Prosecution Insights
Last updated: April 19, 2026
Application No. 18/753,352

Spectroscopic Methods and Systems for the Qualitative and Quantitative Analysis of Samples

Non-Final OA §101§102§103
Filed
Jun 25, 2024
Examiner
TON, TRI T
Art Unit
2877
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Mariposa Technology Inc.
OA Round
3 (Non-Final)
86%
Grant Probability
Favorable
3-4
OA Rounds
2y 3m
To Grant
97%
With Interview

Examiner Intelligence

Grants 86% — above average
86%
Career Allow Rate
1011 granted / 1169 resolved
+18.5% vs TC avg
Moderate +11% lift
Without
With
+10.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 3m
Avg Prosecution
47 currently pending
Career history
1216
Total Applications
across all art units

Statute-Specific Performance

§101
3.9%
-36.1% vs TC avg
§103
50.4%
+10.4% vs TC avg
§102
21.7%
-18.3% vs TC avg
§112
17.0%
-23.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1169 resolved cases

Office Action

§101 §102 §103
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 . DETAILED ACTION Response to Arguments 1. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). 2. With respect to applicant’s remarks filed on 10/06/25 regarding rejected claims 1-20, pages 7-11, the new added limitation “applying a computer run spectral quality algorithm” has been found in reference of JP 2017524924, (hereafter 2017524924, please see attached file for reference of JP 2017524924), figure 2, computer/microcontroller system 124. Page 7, lines 7-23, acquired spectral quality … after completing the Raman scan and storing the results … classified into three clinically important categories: benign, or Low-grade and high-grade adenomas, or Adenocarcinoma. This limitation is not different from to determine if said sample spectrum is of acceptable quality. Further in page 21, lines 25-35, variation across the series of spectra is less than the maximum value. This limitation is not different from to determine if said sample spectrum is of acceptable quality. Further, new reference Lightner et al. (Pub. No. 2011/0125477) also teaches the new added limitation “applying a computer run spectral quality algorithm” ([0003, 0013, 0032, 0096, 0166, 0204, 0279]). 3. According to current specification, the new added limitation “applying a computer run spectral quality algorithm” is mental, that is can be done with pen and paper and math, (Applicant’s Pub. No. 2024/0426757, [0051] SNR equation) and root mean square, ([0050]). This limitation could be considered an abstract idea (the determination can be done by the mind/human). Therefore, the claimed subject matter does not recite patent eligible subject matter under 35 USC §101. 4. Grounds for the rejection of claims are provided below as necessitated by amendment. Continued Examination Under 37 CFR 1.114 5. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/06/25 has been entered. Claim Rejections - 35 USC § 101 6. 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. 7. Claims 1, 7, 12, rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the followings: Step 1: Is the Claim, to a Process, Machine, Manufacture or Composition of Matter? The claims 1, 7, recite method for analyzing a sample. Step 2A Prong One: Does the Claim Recite an Abstract Idea? Claims 1, 7, 12, recite method comprising the steps of: applying a computer run spectral quality algorithm to the sample spectrum; According to current specification, the new added limitation “applying a computer run spectral quality algorithm” is mental, that is can be done with pen and paper and math, (Applicant’s Pub. No. 2024/0426757, [0051] SNR equation) and root mean square, ([0050]). This limitation could be considered an abstract idea (the determination can be done by the mind/human). Therefore, the examiner finds that the foregoing underlined elements recite a mental process because they can be performed in the human mind. Step 2A Prong Two: Does the Claim Recite Additional Elements That Integrate the Abstract Idea into a Practical Application? The elements in the claim that are not underlined above are the additional elements. The examiner finds that each of the following additional elements merely adds insignificant extra-solution activity to the abstract idea: sending said beam of light though a spectral analyzer, a computer run. The examiner finds that each of the following additional elements does no more than generally link the use of the abstract idea to a particular technological environment or field of use because they are merely an incidental or token addition to the claim that does not alter or affect how the method steps of to determine if said sample spectrum is of acceptable quality, to determine a correct class for said sample, to determine the identity and concentration of any chemical species present in said sample: a spectral analyzer, a computer run. Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For example, there is no indication that the combination of elements improves the functioning of a computer, a spectral analyzer or improves any other technology. Step 2B: Does the Claim Recite Additional Elements That Amount to Significantly More Than the Abstract Idea? The examiner finds that the additional elements do not amount to significantly more than the abstract idea for the same reasons discussed above with respect to the conclusion that the additional elements do not integrate the abstract idea into a practical application. In the other words, it appears that these identified elements could be considered an abstract idea (the determination can be done by the mind/human). Therefore, the claimed subject matter does not recite patent eligible subject matter under 35 USC §101. Claim Rejections - 35 USC § 102 8. 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. 9. Claim(s) 1, 3-6, is/are rejected under 35 U.S.C. 102 as being unpatentable over Lightner et al. (Pub. No. 2011/0125477). Hereafter “Lightner”. Regarding Claim(s) 1, Lightner teaches a method for analyzing a sample (Abstract; [0068, 0070]; [0190], lines 10-13; [0260], lines 8-9), said method comprising the steps of: a. measuring a spectrum of said sample by first exposing said sample to a beam of light to allow said beam of light to interact with said sample ([0004]; [0049], lines 1-6; [0056]; [0103]; [0133], lines 1-5; [0150], lines 2-6; [0159]; Figure 2) and then sending said beam of light though a spectral analyzer ([0032]; [0049], lines 6-11; [0096]; [0133], lines 6-11; [0150], lines 6-11. It is inherent that in order to analyze the spectroscopic data, the method must have a spectral analyzer); b. applying a computer run spectral quality algorithm to the sample spectrum measured in step (a) to determine if said sample spectrum is of acceptable quality ([0003], lines 2-4; [0059, 0096]; [0166], lines 1-5; [0178]. Note: Errors are the rule rather than the exception due, for example, to trivial errors, instrument errors, and sampling errors. If significantly large in quantity or quality, these errors can destroy meaningful results or interpretation. This is not different from to determine if said sample spectrum is of acceptable quality; [0204, 0219]); c. applying a classification algorithm to sample spectrum deemed of acceptable quality in step (b) to determine a correct class for said sample ([0014, 0035, 0068, 0195]. Note: allows classification to reliably assign new samples to existing classes in a given population is not different from to determine a correct class for said sample; [0376]. Note: The modeling classifies plants into more classes is not different from to determine a correct class for said sample); and d. identifying a quantitative algorithm suitable for the sample class determined in step (b) and applying said quantitative algorithm to said sample spectrum ([0003, 0032]; [0049], lines 6-11; [0096]; [0133], lines 6-11; [0150], lines 6-11) to determine the identity and concentration of any chemical species present in said sample ([0154], lines 1-7; [0190], lines 10-13; [0423], lines 8-15). Regarding Claim(s) 3, Lightner teaches computer run spectral quality algorithm applied in step (b) is selected from the group consisting of noise level, peak-to-peak noise level, root mean square noise level, signal-to-noise ratio, and a peak position or positions compared to the peak positions of a reference standard ([0179, 0203, 0270, 0271, 0336]). Regarding Claim(s) 4-5, Lightner teaches the classification algorithm applied in step (c) or the quantitative algorithm identified and applied in step (d) is selected from the group consisting of principle components analysis, least squares, partial least squares, discriminant analysis, linear discriminant analysis, neural networks, SIMCA (Soft Independent Modeling of Class Analogies), Machine Learning and Artificial Intelligence algorithms, Multivariate Curve Resolution (MCR), Decision Trees, Nearest Neighbor Classification, Kernel Approximation Classification, Ensemble Classification, Neural NetClassification, library searching, spectral subtraction, classical least squares, K-Matrix,inverted least squares, and P-matrix ([0050, 0064, 0066, 0068, 0070, 0095, 0115, 0136, 0140, 0160, 0185, 0190, 0193, 0195, 0219, 0224, 0228, 0259, 0291, 0292, 0336, 0351, 0353, 0370, 0372, 0387, 0389, 0406, 0408, 0425]). Regarding Claim(s) 6, Lightner teaches the chemical species information determined in step (d) is communicated to an output device via a wired or wireless connection, further wherein said output device is selected from the group consisting of a cellular phone, smart phone, and computer ([0040, 0046, 0051, 0052, 0139, 0215]). Claim Rejections - 35 USC § 103 10. 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 of this title, 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. 11. Claim(s) 2, is/are rejected under 35 U.S.C. 103 as being unpatentable over Lightner et al. (Pub. No. 2011/0125477) in view of Messerchmidt (U.S. Pat. No. 9,041,923). Hereafter “Lightner”, “Messerchmidt”. Regarding Claim(s) 2, Lightner teaches all the limitations of claim 1 as stated above except for the spectral analyzer utilized in step (a) is selected from the group consisting of dispersive, Fourier transform, non-dispersive, filter based, and Fabry-Perot and the type of spectroscopy utilized in step (a) is selected from the group consisting of radio wave, microwave, far infrared, mid-infrared, near infrared, visible, ultraviolet, x-ray, absorption, reflection, transmission, scattering, emission, and Raman. Messerchmidt teaches the Fourier transform spectral analyzer consisting of infrared (column 15, lines 55-56). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention was made to modify Hammer by having Fourier transform spectral analyzer consisting of infrared in order to generate light beam for the system (column 15, lines 55-56). 12. Claim(s) 7, 9-12, 15-20, is/are rejected under 35 U.S.C. 103 as being unpatentable over Lightner et al. (Pub. No. 2011/0125477), in view of Dou et al. (U.S. Pat. No. 5,815,260), and further in view of Smith (U.S. Pat. No. 10,451,480). Hereafter “Lightner”, “Dou”, “Smith”. Regarding Claim(s) 7, 12, 18, Lightner teaches all the limitations of claim 7 and 12, similarly as in claim 1 above (please see rejection claim 1 in paragraph 9 above) except for Raman spectrum, cannabis. Dou teaches Raman spectrum (column 2, lines 42-48) and Smith teaches cannabis (column 3, lines 18-20; Column 13, lines 35-48), concentration of tetrahydrocannabinol present in cannabis sample (column 19, lines 21-28). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention was made to modify Lightner by having Raman spectrum and cannabis in order to have a number of items can be simultaneously measured in a short time (Dou, column 2, lines 42-48) and to inspect special concentration of tetrahydrocannabinol present in cannabis sample (Smith, column 3, lines 18-20; Column 13, lines 35-48; Column 19, lines 21-28). Regarding Claim(s) 9, 10, 15, 16, 19, 20, Lightner and Dou and Smith teach all the limitations of claims 7, 12, as stated above, Lightner also teaches classification/quantitative algorithm applied is selected from the group consisting of principle components analysis, least squares, partial least squares, discriminant analysis, linear discriminant analysis, neural networks, SIMCA (Soft Independent Modeling of Class Analogies), Machine Learning and Artificial Intelligence algorithms, Multivariate Curve Resolution (MCR), Decision Trees, Nearest Neighbor Classification, Kernel Approximation Classification, Ensemble Classification, Neural Net Classification, library searching, spectral subtraction, classical least squares, K-Matrix, inverted least squares, and P-matrix ([0050, 0064, 0066, 0068, 0070, 0095, 0115, 0136, 0140, 0160, 0185, 0190, 0193, 0195, 0219, 0224, 0228, 0259, 0291, 0292, 0336, 0351, 0353, 0370, 0372, 0387, 0389, 0406, 0408, 0425]). Regarding Claim(s) 11, 17 Lightner and Dou and Smith teach all the limitations of claim, 7, 12, as stated above, Lightner also teaches the chemical species information determined is communicated to an output device via a wired or wireless connection, further wherein said output device is selected from the group consisting of a cellular phone, smart phone, and computer, ([0040, 0046, 0051, 0052, 0139, 0215]). 13. Claim(s) 8, 13-14, is/are rejected under 35 U.S.C. 103 as being unpatentable over Lightner et al. (Pub. No. 2011/0125477), in view of Dou et al. (U.S. Pat. No. 5,815,260), and further in view of Smith (U.S. Pat. No. 10,451,480), and in view of Messerchmidt (U.S. Pat. No. 9,041,923). Hereafter “Lightner”, “Dou”, “Smith”, “Messerchmidt”. Regarding Claim(s) 8, 13, 14, Lightner teaches the spectral quality algorithm applied in step (b) is selected from the group consisting of noise level, peak-to-peak noise level, root mean square noise level, signal-to-noise ratio, and a peak position or positions compared to the peak positions of a reference standard ([0179, 0203, 0270, 0271, 0336]). Although Lightner and Dou and Smith do not teach the spectral analyzer utilized in step (a) is selected from the group consisting of dispersive, Fourier transform, non-dispersive, filter based, and Fabry-Perot, Messerchmidt teaches the Fourier transform spectral analyzer consisting of infrared (column 15, lines 55-56). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention was made to modify Although Lightner and Dou and Smith by having Fourier transform spectral analyzer consisting of infrared in order to generate light beam for the system (column 15, lines 55-56). Other references New reference of JP 2017524924 also discloses new added limitation “applying a computer run spectral quality algorithm”, (figure 2, computer/microcontroller system 124. Page 7, lines 7-23, acquired spectral quality … after completing the Raman scan and storing the results … classified into three clinically important categories: benign, or Low-grade and high-grade adenomas, or Adenocarcinoma. This limitation is not different from to determine if said sample spectrum is of acceptable quality. Further in page 21, lines 25-35, variation across the series of spectra is less than the maximum value. This limitation is not different from to determine if said sample spectrum is of acceptable quality. Please see attached file for reference of JP 2017524924). Fax/Telephone Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRI T TON whose telephone number is (571)272-9064. The examiner can normally be reached on 8am-4pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michelle Iacoletti can be reached on (571)270-5789. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. October 28, 2025 /Tri T Ton/ Primary Examiner Art Unit 2877
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Prosecution Timeline

Jun 25, 2024
Application Filed
Sep 18, 2024
Non-Final Rejection — §101, §102, §103
Dec 16, 2024
Response Filed
Dec 18, 2024
Interview Requested
Dec 31, 2024
Final Rejection — §101, §102, §103
Jan 08, 2025
Examiner Interview Summary
Jan 08, 2025
Applicant Interview (Telephonic)
Jul 07, 2025
Notice of Allowance
Oct 06, 2025
Request for Continued Examination
Oct 13, 2025
Response after Non-Final Action
Oct 28, 2025
Non-Final Rejection — §101, §102, §103
Nov 06, 2025
Interview Requested

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Prosecution Projections

3-4
Expected OA Rounds
86%
Grant Probability
97%
With Interview (+10.8%)
2y 3m
Median Time to Grant
High
PTA Risk
Based on 1169 resolved cases by this examiner. Grant probability derived from career allow rate.

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