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 .
REQUEST FOR CONTINUED EXAMINATION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 2/06/2026 has been entered.
Information Disclosure Statement
The IDS filed 2/2/2022 have been considered by the Examiner. Listed references with missing citation data have been lined through.
Status of Claims
Amendments to the claims are acknowledged.
Claims 1-2, 4-6, and 8-12 are under examination.
Claims 3 and 7 are cancelled.
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under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) to US application 63/075804 filed 9/08/2020 is rescinded. Claim 1 has been amended to recite step (C) that selection of a pathogen of interest determines a Multiple Linear Regression equation and in step (D) that the Multiple Linear Regression equation determines the presence of pathogens in a biological sample. Support for a Multiple Linear Regression equation is not found in 63/075804 filed 9/08/2020. The provisional 63/075804 supports an algorithm for linear data but not explicitly a Multiple Linear Regression equation for determining a Multiple Linear Regression equation by selecting a pathogen of interest and applying the Multiple Linear Regression equation to the detection of a pathogen in a sample.
Support for claims 1-2, 4-6, 8-12 is afforded the instant filing date of 9/07/2021.
Claim Election/Restriction
Election without Traverse
Applicant’s election without traverse of Group I (claims 1-12) in the reply filed on 11/14/2024 is acknowledged.
Claims 13-21 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected Group, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 11/14/2024.
Claim Rejections - 35 USC § 101
The instant rejection is maintained from the Office action filed 11/06/2025 and modified in view of claims filed 1/6/2026.
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 1-2, 4-6, and 8-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Process, Machine, Manufacture or Composition
Claims 1-2, 4-6, and 8-12 are drawn to a method, so a process.
Step 2A Prong One: Identification of an Abstract Idea
The claim(s) recite(s):
1. receiving an indication of a biological pathogen of interest.
This step reads on the mental process of thinking and therefore is an abstract idea.
2. determining from the indication of the biological pathogen of interest a Multiple Linear Regression equation.
This step reads on a process that can be performed by the human mind and is therefore an abstract idea.
3. determining from spectrographic data and the determined Multiple Linear Regression equation, the presence of one or more biological pathogens in the sample, as in claim 1.
The instant step can be performed by the human mind as a mental analysis step or by applying the math of a Multiple Linear Regression equation. The step is therefore an abstract idea.
4. Selecting a biological pathogen of interest, as in claim 2.
The instant step can be performed by the human mind as a process of selecting information. The step is therefore an abstract idea.
5. Performing a classification procedure on the spectrographic data that determines if a specified pathogen family is present in the biological sample, as in claim 2.
The instant step of classifying can be performed by the human mind and is therefore an abstract idea.
6. performing a membership procedure on the spectrographic data that determines if at least one pathogen variant is present in a pathogen family, as in claim 2.
The instant step can be performed by the human mind as a mental analysis step. The step is therefore an abstract idea.
6. wherein performing the classification procedure comprises executing a Universal Pathogen Family Classification Model to determine the presence/absence of a pathogen family in a sample, as in claim 3.
The instant step can be performed by the human mind or with math because executing a Universal Pathogen Family Classification Model reads on classifying the family of the pathogen using math or mental analysis as exemplified in Figure 5. The step is therefore an abstract idea.
Claims 4-7 and 9-11 recite further steps that can be performed as mental processes or with math and are therefore also abstract ideas.
Step 2A Prong Two: Consideration of Practical Application
The claims are drawn to gathering data from a sample and performing an analysis to determine biological pathogens in the sample. The claims do not recite additional elements that integrate the abstract idea into a practical application.
The judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than
a drafting effort designed to monopolize the exception.
Step 2B: Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea. The recited additional elements are drawn to:
obtaining a biological sample from a subject into a receptacle, as in claim 1, step (A).
receiving the receptacle into a sample holder of a sensor box and directing light from into the receptacle containing the sample and onto a grating and then to a camera, the camera recording spectrographic data from the sample, as in claim 1, step (B).
A data processor coupled to the sensor box, as in claim 1, step (D).
Communicating the spectrographic data from the sensor unit to a results server, as in claim 8, step (C).
Receiving an exhalation of the subject through a tube into water, as in claim 12.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because analyzing a biological sample with a light senor and transmitting the results to a computer coupled with the sensor is routine, conventional and well understood. Spectroscopic methods for analyze microbes including at least RAMAN spectroscopy, NMR, Near infrared and Micro-FTIR are all well known for microbe analysis, including for viruses. Santos et al. (Trends in Analytical Chemistry vol. 97 (2017) pgs. 244-256) evidence spectroscopic techniques with computer analysis for viral studies. He et al. (E3S Web of Conferences vol. 271. EDP Sciences (2021) pgs. 1-6) teach a LAMBDA 750 UV/Vis/NIR (page 2, col. 2, par. 5) for near infrared spectroscopy which includes a sample holder, light and detector, where the “box” is typically coupled to a computer. Furthermore, collecting data by well known techniques and transmitting data to a computer for analysis is deemed to be extra solution activity as described in MPEP 2106.05(g).
Claim 1, step (B) recites receiving the receptacle with a biological sample into a holder and directing light at the receptacle and then onto a light source and camera. This limitation is an additional element however, it is tangential to the abstract idea steps. The structure of the device is not integrated with the abstract idea of selecting a Multiple Linear Regression equation and determining the presence of a biological pathogen. The recited sample holder, grating and camera do not meaningfully limit the analysis steps and are therefore deemed to be extra-solution activity and part of the data gathering. See MPEP 2016.05(g) and 2106.05(f). Furthermore, light spectroscopy with a grating in the path of the light and camera is well known as evidenced by Scheeline et al. (US 2013/0093936, see Figure 1B) and Maher (2015/0185152, par. 0049 and Figure 12)
Claim 12 pertains to collecting a pathogen sample by exhaling into a tube inserted into water which is the well-known, routine and conventional exhaled breath condensate (EBC) technique. The step is well known, routine and conventional and also an extra solution activity to the steps of data analysis which are the abstract idea.
Other elements of the method include recitation of a generic computer which is a recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed 1/06/2026 have been fully considered but they are not persuasive.
Applicants argue (Remarks, page 8, par. 2) that claim 1 defines a method using a sample box which has advantages in that the tests require no sample preparation; patients can load their own untreated saliva sample into the sensor box test port and thus highly skilled personnel are not needed. Applicants argue (Remarks, page 9, par. 1) that the invention is not simply “doing math.”
In response, Applicants are arguing a method that is tangential to the claimed abstract idea. The claims are draw to steps (claim 1 (C), (D) and (E)) that can be performed by the human mind and are therefore an abstract idea. The abstract idea recited is not related to the structure of the sample analysis device of claim 1, step (B). The sample collection device comprising sample receptacle, grating, and camera does not further limit the steps of determining a Multiple Linear Regression equation from indication of a biological pathogen and determining from the spectrographic data and Regression equation the presence of a biological pathogen. The selection of the equation and determination of the pathogen with spectrographic data can be performed with signal data from any other adequate spectrographic device. Therefore the specific structure of the device in Step (B) is tangential to the analysis which is the abstract idea.
Applicants argue (Remarks, page 9, par. 2) that the Office has rejected the spectrographic elements of claim 1 as amounting to post solution activity.
In response, the spectrograph elements were not rejected as post-solution activity. Clearly, the elements are part of the extra-solution activity of data gathering. MPEP 2016.05(g) sets forth relevant examples:
Mere Data Gathering:
i. Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989);
vi. Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis).
Applicants argue (Remarks, page 10-11) that while it is theoretically possible to do multiple linear regression in the mind using complex matrix algebra and formulas, it is highly impractical and prone to massive errors for anything except the tiniest datasets. Applicants argue that a computer is essential to perform multiple linear regression on the large sets of spectrographic data.
In response, multiple linear regression is math and therefore an abstract idea. With respect to analyzing a lot of data by math, while there is no actual step of processing robust amount of signal data, for the record, it is important to explain that analyzing a lot of data does not augment the steps being performed to analyze the data, which are abstract ideas. Computations on a lot of data performed mentally, or with paper and pencil, would take considerable time and effort, but that is, of course, the singular purpose of computers and computer networks, to perform large numbers of calculations, via algorithms, rapidly, and without error (assuming no error in user input). Although a general purpose computer can perform calculations at a rate and accuracy that can far outstrip the mental performance of a skilled artisan, the nature of the activity is essentially the same, and constitutes an abstract idea. See Bancorp Serves., L.L. C. v. Sun Life Assur. Co. of Canada (U.S.), 687 F.3d 1266,1278 (Fed. Cir. 2012) (holding that “the fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter”); see also See SiRF Tech., Inc. v. Int’l Trade Comm ’n, 601 F.3d 1319,1333 (Fed. Cir. 2010) (holding that: In order for the addition of a machine to impose a meaningful limit on the scope of a claim, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly, i.e., through the utilization of a computer for performing calculations).
For the reasons set forth above, the 35 USC 101 rejection must be maintained.
Claim Rejections - 35 USC § 112-2nd paragraph
The rejection of claim 3 under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph is withdrawn in view of Applicant’s cancelling the claim.
Claim Rejections - 35 USC § 102
The rejection of claims 1-6 and 8-10 under 35 U.S.C. 102(a) as being anticipated by Santos et al. is withdrawn in view of Applicant’s amendments filed 8/18/2025.
Claim Rejections - 35 USC § 103
The rejection of claim 7 under 35 U.S.C. 103(a) as being unpatentable over Santos et al. in view of Wang et al. is withdrawn in view of Applicant’s amendments filed 8/18/2025.
The rejection of claims 1-2, 4-6 and 8-10 under 35 U.S.C. 103(a) as being unpatentable over Santos et al. in view of He et al. is withdrawn in view of Applicant’s amendments filed 1/06/2026.
The rejection of claims 11-12 under 35 U.S.C. 103(a) as being unpatentable over Santos in view of He et al. and in view of Sawano et al. is withdrawn in view of Applicant’s amendments filed 1/06/2026.
The following rejection is necessitated by Applicant’s amendments filed 1/06/2025.
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims under 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of 35 U.S.C. 103(c) and potential 35 U.S.C. 102(e), (f) or (g) prior art under 35 U.S.C. 103(a).
Claims 1-2, 4-6 and 8-10 are rejected under 35 U.S.C. 103(a) as being unpatentable over Scheeline et al. (US 2013/0093936) in view of Santos et al. (Trends in Analytical Chemistry, vol. 97 (2017) pages 244-256) in view of He et al. (E3S Web of Conferences vol. 271 (2021) pgs. 1-6).
Scheeline et al. teach an energy dispersion device, spectrograph and method that can be used to evaluate the composition of matter on site without the need for specialized training or expensive equipment (Abstract).
Scheeline et al. teach a sample holder capable of receiving a fluid, test strip, or solid sample into the energy dispersion device (par. 0007) wherein the energy may be light (par. 0013-0014); Scheeline et al. teach that the sample may include infectious bacteria, water, food, or soil samples (par. 0002) or a living organism (par. 0043)(i.e. obtain biological sample into a receptacle), as in claim 1, step (A).
Scheeline et al. teach the spectrographic device as including a sample holder such as a cuvette, in the path of a light source (par. 0039 and Figure 1B); the path of the light includes gratings and then a camera (par. 0039-0040 and Figure 1B); the gratings can reflect or transmit light (par. 0052-0053), as in claim 1, step (B).
Sheeline et al. do not teach a sample from a subject, as in claim 1, step (A).
Sheeline et al. do not teach receiving indication of a biological pathogen of interest, as in claim 1, step (C).
Sheeline et al. do not teach determining by a processor coupled to a sensor light box, and from the indication of biological pathogen of interest, a Multiple Linear Regression equation, as in claim 1, step (D).
Sheeline et al. do not teach determining the presence of a biological pathogen from the Multiple Linear Regression equation, as in claim 1, step (E).
Santos et al. teach detecting viruses with spectroscopy (Abstract); Santos et al. teach detecting virus infection in cells (page 245, col. 1, par. 1-2)(i.e. obtaining a biological sample from a subject), as in claim 1, step (A).
Santos et al. relies on determining spectral finger print regions for biochemical species and associating spectral fingerprints (Figures 1 and 2) with certain viruses and using classification algorithms for classifying a sample (Abstract); Santos teaches using principle component analysis (PCA)(page 248, col. 2, par. 3-5 and Figures 4-5) to classify different samples. However Santos et al. do not teach Multiple Linear Regression.
Scheeline et al. and Santos et al. do not specifically teach all of claim 1, step (D), (D) and (E).
However He et al. teach detecting HIV-1 by screening serum for HIV (Abstract) with NIR spectroscopy (Abstract and Figure 4).
He et al. teach Multiple Linear Regression (MLR) in combination of PCA as part of partial least squares analysis (PLSR)(page 5, col. 1, par. 3). He et al. teach that they established the best mathematical model based on HIV-1 virus characteristic spectrum because only a few limited wavelengths are needed for NIRS (page 5, col. 1, par. 4) which makes obvious choosing the MLR based model when HIV-1 is being detected. He et al. therefore associated HIV-1 detection with multiple linear regression (i.e. receiving indication of a biological pathogen of interest and determining from the indication of the biological pathogen of interest, a Multiple Linear Regression equation), as in claim 1, step (C).
He et al. perform partial least square fitting of each segment of spectral data to diagnose HIV-1 (page 1, col. 2, par. 2). He et al. teach their method combines principle component analysis (PCA) and multiple linear regression (MLR)(page 2, col. 2, par. 6-8)(i.e. determining from the spectrographic data and the determined Multiple Linear Regression equation, the presence of one or more pathogens in the biological sample), as in claim 1, step (D).
It would have obvious to one of ordinary skill in the art at the time the invention was made to have combined the teaching of Scheeline et al. for a spectrograph device for measuring organisms in a sample with the method of Santos et al. which teach detecting virus infection in cells with spectroscopy. One or ordinary skill would be motivated to use the spectrograph device of Scheeline et al. because Scheeline et al. teach that the spectrograph and method that can be used to evaluate the composition of matter on site without the need for specialized training or expensive equipment (Abstract). One of ordinary skill would have a reasonable expectation of success at combining Scheeline et al. and Santos et al. because both teach biological sample analysis with light spectroscopy.
It would have obvious to one of ordinary skill in the art at the time the invention was made to have combined the spectral analysis and viral classification made obvious by Scheeline et al. and Santos et al. with the method of He et al. which uses Multiple Linear Regression to determining HIV-1 in a sample. Santos et al. teach that specific viral samples associated with their specific fingerprint spectra. He et al. teach Multiple Linear Regression for determining the best spectral bands associated with HIV for HIV sample classification. He et al. provide motivation by teaching that Multiple Linear Regression tries to extract the maximum information reflecting the variation of data (page 5, col. 1, par. 3). One of skill in the art would have had a reasonable expectation of success at combining Scheeline et al. and Santos et al. with He et al. because all are concerned with detecting organisms in samples with light and Santos et al. and He et al. are both concerned with the classification of samples containing viral pathogens.
Regarding dependent claims 2, 4-6 and 8-10
Santos et al. teach identifying and classifying respiratory syncytial virus (page 249, col. 1-2, connecting par.) where Raman spectra of B2, A2 and recombinant A2 G mutants (i.e. variant) are recorded (i.e. selecting a biological pathogen of interest); based on the intrinsic spectra the three viruses were detected and identified (i.e. performing a classification on the spectrographic data that determines if a specified pathogen family is present); PCA analysis was able to segregate (individually identify) the three virus strains (i.e. performing a membership procedure on the spectrographic data that determines if at least one pathogen variant is present in the family), as in claim 2.
Santos et al. teach a score plot (page 249, col. 2, par. 1 and Figure 5) for each pathogen family, as in claim 4.
Santos et al. teach creating a loading vector that represents a cluster representing a class of viruses (page 248, col. 2, section 3.21, par. 1 and page 249, col. 2, par. 1); Santo et al. teach applying principle component (PC) analysis to determine a score (page 248, col. 2, section 3.21, par. 1-2), as in claim 5.
Santos et al. teach PCA analysis was able to segregate (individually identify) the three virus strains (page 249, col. 1-2, connecting par.), as in claim 6.
Santos et al. teach coupling spectroscopic data collection with computational data analysis (page 247, col. 2, section “Computational analysis) including preprocessing the spectra (i.e. processing the spectrographic data in the results server) and determining patient samples with pathogens for display (page 249-250, Figures 5-8)(i.e. communicating results from the server to a computer coupled to the sensor unit), as in claim 8.
Santos et al. teach assigning wavelength and Intensity to spectrographic data (page 246, col. 2, Figure 1), as in claim 9.
Santos et al. teach that identifying specific viruses in microbiome of many viruses in a human (page 245, col. 1, par. 2), as in claim 10.
Claims 11-12 are rejected under 35 U.S.C. 103(a) as being unpatentable over Scheeline et al. in view of Santos in view of He et al. as applied to claims 1, 2, 4-6 and 8-10 above, and further in view of Sawano et al. (J. Breath Res. Vol. 14 (2020) pages 1-5).
Scheeline et al., Santos et al. and He et al. make obvious claims 1, 2, 4-6 and 8-10, as set forth above.
Scheeline et al. in view of Santos et al. in view of He et al. do not teach that one or more viruses comprise coronaviruses and their variants, as in claim 11.
Scheeline et al. in view of Santos et al. in view of He et al. do not teach collecting a pathogen sample by exhaling into a tube inserted into water, as in claim 12.
Sawano et al. however teach exhaled breath condensate (EBC) technique (page 3, col. 2, section “5. ECB sample collection procedure”) to collect samples of coronavirus, as in claims 11-12.
It would have obvious to one of ordinary skill in the art at the time the invention was made to have combined the spectral analysis and viral detection with MLR made obvious by Scheeline et al. in view of Santos et al. in view of He et al. with the coronavirus sample collection using EBC as taught by Sawano et al. Sawano et al. provide motivation by teaching that EBC is a promising approach for SARS-COV-2 collection (page 1, col. 2, par. 2). One of skill in the art would have had a reasonable expectation of success at combining Scheeline et al. in view of Santos et al. in view of He et al. with Sawano et al. because Santos et al., He et al. and Sawano et al. teach viral identification wherein a viral sample must first be collected.
Response to Arguments
Applicant's arguments filed 1/06/206 have been fully considered but they are not persuasive.
Applicants argue that He et al. relates only to analysis of HIV samples thus there is no indication of a pathogen of interest, selected from multiple options which would then determine a multiple linear regression equation to use in the analysis.
In response, the claims do not recite presenting multiple pathogen options wherein a user selects one and correlates that selection to a multiple regression equation out of a plurality of other models. However even so, He et al. teach prior knowledge or intention to detect HIV in a sample and therefore reads on “receiving an indication of a biological pathogen of interest.” He et al. then teach that their Partial least squares regression (PLSR) analysis which combines both PCA and MLR is the “best mathematical model based on the HIV-1 virus characteristic spectrum” (page 5, col. 1, par. 4) which therefore makes obvious selecting this particular mathematical model with MLR for the analysis of HIV-1. Furthermore it would be obvious and common sense to one of ordinary skill to select the best mathematical model for the type of data available. He et al. clearly make obvious that based on the NIRS spectral data from a sample with HIV-1, their model of choice is the PLSR comprising multiple linear regression (MLR).
The claims are therefore made obvious by Scheeline et al, in view of Santos et al. in view of He et al. as set forth above.
E-mail communication Authorization
Per updated USPTO Internet usage policies, Applicant and/or applicant’s representative is encouraged to authorize the USPTO examiner to discuss any subject matter concerning the above application via Internet e-mail communications. See MPEP 502.03. To approve such communications, Applicant must provide written authorization for e-mail communication by submitting the following statement via EFS Web (using PTO/SB/439) or Central Fax (571-273-8300):
Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.
Written authorizations submitted to the Examiner via e-mail are NOT proper. Written authorizations must be submitted via EFS-Web (using PTO/SB/439) or Central Fax (571-273-8300). A paper copy of e-mail correspondence will be placed in the patent application when appropriate. E-mails from the USPTO are for the sole use of the intended recipient, and may contain information subject to the confidentiality requirement set forth in 35 USC § 122. See also MPEP 502.03.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Anna Skibinsky whose telephone number is (571) 272-4373. The examiner can normally be reached on 12 pm - 8:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Ram Shukla can be reached on (571) 272-7035. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Anna Skibinsky/
Primary Examiner, AU 1635
Prosecution Insights