mathematical concept under abstract ideas.
The limitations regarding calculating trends/correlation of toxin levels, and generating alerts when there are changes or exceedances utilizes comparison functions, rolling averages, nonlinear regression functions, and other mathematical concepts to analyze and correlate data, making them a mathematical concept. In addition, based on the broadest reasonable interpretation, there are no additional limits on the data being processed, other than that they represent gene copy numbers with a date, such that the mathematical calculations cannot be performed in the human mind, hence these limitations also constitute a mental process. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. While claims 1-21 recite performing some aspects of the analysis with a “computer system” and “processors”, there are no additional limitations that indicate that the computer system and processors requires anything other than carrying out the recited mental process or mathematical concept in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then if falls within the “Mental processes” grouping of abstract ideas. As such, claims 1-24 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or uses the recited judicial exceptions in some other meaningful way. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment. Specifically, the claims recite the following additional elements:
Claim 1 recites a computer system that is able to initiate test data objects, identified by a test location and a test year. The test data object contains multi-dimensional array objects with ordered pairs of measurement dates and detection values. These additional elements are a mere data-gathering and data-organization step. In addition, the computer system seems to be just a generic computer.
Claim 1 and 7 also recites an alert processor that is able to generate an alert, which is just a mere conventional part/processor in a generic computer.
Claim 2 recites that the detection values are numbers that reflect toxin gene expression detected on the measurement date. While this further limits the data collected and analyzed, it does not change the fact that the limitation is mere data-gathering.
Claim 3 recites that the toxin gene expression are copies of genes selected from a group consisting of genes that produce microcystin, anatoxin, saxitoxin, and cylindrospermopsin. Again, while this further limits the data collected and analyzed, it does not change how the limitation is mere data-gathering.
Claim 4 recites at least one trend processor, which again is just a mere conventional part/processor in a generic computer.
Claim 14 recites a graphical interface (defined as a processor) for the computer system, which again, is a generic component of a generic computer.
Claim 20 recites a predictive modeling processor that is able to receive data (physical and chemical parameters). While the claim is adding additional components to the computer system, it seems that this additional processor is just a generic processor, capable of receiving data, for a generic computer. In addition, the limitation of receiving data (physical and chemical) is just mere data gathering.
Claim 21 recites that the nutrient parameters reflect quantities of nutrient (nitrates, phosphates, sulphates, and iron). While the claim further limits the type of data collected, it does not change the fact that the step is mere data gathering.
There are no limitations that indicate that the above claimed computer system or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. In general, linking the use of an abstract idea to a particular technological environment, such as a computer, does not integrate the abstract idea into a practical application based on MPEP 2106.05(h). As such, claims 1-24 are directed to an abstract idea as the additional elements do not integrate the judicial exceptions into a practical application (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). In the instant application, claims 1-24 do not recite further limitations or specifications to the additional elements that would indicate anything other than applying the judicial exceptions in a generic way on a generic computing environment. As discussed above, claims 1-24 do not include additional elements or limitations that would indicate anything other than carrying out the mathematical analysis of the data on a generic computer. Based off of MPEP 2106.05(f), mere instructions to implement an abstract idea on a computer does not amount to significantly more than the judicial exception. Hence, tthe additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-24 are not patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 22-24 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dong et al. (Scientific Reports 6 Article 20886, Published Feb 15 2016). The limitations of the instant application are italicized below.
With respect to claim 22, Dong et al. discloses the use of real-time qPCR (RT-qPCR) data, pertaining to Microcystis (a cyanotoxin producer that produces microcystin), in a monitoring system with warning threshold (pg. 1 Abstract, a method for processing qPCR test data and predict cyanotoxin levels for a single body of water). Dong et al. collected water samples weekly (July 2012 – October 2012) at 6 different sites for a total of 81 water samples for analysis through qPCR and RT-qPCR (pg. 6 para 3). Dong et al. discloses that they examined the presence and concentration of Microcystis, a microcystin (MC) producer with RT-qPCR methods (pg. 7 para 2). Specifically, Dong et al. chose the gene mcyA, which is responsible for the biosynthesis of microcystin, to be amplified and quantify through RT-qPCR (pg. 7 para 2, identifying the genes as a gene copy from a group consisting of microcystin, anatoxin, saxitoxin, and cylindrospermopsin). After running the RT-qPCR assays and analyzing the results, Dong et al. obtains a dataset comprised of gene copies of mycA per liter of water for each sample identified with a date and testing site, which was plotted in Figure 2. (pg. 3 Fig. 2, iteratively extracting the data from qPCR test results; populating an array to store date and number of gene copies per liter of water). Dong et al. then highlights how by correlating the dataset of mycA copies/L to MC concentration levels, they would be able to create a significant indicator for the early warning of potential MC hazards (pg. 4 para 4). Finally, Dong et al. generates two-level warning thresholds of 1.0 x 107 and 8.0 x 1010 mycA gene copies/L that correspond to standard compliance values for drinking water sources (pg. 6 para 1, generating an alert if the aggregate number of gene copies is greater than a certain level).
Regarding claim 23, Dong et al. teaches the use of a nonlinear regression process to predict the dependent variable of MC concentration in ug/L based on the independent variable of mycA copies/L with a 95% confidence interval, for each site (pg. 6 para 5 and pg. 5 Fig. 3, performs a nonlinear regression analysis function to predict the toxin level).
Concerning claim 24, Dong et al teaches the use of a nonlinear regression process to predict the dependent variable of MC concentration in ug/L based on the independent variable of mycA copies/L with a 95% confidence interval, for each site (pg. 6 para 5 and pg. 5 Fig. 3, nonlinear regression analysis function predicts said toxin with a 95% confidence interval).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 8-21 are rejected under 35 U.S.C. 103 as being unpatentable over Lu et al. in view of Dai et al. (CN103678910B, Published Dec 10, 2014). The limitations of the instant application are italicized below.
With respect to claim 1, Lu et al. discloses the use of RT-qPCR and qPCR data, pertaining to microcystin (a cyanotoxin) producers (MCPs), in an early warning system for alerting and predicting the onset of toxic algal bloom (pg. 1 Abstract, generating early warnings and predictions of cyanotoxin production in source water). To begin, Lu et al. collected water samples from 4 different test locations, named EMB, BUOY, EFLS, CGB (pg. 2 right col para 2). Lu et al. collected these water samples weekly (May 6, 2015 – Sep 30, 2015) and daily (during the bloom, entire month of June) for analysis through qPCR and RT-qPCR (pg.2 right col para 3). After running the RT-qPCR assays and analyzing the results, Lu et al. has a dataset comprised of gene copy numbers (gns) of various MCPs per mL of water, for each sample that is identified with a date and testing location (pg. 3 right col para 1, initiating RT-qPCR test data objects for storing RT-qPCR gene expression data, where each object is identified by test location, test year). Lu et al. then organizes the data by testing location and plots the ordered pairs of detected gns/mL and measurement dates in Fig.2, Fig. 3, and Supplementary Fig. 1. Lu et al. also shows how the data is organized into various tables (columns representing dates, rows representing genes, data represents detected gns/mL) with ordered pairs of measurement dates and detection values (Supplementary Table S8, wherein each of said RT-qPCR test data objects includes one or more multi-dimensional array objects; wherein each of said multi-dimensional array objects is configured to store ordered pairs of data wherein each of said ordered pairs is comprised of measurement dates and a detection value). Then through analysis of the collected data and RT-qPCR results, Lu et al. found the threshold gns/mL values correlating to microcystin (MC) concentrations of 0.3ug/L, 1.6 ug/L, and 4ug/L, which are the US EPA Health Advisory cutoff thresholds (pg. 7 right col para 1, pg. 7 Table 4). With the knowledge of these threshold values, Lu et al. proposes a rapid and cost-effective monitoring process where proactive toxin measurements would be initiated when RT-qPCR targeting MCPs reached a threshold level (pg. 10 right col para 1). Lu et al. specifically proposes a one-week early warning of MC exceedance over the EPA Health Advisory (pg.1 Abstract, generates an alert when one of said detection values exceeds a certain level).
Regarding claim 2, Lu et al. teaches that the detection values are measured in gns/mL, which reflect the number of copies of a toxic gene per mL of water for each sample collected on a measurement date (pg. 3 right col para 1, wherein each of said detection values is a value that reflects the number of a toxin gene expression level detected on said measurement date).
Concerning claim 3, Lu et al. discloses that they examined the presence of toxin (microcystin, anatoxin-a, saxitoxin, cylindrospermopsin and nodularin) producers with the PCR methods (pg. 2 left col para 1). For example, Lu et al. chose the genes mycE, mcyA, and mycG, which are clusters of genes responsible for the biosynthesis of microcystin, to be amplified through RT-qPCR (pg. 3 left col para 2, wherein said gene expression are copies of a gene selected from a group consisting of production of microcystin, anatoxin, saxitoxin, and cylindrospermopsin).
With respect to claim 4, Lu et al. teaches statistical analysis of the data derived from RT-qPCR for trend analysis over time (pg. 5 right col para 2). By comparing the detection values (gn/mL) of MCPs, including Microcystis, over time, Lu et al. showed how the trend in detection values followed the bloom of Microcystis (pg. 5 right col para 2, wherein said trend function compares the detection values of one or more ordered pairs of gen copy data having current measurement dates to the detection values of the ordered pairs having prior measurement dates to identify a trend state). In addition, Lu et al. expands on the trend seen, talking about how there was no significant expression of MCPs in May, before the values slowly began to increase from late May to June, peaking in June/July before starting to decrease again in August, and eventually ending in September with no significant detection (pg. 5 right col para 2, a trend state).
Regarding claim 5, Lu et al. discloses that the detection values are measured in gns/mL, which reflect the number of copies of a toxic gene per mL of water for each sample collected on a measurement date (pg. 3 right col para 1, wherein said trend state is calculated based on detection values reflecting the number of cyanotoxin gene copies).
Concerning claim 6, Lu et al. teaches how the variation of toxin gene RT-qPCR signal and total microcystin (MC) along the time course (Fig. 3) reflected various stages (initiation, growth, stagnation, and decrease) of potential MC production (pg. 10 left col para 2, wherein said trend state is selected from a group consisting of the following increasing, peak, decreasing, and end). In addition, Lu et al. expands on the trend seen, talking about how there was no significant expression of MCPs in May, before the values slowly began to increase from late May to June, peaking in June/July before starting to decrease again in August, and eventually ending in September with no significant detection (pg. 5 right col para 2, increasing, peak, decreasing, and end). Furthermore, Lu et al. states that Fig. S3 also shows how the genome copy number of MCPs trended upward in mid-June, peaked from late June to mid-July, and decreased in late July in all four sites (pg. 5 left col para 1).
With respect to claim 8, Lu et al. teaches the calculation of average monthly quantities of genome copy number per mL for each month and comparing month from month to determine a trend (pg. 5 right col para 2, Table S8, perform said trend function using a moving average calculation and a comparison operation). Specifically, Lu et al. calculates the average detection value in each month (May, June, July, August, and September) in Table S8 and then compares the values from month to month to determine the monthly fold changes presented in Table 3 (pg. 5 left col).
Regarding claim 9, Lu et al. teaches the calculation of the average detection value in each month (May, June, July, August, and September) in Table S8 and then compares the values from month to month to calculate the monthly fold changes presented in Table 3 (pg. 5 left col, a trend direction function calculation to determine the rate at which said gene expression values are changing).
Concerning claim 10, Lu et al. teaches that Microcystis is the dominate MCP in the sample populations (pg. 4 right col para 2). In addition, Lu et al. also teaches the determination of a trend pattern (described above) based on Microcystis as the main MCP (pg. 5 right col para 2, wherein the trend is based on the growth rate of dominant toxin-producing cyanobacteria).
With respect to claim 11, Lu et al. teaches the calculation of average monthly quantities of genome copy number per mL for each month and comparing month from month to determine a trend (pg. 5 right col para 2, Table S8, wherein the trend is based on a running average of detection values on successive sampling dates).
Regarding claim 12, Lu et al. teaches the calculation of the average detection value in each month (May, June, July, August, and September) in Table S8 and then compares the values from month to month to calculate the monthly fold changes presented in Table 3 (pg. 5 left col, a rate of change function to identify the rate of change of said trend status).
Concerning claim 13, Lu et al. discloses that the detection values are measured in gns/mL, which reflect the number of copies of a toxic gene per mL of water for each sample collected on a measurement date (pg. 3 right col para 1, to identify the rate of change of said trend status based on the number of gene copies).
With respect to claim 14, Lu et al. converts the data from the RT-qPCR along with their measurement dates into graphical representation of the MCPs levels over time to help visualize the trends (pg. 6 Fig.2 and Fig. 3, convert data stored in one or more said multi-dimensional array objects into a graphical representation of measurement dates and detection values to graphically illustrate a trend).
Regarding claim 15, Lu et al. discloses that they chose to collect the data weekly (7-day interval) and daily (1-day interval) for analysis (pg. 2 right col para 2, process test user-defined testing intervals).
Concerning claim 16, Lu et al. discloses that they chose to collect the data weekly (7-day interval) and daily (1-day interval) for analysis (pg. 2 right col para 2, wherein the user-defined testing is from seven to ten days).
With respect to claim 17, Lu et al. selected threshold parameters based on MC concentrations detected for generating an alert, specifically Lu et al. utilized US EPA Advisory thresholds of 0.3 ug/L, 1.6 ug/L and 4 ug/L (pg. 1 right col para 1, value for generating an alert, elected from a group consisting of a single MC detection value, a trend, a rate, a value obtained from a rolling average calculation).
Regarding claim 18, Lu et al. teaches the correlation of the qPCR derived genome copy numbers with ELISA derived MC concentrations through maximum likelihood estimation, in order to use regressions to predict the dependent variable of MC concentration based on the independent variable of genome copy numbers (pg. 4 left col para 1, predict cyanotoxin level estimated based on the correlations between qPCR-based gene copies and ELIA-based cyanotoxin concentrations). Lu et al. then goes on to compare the estimated cyanotoxin concentration with EPA thresholds in order to determine microcystin exceedance (pg. 4 left col para 2, to compare the estimated cyanotoxin concentration level can be compared with EPA guideline level to indicate alert).
Concerning claim 19, Lu et al. teaches how the analysis of the qPCR and RT-qPCR data can be utilized to predict the dominant type of cyanobacteria as Microcystis (pg.8 right col para 2, perform a calculation to determine the probability of … type … of cyanotoxin production). In addition, Lu et al. also teaches how the genus or species-specific RT-qPCR signals can be used to indicate potential MC production levels (pg. 10 left col para 3, perform a calculation to determine the probability of … level … of cyanotoxin production). And finally, Lu et al. concludes with RT-qPCR data can be used to indicate the initiation/ending and peak period of toxin in raw water (pg.11 left col para 1, perform a calculation to determine the probability of … duration … of cyanotoxin production)
However, Lu et al. fails to explicitly teach a computer system (claim 1) with a trend processor (claim 4, 8, 9, 12, 13, 15), an alert processor (claim 1 and 7), a graphical interface (claim 14), and a predictive modeling processor (claim 20). Hence, Lu et al. was not able to teach selecting parameter values with the computer system (claim 17). In addition, Lu et al. only utilized RT-qPCR data from one year and failed to incorporate other physical and chemical parameters, nutrient parameters, and past year’s data (claim 19). Yet, a computer system capable of collecting data, analyzing/predicting trends based on current and previous records, displaying the trends, and generating alerts based on trend calculations was well known in the art at the time of the effective filing date of the invention and has been successfully demonstrated by Dai et al.
With respect to claim 1, Dai et al. teaches an early warning system for algal bloom in the reservoirs that includes a monitoring cloud module (1), an information cloud module (2), an application support module (3), an algal bloom early warning module (4), and a consultation and decision-making module (5) (Claim 1, A computer system for generating early warnings and predictions of cyanotoxin production in source water). Dai et al. also discloses that the algal bloom early warning module consists of a risk analysis unit and an early warning and forecasting unit (Description [0018]). The early warning and forecasting unit specifically makes judgments based on the algal bloom risk threshold to distribute early warnings (Description [0018], at least one alert processor which generates an alert when one of said detection values exceeds a certain level).
Regarding claim 4, 8, 9, 12, 13, and 15, Dai et al. discloses a data collaboration unit that is used for multi-functional data management and data mining applications on large datasets, including trend analysis (Description [0042], at least trend processor, said trend processor).
Concerning to claim 14, Dai et al. demonstrate that collected data can then be plotted into graphical representations for easier visualization (Description [0080] - [0086], Drawings Fig. 6 - Fig. 11, a graphical interface which is a processor which performs functions to convert data stored in one or more said multi- dimensional array objects into a graphical representation).
With respect to claim 17, Dai et al. chose set the parameters for generating an alert into five levels with values of 0.2, 0.4, 0.6, 0.8 and 1.0 to corresponding to no risk, low risk, moderate risk, high risk, and extreme risk respectively (Description [0120], configured to allow a user to select user- selected parameters and values for generating an alert).
Concerning claim 19, Dai et al. teaches the use of dynamic testing, data-driven risk prediction, and event analogy reproduction to analyze the risk and potential severity of algal bloom outbreaks (Description [0056], perform a probability function on one or more on said ordered pairs within one or more … test data objects for a current year and to perform a calculation to determine the probability of types, level and duration of cyanotoxin production according to modeling calculations). Dai et al. further explains that environmental factors (flow velocity, water level, water temperature, wind speeds, pH value, total phosphorus, total nitrogen, etc.) from the current year and historical data records are utilized for these probability calculations (Description [0064] and [0065], according to modeling calculations based on previous year datasets and current year’s water parameters).
With respect to claim 20, Dai et al. teaches that the risk analysis unit of the algal bloom early warning module takes as input environmental parameters of the water, such as flow velocity, water level, water temperature, wind speeds, pH value, total phosphorus, and total nitrogen, for analysis (Description [0064], predictive modeling processor is configured to receive parameters selected from a group consisting of physical parameters and chemical parameters over time).
Regarding claim 21, Dai et al. teaches that the environment parameters included quantities of total phosphorus and total nitrogen (Description [0064], nutrient parameters reflect quantities of nutrients selected from a group consisting of nitrates, phosphates, sulphates and iron).
It would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention to incorporate the RT-qPCR data and analysis of Lu et al. with the water monitoring system of Dai et al. to create a quicker and more cost-effective water monitoring system that would be able to generate more specific and accurate predictions on cyanotoxin blooms. One of ordinary skill in the art would have been motivated to incorporate the data and analysis of Lu et al. in the water monitoring system of Dai et al. to predict with cyanotoxin blooms in better detail, as the RT-qPCR data would allow the monitoring system to further analyze the types of cyanobacteria present in the water, the levels of cyanotoxins produced, and even predict with lower cost, the risk of a future cyanotoxin bloom (Lu et al. pg. 10 right col). In addition, one of skill in the art before the effective filing date of the claimed invention would have a reasonable expectation of success at incorporating the RT-qPCR data of Lu et al. into the system of Dai et al. as Dai et al. has explicitly demonstrated capabilities of processing multi-parameter and structured datasets similar to that of Lu et al., such as algal cell abundance, algal toxin centration, and chlorophyll concentration (Dai et al. [0064]).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Lu et al. and Dai et al. as applied to claim 1-6, and 8-24 above, further in view of Molenaar et al. (CA3043600A1, Published Nov 17 2019). The limitations of the instant claim are italicized below.
The limitations of claims 1-6 and 8-24 have been taught by Lu et al. and Dai et al. above.
With respect to claim 7, although Lu et al. and Dai et al. do describe generating an alert/warning based on exceedance over a threshold, they do not explicitly teach generating an alert based on detection of a change in the data. However, Molenaar et al. does teaches a water monitoring system that is capable of generating an alert if a rapid change in any one or more of the multi-parameter sensor data measured is detected (pg. 9 [0029], alert processor which is configured to perform an alert function and generate an alert when there is a change in the trend state).
It would have been prima facie obvious to one of ordinary skill in the art at the effective filing date of the invention to implement the alert system of Molenaar et al. with the data of Lu et al. and water monitoring system of Dai et al. to detect minute changes in the trend of cyanotoxins that might indicate the onset of a bloom, as alerting when the toxin levels exceed the threshold might mean it is too late for intervention. One of ordinary skill in the art would have been motivated to incorporate the alerting system of Molenaar et al. to track the trends over time and generate an earlier warning as soon as changes in toxin levels are detected to prevent the onset of a cyanotoxin bloom. In addition, one of skill in the art before the effective filing date of the claimed invention would have a reasonable expectation of success at incorporating the alert system of Molenaar et al. into the water monitoring system of Dai et al. as both systems are carried out on similar computing system with similar functions, to alert for abnormalities in detected water parameters.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gallager et al. (US20190293565A1, Sep 6, 2019)
Clark et al. (US20250116606A1, Apr 10, 2025)
Fu et al. (CN108519472A, Sep 11, 2018)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WENYU YANG whose telephone number is (571)272-0035. The examiner can normally be reached 8:30am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached at (571) 272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/W.Y./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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