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 .
Status of Claims
Claims 1-20 are currently pending and examined on the merits.
Priority
Applicant’s claim for the benefit of a prior-filed applications 63/473,733 filed 18 June 2022 under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged and accepted.
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 4, 5, 10, 13, and 14 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 4 recites “which is performed in 6 hours or less”. It is unclear what active step or steps of claim 1 are performed in 6 hours or less. Claim 4 does not recite any active step. The specification is silent regarding the time to complete any particular steps. Further, one skilled in the art would not recognize in particular timing of the active steps.
Claim 5 recites “which is performed in 2 hours or less”. It is unclear what active step or steps of claim 1 are performed in 6 hours or less. Claim 5 does not recite any active step. The specification is silent regarding the time to complete any particular steps. Further, one skilled in the art would not recognize in particular timing of the active steps.
Claim 10 recites “…using a PCR- technology platform linked via API integration to a database of empiric antimicrobial regimens.” There is no disclosure in the claims or specification that describes the method, nor would this method be known to one of ordinary skill in the art. The specification merely repeats “a method for analyzing” without further disclosure. “A method for analyzing a biological sample…”as disclosed in claim 10 is known broadly in the art; for example, bioinformatics and computational next generation sequencing analysis methods applied to clinical genetics are described in a review from Pereira, et al (J Clin Med. 2020 Jan 3;9(1):132.). In relation to “a PCR-technology” as disclosed in claim 10, Pereira includes descriptions of PCR analysis on pg. 3 and 4 (“NGS Library”). Therefore, one of ordinary skill in the art could reasonably interpret claim 10 as a computational or bioinformatics analysis, and the examiner follows this interpretation.
Claim 13 recites “…the necessary sensitivity and resistance…” “Necessary” is a relative term which renders the claim indefinite. The term “necessary” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. See MPEP 2173.05.
Claim 14 recites “…the method of claim 13, having a sensitivity of between 90-99%.” It is unclear what active step or steps of claim 13 have a sensitivity of between 90-99%. Claim 14 does not recite any active step. The specification is silent regarding the time to complete any particular steps. Further, one skilled in the art would not recognize in particular timing of the active steps.
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 10-12 are 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 "Use" claims that do not purport to claim a process, machine, manufacture, or composition of matter fail to comply with 35 U.S.C. 101.
Claim 10 recites “…using a PCR- technology platform linked via API integration to a database of empiric antimicrobial regimens.”
Claims 11 and 12 depend on claim 10
Attempts to claim a process without setting forth any steps involved in the process generally raises an issue of indefiniteness under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. For example, a claim which read: "[a] process for using monoclonal antibodies of claim 4 to isolate and purify human fibroblast interferon" was held to be indefinite because it merely recites a use without any active, positive steps delimiting how this use is actually practiced. Ex parte Erlich, 3 USPQ2d 1011 (Bd. Pat. App. & Inter. 1986). See MPEP 2173.05(q).
Claims 1-9 and 13-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental steps, mathematic concepts, organizing human activity, or a natural law without significantly more.
Step 2A, Prong 1
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/law of nature/natural phenomenon:
Claim 1 recites:
“…identifying a microorganism in a biological sample…”, which is a mental step, i.e. could be performed with pen and paper, as one of ordinary skill in the art could, for example, visually discern infected biological tissue from non-infected biological tissue.
“… performing molecular amplification analysis…”, which is a mental step, i.e. could be performed with pen and paper, as one of ordinary skill in the art could, for example, draft an analysis of amplified DNA without computational means.
“…identifying one or more pathogens…”, mental step;
“… identifying empiric antibiotic therapy…”, mental step;
Claim 2 recites: “…wherein the molecular amplification analysis on a biological sample is a PCR-based technique.” , which further limits the type of infection identified by the mental step of claim 1.
Claim 3 recites: “The method of claim 1wherein the pathogen comprises one or more of a bacterium, a virus, a fungus, or a parasite.”, which further limits the type of infection identified by the mental step of claim 1.
Claim 4 recites: “The method of claim 1 which is performed in 6 hours or less.”, which further limits the method of identifying mental step of claim 1.
Claim 5 recites: “The method of claim 1 which is performed in 2 hours or less.” , which further limits the method of identifying mental step of claim 1.
Claim 6 recites: “…wherein the biological sample is selected from the group consisting of blood, blood components, nasal swabs, sputum, saliva, stool, urine, throat swabs, vaginal swabs, abscess fluid, or wound swabs.” , which further limits the method of identifying mental step of claim 1.
Claim 7 recites, “… determining a genetic variation which identifies drug resistance.”; mental step
Claim 8 recites: “…wherein the empiric antibiotic therapy is an oral antibiotic.” , which further limits the method of identifying mental step of claim 1.
Claim 9 recites, “…point of care testing”; mental step.
Claim 11 recites: “…wherein the PCR technology platform is integrated with data management systems, locally, regionally and nationally to allow for effective epidemiological surveillance, antibiotic selection, and control of disease outbreaks.” , which further limits the method of identifying mental step of claim 10.
Claim 12 recites: “…, wherein the API integration permits a user to search, navigate, and reference empiric oral antimicrobial regimens without exiting the PCR- technology platform.” , which further limits the method of identifying mental step of claim 10.
Claim 13 recites, “…one or more pathogens are identified…” and “…the report is generated and sent to a physician or a patient for review…”, mental step
Claim 14 recites: “…having a sensitivity of between 90-99%.” , which further limits the method of identifying mental step of claim 13.
Claim 15 recites: “…having a turnaround time from a collection of a biological specimen to having a report generated is less than two hours.” , which further limits the method of identifying mental step of claim 13.
Claim 16 recites: “…further comprising a PCR method for identifying mutation loci that confer resistance to antibiotics..” , which further limits the method of identifying mental step of claim 13.
Claim 17 recites: “…a kit.”, which further limits the method of identifying mental step of claim 13.
Claim 18 recites: “…wherein the report is captured in the patient's electronic medical record via API or is captured in local and international surveillance databases.” , which further limits the method of identifying mental step of claim 18.
Claim 19 recites: “…comprising a kit having connectivity through the Cloud, an App, a computer, artificial intelligence (AI) or through other electronic means..” , which further limits the method of identifying mental step of claim 13.
Claim 20 recites: “…wherein the API integration is implemented in computer system selected from the group consisting of a desktop computer, a laptop computer, a server computer, a tablet computer, a smart phone or a mobile device..” , which further limits the method of identifying mental step of claim 13.
The claims recite an abstract idea of analyzing and generating reports about microorganisms (See MPEP 2106.07(a)).
These recitations are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or mathematical relationships. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas.
There are no additional limitations that indicate that the methods referenced in claims 1-20 require 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, claim(s) 1-20 recite(s) an abstract idea (Step 2A, Prong 1: YES).
Step 2A, Prong 2
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 applies or uses the recited judicial exception to affect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment. Specifically, the claims recite the following additional elements:
Claim 1 recites “… conducting API integration with an empiric antibiotic database…”
Claim 13 recites:
“…a kit…”
“…API integration with the Laboratory Information Management System (LIMS) system…”
“…the identified pathogen is processed in LIMS…”
“… API integration with an empiric antimicrobial database…”
“…the LIMS system integrates details that correspond with the pathogen present onto a report…”
Claim 18 recites: “…electronic medical record…” and “…international surveillance databases…”
Claim 19 recites: “…the Cloud, an App, a computer, artificial intelligence (AI) or through other electronic means…”
Claim 20 recites: “…a desktop computer, a laptop computer, a server computer, a tablet computer, a smart phone or a mobile device.”
There are no limitations that indicate that the claimed analysis engine 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 (see MPEP 2106.05). As such, claims 1-20 is/are directed to an abstract idea (Step 2A, Prong 2: NO).
Step 2B
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). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment. The instant claims recite the following additional elements:
Claim 1 recites,
“… obtaining a biological sample from a patient…”
“… extracting DNA from the sample…”
Claim 13 recites,
“…DNA is extracted from a cell and subject to a PCR amplification process…”
Regarding claims 1, 7, and 13, The steps of obtaining sequencing data and performing sample collection do not integrate the abstract idea into a practical application and constitutes an insignificant extra-solution activity (i.e., data gathering and presentation), which does not impose a meaningful limit on the abstract idea (see MPEP 2106.05(g)). As discussed above, there are no additional limitations to indicate that the claimed analysis engine requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims.
Furthermore, the additional elements recited in the claims amount to well-understood, routine and conventional activity, as evidenced by reviews from Ghaheri, et al. (Cell. Mol. Biol.2016, 62 (3): 120-124) and Koshy, et al., (Mol Biol Rep 44, 97–108 (2017).
Ghaheri, et al. is directed to a comparative evaluation of four DNA extraction protocols from whole blood samples, including the PCR amplification process.
Koshy, et al. is directed to an evaluation of genomic DNA extraction methods from human whole blood using PCR assays.
The 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 1-9 and 13-20 is/are not patent eligible.
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.
Claim(s) 1-3, 6, 7, and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Lipkin et al. (WO 2019226992A1), in view of Kaur et al. (Sci Rep. 2021 May 27;11(1):11226.)
Regarding claims 1 and 10, Lipkin et al. discloses a system and method for the simultaneous detection, identification and/or characterization of pathogenic bacteria known or suspected to infect vertebrates and antimicrobial resistant genes or biomarkers comprising obtaining a biological sample and sequencing with PCR (specification, Example 6; Figure 3, clm. 46; spec, “PCR”; clm. 1, clm. 18-23, specification [Pathogenic Bacteria and Antimicrobial Resistant Genes], re: clm. 1, A method for identifying a microorganism in a biological sample comprising: obtaining a biological sample from a patient suspected of being infected with a pathogen; extracting DNA from the sample; performing molecular amplification analysis; identifying one or more pathogens…clm. 10, … analyzing a biological sample for pathogens comprising using a PCR- technology platform l)
Lipkin et al. does not teach conducting API integration with an empiric antibiotic database or identifying antibiotics for therapy/regimens (re: clm. 1, …conducting API integration with an empiric antibiotic database; and identifying empiric antibiotic therapy…, clm. 10, … analyzing a biological sample for pathogens comprising using a PCR- technology platform linked via API integration to a database of empiric antimicrobial regimens.)
Kaur et al. teaches a integrating a python-based web API using a computerized system with a database associated with clinical and antimicrobial resistance data. Kaur et al details an antibiotics database derived from Laboratory and Hospital Information systems (LIS-HIS), stating in their methods:
“Based upon the comprehensive analysis of the data from LIS and HIS of various hospitals in the network, it was concluded that the data is mainly exported in two formats: (a) the format with antibiotics names in rows (file comprises the antibiotic names and their corresponding susceptibility test values in the multiple respective rows) (supplementary Fig. 1a); (b) the format with antibiotic names as column headers (the file contains antibiotic names as multiple column headers and corresponding susceptibility test values are present in the respective rows) (supplementary Fig. 1b).” (Introduction, Fig. 2, Methods, re: clm. 1, … conducting API integration with an empiric antibiotic database… clm. 10, …platform linked via API integration to a database of empiric antimicrobial regimens.)
In KSR Int 'l v. Teleflex, the Supreme Court, in rejecting the rigid application of the teaching, suggestion, and motivation test by the Federal Circuit, indicated that “The principles underlying [earlier] cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.” KSR Int'l v. Teleflex lnc., 127 S. Ct. 1727, 1740 (2007).
Applying the KSR standard of obviousness to Lipkin et al. and Kaur et al., the Examiner concludes
method of identifying pathogenic bacteria as taught by Lipkin et al. with the clinical and antimicrobial resistance data API database as taught by Kaur et al. represents Some Teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention, with no more than a predictable outcome of a method of identifying pathogenic bacteria as related to an antimicrobial resistance database with an API.
One would have been motivated to combine the teachings of Lipkin et al. and Kaur et al. because the resultant combination would lead to a stronger method of identifying a pathogenic, antibiotic resistant organism that impacts public health (in address of Kaur et al.’s declaration of antimicrobial resistance being a “global health emergency” on pg. 1).
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success of combining the teachings of Lipkin et al. and Kaur et al. because both arts teach computational analysis and characterization of antibiotics as they relate to pathogens. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
In regards to claim 2, Lipkin et al. discloses a system and method for the simultaneous detection, identification and/or characterization of pathogenic bacteria known or suspected to infect vertebrates and antimicrobial resistant genes or biomarkers comprising obtaining a biological sample and sequencing with PCR (Lipkin et al, spec, “PCR”; clm. 18-23, specification [Pathogenic Bacteria and Antimicrobial Resistant Genes], re: clm. 2, wherein the molecular amplification analysis on a biological sample is a PCR-based technique. As Lipkin et al teaches PCR, Lipkin teaches the limitations of claim 2.
In regards to claim 3, Lipkin et al. discloses a system and method for the simultaneous detection, identification and/or characterization of pathogenic bacteria (Lipkin et al., specification, Example 6; Figure 3, clm. 46, re: clm. 3, wherein the pathogen comprises one or more of a bacterium, a virus, a fungus, or a parasite). As Lipkin et al. detects bacteria, Lipkin et al. teaches the limitations of claim 3.
In regards to claim 6, Lipkin et al. discloses obtaining a biological sample from blood (clm. 24, spec, “The Bacterial Capture Sequencing Platform” re: clm. 6, wherein the biological sample is selected from the group consisting of blood, blood components, nasal swabs, sputum, saliva, stool, urine, throat swabs, vaginal swabs, abscess fluid, or wound swabs.) As Lipkin et al. obtains a blood sample, Lipkin et al. teaches the limitations of claim 6.
In regards to claim 7, Lipkin et al. discloses PCR-based antibiotic selection using the Comprehensive Antibiotic Resistance Database (CARD). The Comprehensive Antibiotic Resistance Database (CARD) is a bioinformatic database of resistance genes, their products and associated phenotypes, including lists of single nucleotide polymorphisms and/or genetic mutations associated with antibiotic resistance. In their specification, Lipkin et al. states:
“BacCapSeq platform is ideally suited for analyses of genome composition and dynamics and will enable transition of high throughput sequencing to clinical diagnostic as well as research applications…”
Therefore, Lipkin et al. integrates PCR with a data management system capable of identifying bacterial resistant genes and mutations (Spec, “Summary of the invention”, re: clm. 7, … determining a genetic variation which identifies drug resistance). Lipkin et al. teaches the limitations of claim 7.
In regards to claim 9, Yancey discloses in the specification:
“In one embodiment, a means for monitoring antibiotic/antimicrobial usage patterns in the hospital in the form of a database and a means for correlating that database with hospital bacterial resistance patterns are provided in the systems and methods of the invention.”
Yancey therefore teaches maintaining a clinically-relevant, empiric antibiotic database, and additionally teaches computationally identifying empiric antibiotic therapy communicated from physicians, including at sites of patient care. (re: clm. 9, …comprising point of care testing…). Yancey teaches the limitations of claim 9.
In regards to claim 11, Lipkin et al. discloses PCR-based antibiotic selection with BacCapSeq using the Comprehensive Antibiotic Resistance Database (CARD), an online database (Spec, “Summary of the Invention”). As previously mentioned, Lipkin et al. integrates PCR with CARD to identify bacterial resistant genes and mutations (clm. 2, “Comprehensive Antibiotic Resistance Database (CARD)”, spec: “BacCapSeq was used to pursue biomarkers in bacteria exposed to antibiotics…”). CARD is an online database of McArthur et al. containing publications through sources including PubMed (as disclosed in their materials and methods), which has no regional or national limit (as evidenced by McArthur et al.). Additionally, McArthur et al. discloses in their methods the identification of antibiotic resistance terms and state in their introduction:
“Surveys of genes originating from both clinical and environmental sources (microbes and metagenomes) will provide increasing insight into these reservoirs and offer predictive capacity for the emergence and epidemiology of antibiotic resistance.”,
Thereby disclosing epidemiological applications.
Therefore, Lipkin et al. teaches a PCR technology platform with a data management system and therefore teaches the limitations of claim 11 (re: clm. 11, wherein the PCR technology platform is integrated with data management systems, locally, regionally and nationally to allow for effective epidemiological surveillance, antibiotic selection, and control of disease outbreaks).
Claim(s) 12 is rejected under 35 U.S.C. 103 as being unpatentable over Lipkin et al. and Kaur et al. as evidenced by McArthur et al. as applied to claims 1-3, 6, 7, and 9-11, and in view of Robert W Yancey, Jr. (US 8374797B2).
Lipkin et al. and Kaur et al. as evidenced by McArthur et al. are applied to claims 1-3, 6, 7, and 9-11.
Regarding claim 12, Lipkin et al. teaches that their bacterial capture sequencing platform can be searchable, stating in their specification:
“The bacterial capture sequencing platform can also be in the form of a database or databases which can include information regarding the sequence and length and Tm of each oligonucleotide probe, and the bacterium from which the oligonucleotide sequence derived as well as antimicrobial resistant genes and virulence factors. The database can searchable. “ Furthermore, Lipkin et al. discloses PCR-based antibiotic selection with BacCapSeq using the Comprehensive Antibiotic Resistance Database (CARD), an online database (Spec, “Summary of the Invention”). Lipkin et al. integrates PCR with CARD to identify bacterial resistant genes and mutations (clm. 2, “Comprehensive Antibiotic Resistance Database (CARD)”, spec: “BacCapSeq was used to pursue biomarkers in bacteria exposed to antibiotics…”). CARD is an online database of McArthur et al. containing publications through sources including PubMed (as disclosed in their materials and methods), which has no regional or national limit and is searchable (as evidenced by McArthur et al., pg. 3353, re: clm. 12, … search, navigate, and reference…)
Lipkin et al. does not teach conducting API integration with an empiric antibiotic database or identifying antibiotics for therapy/regimens (re: clm. 12 …wherein the API integration permits a user to search, navigate, and reference empiric oral antimicrobial regimens without exiting the PCR- technology platform.).
As previously mentioned, Kaur et al. teaches a integrating a python-based web API using a computerized system with a database associated with clinical and antimicrobial resistance data (Introduction, Fig. 2, Methods)/ Kaur et al. is an API integration operating independently of a PCR-technology platform. Therefore, it would be reasonable to conclude a user could perform or would be permitted to perform actions independent of the API integration (re: clm. 12, … wherein the API integration permits a user to search, navigate, and reference empiric oral antimicrobial regimens without exiting the PCR- technology platform.)
Kaur et al. does not teach conducting API integration explicitly to identify an antibiotic therapy or to a database of empiric antimicrobial regimens (re: clm. 12, … wherein the API integration permits a user to search, navigate, and reference empiric oral antimicrobial regimens without exiting the PCR- technology platform.)
Yancey discloses a computational information processing system for establishing at least one preferred and/or recommended antibiotic regimen for a patient (Abstract). Yancey discloses in the specification: “The major cause of inappropriate antibiotic therapy is the complexity of the prescribing process. There are more than 90 parental and oral antibiotics from which to choose.” To address this, Yancey describes “A hospital-based application of a method for administering preferred antibiotic regimens to patients is illustrated in FIG. 1. In FIG. 1, a multidisciplinary antimicrobial therapy team (MATT) is established…” in which “In certain embodiments, MATT members provide data input into a program storage device. Data provided by MATT members include… drug of choice given the final identification and sensitivities of infecting bacteria; recommendations of duration of antibiotic therapy based upon the clinical situation; antibiotic streamlining programs; oral medications programs…”
Oral medication programs read on oral antibiotics. It would be reasonable for one to apply Yancey’s teaching towards the development of an oral antibiotic regimen. (re: clm. 12, … reference empiric oral antimicrobial regimens…).
Yancey does not teach API integration.
Applying the KSR standard to Lipkin et al., Kaur et al., and Yancey, the examiner concludes that the combination of the system and method for the simultaneous detection, identification and/or characterization of pathogenic bacteria known or suspected to infect vertebrates and antimicrobial resistant genes or biomarkers comprising obtaining a biological sample according to Lipkin et al., with the API according to Kaur et al., and the antibiotic database and antibiotic therapy treatment selection as taught by Yancey represents Some Teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention, with no more than a predictable outcome of, which would yield the predictable result of a method for identifying a microorganism in a biological sample comprising: obtaining a biological sample from a patient suspected of being infected with a pathogen; extracting DNA from the sample; performing molecular amplification analysis; identifying one or more pathogens; conducting API integration with an empiric antibiotic database, and searching for and identifying empiric antibiotic therapy which is sent for review by a physician.
One of ordinary skill in the art of bioinformatics and clinical diagnostics would have been motivated to combine Lipkin et al.’s sample collection method, Kaur et al.’s API, and Yancey’s antibiotic regimen and communication system as the resultant combination would lead to a stronger method of identifying a pathogen and antibiotic therapy regimen to address said pathogen.
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because the teachings of Lipkin et al., Kaur et al. and Yancey disclose computationally-based or computational-adjacent healthcare-related data collection and analysis or database management. Combining Kaur et al.’s API, Yancey’s diagnostic method, and Lipkin et al.’s sample collection system and methods would allow one skilled in the art of clinical diagnostic to more efficiently analyze, diagnose, and ascertain treatment for bacterial infections, for example. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Claims 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Lipkin et al., Kaur et al., and Yancey as applied to claims 1-3, 6, 7, and 9-12 above, and in view of Jarvius et al. (US10655188B2).
Lipkin et al., Kaur et al., and Yancey are applied to claims 1-3, 6, 7, and 9-12 above.
Regarding claims 4 and 5, the examiner interprets the act as identifying a microorganism in a biological sample within 6 hours or less.
Jarvius et al. discloses a method for detecting and characterizing a microorganism in a clinical sample from a subject or patient having or suspected of having or at risk from sepsis using PCR (Abstract, clm. 1, clm. 3) and further teaches rapid antibiotic susceptibility tests which may occur hours after bacterial culture, stating in the specification:
“Advantageously, a rapid AST test is performed. Accordingly, in a preferred embodiment…may give a result in 8, 7, or 6 hours or less, for example in 4 or 5 hours or less.” (Specification, clm. 4, The method of claim 1… performed in 6 hours or less, clm. 5, … The method of claim 1… performed in 2 hours or less).
Therefore, Jarvius et al. teaches all limitations of claims 4 and 5.
Applying the KSR standard to Jarvius et al., Lipkin et al., Kaur et al., and Yancey, the examiner concludes that the combination of the method of pathogenic identification via a bacterial capture sequencing platform as taught by Lipkin et al. with the system and method for detecting and characterizing a microorganism in a clinical sample from a subject or patient having or suspected of having or at risk from sepsis according to Jarvius et al., with the API according to Kaur et al., and the antibiotic database and antibiotic therapy treatment selection as taught by Yancey represents Some Teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention, with no more than a predictable outcome of a method for identifying a microorganism in a biological sample comprising: obtaining a biological sample from a patient suspected of being infected with a pathogen; extracting DNA from the sample; performing molecular amplification analysis; identifying one or more pathogens within 6 hours or less; conducting API integration with an empiric antibiotic database, and identifying empiric antibiotic therapy which is sent for review by a physician.
One of ordinary skill in the art of bioinformatics and clinical diagnostics would have been motivated to combine Jarvius et al.’s sample analysis method, Kaur et al.’s API, and Yancey’s antibiotic regimen and communication system as the resultant combination would become more efficient in that pathogen identification would be rapid (within 6 hours or less). The efficiency aligns with motivations disclosed by Jarvius et al. discloses in their specification:
“In the context of treatment of a microbial infection, it can therefore be desirable, and indeed important, to have information regarding the nature of the infecting microorganism and its antimicrobial susceptibility profile in order both to ensure effective treatment … This is particularly so in the case of serious or life-threatening infections in which rapid effective treatment is vital.”
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because the teachings of Jarvius et al., Kaur et al. and Yancey disclose computationally-based or computational-adjacent healthcare-related data collection and analysis or database management. Therefore, claims 4 and 5 of invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lipkin et al. in view of Kaur et al. view of Yancey, Jr. as applied to claims 1-7, and 9-12 above and in view of Catalán et al. (Nat Commun 13, 2917 (2022).
Lipkin et al., Kaur et al. and Yancey Jr. are applied to claims 1-7, and 9-12 above.
As previously disclosed above, Yancey teaches computationally identifying empiric antibiotic therapy communicated from physicians, including at sites of patient care (Spec).
Lipkin et al., Kaur et al. and Yancey Jr. do not explicitly teach an oral antibiotic (re: clm. 8, … empiric antibiotic therapy is an oral antibiotic.)
In regards to claim 8, Catalán et al. teaches ATLAS (Antimicrobial Testing Leadership and Surveillance), a database with 6.5M minimal inhibitory concentrations (MICs) for 3,919 pathogen-antibiotic pairs isolated from 633k patients (with patient metadata) in 70 countries between 2004 and 2017. One skilled in the art could reasonably search said database and select oral antibiotics. (Abstract, data availability, discussion, re: clm. 8, … empiric antibiotic therapy is an oral antibiotic.)
Applying the KSR standard to Lipkin et al., Kaur et al., Yancey and Catalán et al. the examiner concludes that the combination of computationally identifying empiric antibiotic therapy according to Yancey with Antimicrobial Testing Leadership and Surveillance according to Catalán et al. represents Some Teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention, with no more than a predictable outcome of ,an oral antibiotic therapy using an oral antibiotic identified from an antibiotic database as related (via API) to a method of identifying and analyzing a microorganism.
One of ordinary skill in the art of bioinformatics and clinical diagnostics would have been motivated to combine Yancey’s therapy, Catalán et al.’s database, Lipkin et al.’s microorganism identification method and Kaur et al.’s API as the combination would result in a stronger pathogen identification and treatment method. Yancey explicitly supports this motivation in their specification, stating: “The major cause of inappropriate antibiotic therapy is the complexity of the prescribing process. “ Catalán et al.’s database could provide an avenue to reduce this complexity by providing minimal inhibitory concentrations such that the most effective dose of antibiotic is prescribed by a health practitioner.
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because the claimed elements exist in the same field of antibiotic analysis or assessment which seek to improve antibiotic efficacy—the teachings of Catalán et al. and Yancey disclose antibiotic database management, for example. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Claim(s) 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Lipkin et al. in view of Kaur et al. in view of Yancey in view of Catalán et al. in view of Craig et al. (ACS Synth Biol. 2017 Dec 15;6(12):2273-2280).
In regard to claim 13, as previously stated, “necessary” is indefinite. The necessary sensitivity and resistance could reasonably be interpreted as a dose of antibiotic effective enough to reduce or eradicate a pathogen. The examiner follows this interpretation.
Lipkin et al. discloses a system and method for the simultaneous detection, identification and/or characterization of pathogenic bacteria known or suspected to infect vertebrates and antimicrobial resistant genes or biomarkers comprising obtaining a biological sample and sequencing with PCR (specification, Example 6; Figure 3, clm. 46; spec, “PCR”; clm. 1, clm. 18-23, specification [Pathogenic Bacteria and Antimicrobial Resistant Genes], re: clm. 13, … A method of identifying a microorganism in a biological sample comprising: a biologic specimen is collected from a patient; DNA is extracted from a cell and subject to a PCR amplification process; one or more pathogens are identified)
Lipkin et al. does not teach an API.
Kaur et al. teaches a integrating a python-based web API using a computerized system with a database associated with clinical and antimicrobial resistance data. Kaur et al details an antibiotics database derived from Laboratory and Hospital Information systems (LIS-HIS), stating in their methods:
“Based upon the comprehensive analysis of the data from LIS and HIS of various hospitals in the network, it was concluded that the data is mainly exported in two formats: (a) the format with antibiotics names in rows (file comprises the antibiotic names and their corresponding susceptibility test values in the multiple respective rows) (supplementary Fig. 1a); (b) the format with antibiotic names as column headers (the file contains antibiotic names as multiple column headers and corresponding susceptibility test values are present in the respective rows) (supplementary Fig. 1b).” (Introduction, Fig. 2, Methods, re: …API integration… an empiric antimicrobial database…).
Kaur et. al does not teach an antibiotic regimen.
Yancey discloses a computational information processing system for establishing at least one preferred and/or recommended antibiotic regimen for a patient, and further discloses an embodiment that teaches computationally identifying empiric antibiotic therapy communicated from physicians, including at sites of patient care. (clm. 1, Spec, “…Communications by the system of the invention with the physician/clinician occur during possible stages in the patient's clinical course…”, re: clm. 13, … the report is generated and sent to a physician or a patient for review…). Yancey additionally generates a report based on patient data and involving physician review (clm. 1), and additionally states in the specification:
“In one embodiment, a report is communicated to a physician/clinician, wherein the report contains clinical data and a listing of preferred antibiotic/antimicrobial regimens along with the rationale behind why the regimens are preferred.” (re: clm. 13, … details that correspond with the pathogen present onto a report…)
Yancey et al does not teach a dose of antibiotic effective enough to reduce or eradicate a pathogen (re: clm. 13, … an empiric antimicrobial database identifies the pathogen and the necessary sensitivity and resistance…).
Catalán et al. teaches ATLAS (Antimicrobial Testing Leadership and Surveillance), a database with 6.5M minimal inhibitory concentrations (MICs) for 3,919 pathogen-antibiotic pairs isolated from 633k patients (with patient metadata) in 70 countries between 2004 and 2017. MICs read on a dose of antibiotic effective enough to reduce or eradicate a pathogen (Abstract, data availability, discussion, re: clm. 13, … an empiric antimicrobial database identifies the pathogen and the necessary sensitivity and resistance...).
Lipkin et al, Kaur et al., Catalán et al, and Yancey do not disclose a Laboratory Information Management System (LIMS) system.
In regard to claim 13, Craig, et al. teaches a laboratory information management system (Craig, et al. Fig. 2, re: clm. 13, … API integration with the Laboratory Information Management System (LIMS) system.
Craig et al. does not explicitly disclose API integration, microorganism identification, or reporting (re: clm. 13, identifying a microorganism in a biological sample comprising: a biologic specimen is collected from a patient; DNA is extracted from a cell and subject to a PCR amplification process; one or more pathogens are identified; API integration with the Laboratory Information Management System (LIMS) system; the identified pathogen is processed in LIMS; API integration with an empiric antimicrobial database identifies the pathogen and the necessary sensitivity and resistance; the LIMS system integrates details that correspond with the pathogen present onto a report; and the report is generated and sent to a physician or a patient for review …API integration with the Laboratory Information Management System (LIMS) system).
Applying the KSR standard to Lipkin et al., Kaur et al., Yancey, Catalán et al., and Craig et al., the examiner concludes that the combination of the system and method for the simultaneous detection, identification and/or characterization of pathogenic bacteria comprising obtaining a biological sample according to Lipkin et al., with the API according to Kaur et al., the antibiotic database with minimal inhibitory concentrations as taught by Catalán et al., the patient antibiotic regimen system as taught by Yancey, and the LIMS taught by Craig et al. represents Some Teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention, with no more than a predictable outcome of, which would yield the predictable result of a method for identifying a microorganism in a biological sample comprising: obtaining a biological sample from a patient suspected of being infected with a pathogen; extracting DNA from the sample; performing molecular amplification analysis; identifying one or more pathogens, and processing pathogens in an API integrated LIMS also integrated with an empiric antibiotic database, and identifying a dose of antibiotic effective enough to reduce or eradicate the pathogen.
One of ordinary skill in the art of bioinformatics and clinical diagnostics would have been motivated to combine Lipkin et al.’s sample collection method, Kaur et al.’s API, and Catalán et al.’s antibiotic database, Yancey’s regimens, and Craig et al.’s LIMS as the combination would lead to a stronger method of identifying and choosing a treatment designed in consideration of a microorganism in a biological sample. Lipkin et al. supports this motivation as Lipkin et al. states in their specification a desire for “accurate differential diagnosis of bacterial infections” (Spec, background).
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success in combining the teachings of Lipkin et al., Kaur et al., Yancey, Catalán et al., and Craig et al. because the teachings use similar methods of analyzing/storing data from microorganisms combining the aforementioned arts would generate a more robust process applicable to a range of pathogens and their associated antibiotic dosages. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Regarding claim 14, “a sensitivity” is indefinite and interpreted as a detection sensitivity of identifying a microorganism.
Lipkin et al. discloses in the specification that their invention meets the criteria of having a detection sensitivity of at least 90%, stating:
“Cockerill et al. and Lee et al. have suggested that 80 ml of blood in four separate collections of at least 20 ml of blood are required for 99% test sensitivity in detecting viable bacteria. Current estimates of BacCapSeq sensitivity (a minimum of 40 copies per ml) corresponded favorably to the 80 ml sample volume recommended in culture tests (Lee et al. 2007).”
Therefore, Lipkin et al. teaches the limitations of claim 14.
Regarding claim 15, Yancey et al teaches one embodiment including point of care assessment (a patient being treated by a physician in a hospital, for example), stating in the specification:
“The educational nature of the subject invention further improves the general treatment of infections by improving early detection and treatment of serious infections, improving patient survival, and shortening patient length of stay. Unlike other antimicrobial control and stewardship programs, the system of the invention does not attempt to dictate to physicians/clinicians their antimicrobial choice, but merely to educate physicians regarding hospital ecology and antimicrobial pharmacokinetics as they relate to the individual patient. The information is presented in such a way to be of obvious and immediate clinical relevance at the point of usage.” (Yancey, Spec).
Under the broadest reasonable interpretation, point of care reports can be generated immediately. Therefore, Yancey teaches the limitations of claim 15 (re: clm. 15, …having a turnaround time from a collection of a biological specimen to having a report generated is less than two hours).
Regarding claim 16, Lipkin et al.’s usage of PCR and the CARD database as previously disclosed inherently includes mutation loci conferring resistance to antibiotics as evidenced by the methods of McArthur et al. which state:
“For antibiotic resistance involving specific mutations (i.e., single nucleotide polymorphisms [SNPs]), [Antibiotic Resistance Ontology] terms are additionally associated with hidden Markov models (HMMs), alignment reference sequences, and position-specific SNPs for positional alignment of sequences and detection of position-specific SNPs.” (re: clm. 16, …further comprising a PCR method for identifying mutation loci that confer resistance to antibiotics.)
Therefore, Lipkin et al. teaches the limitations of claim 16.
Regarding claim 17, Lipkin et al. teaches “kits described herein” (Abstract, re: clm. 16, …comprising a kit). Therefore, Lipkin et al. teaches the limitations of claim 17.
Regarding claim 18, Yancey teaches in their specification:
“In one embodiment, a means for monitoring antibiotic/antimicrobial usage patterns in the hospital in the form of a database and a means for correlating that database with hospital bacterial resistance patterns are provided in the systems and methods of the invention.”
Yancey additionally teaches a “communicated to a physician/clinician, wherein the report contains clinical data and a listing of preferred antibiotic/antimicrobial regimens along with the rationale behind why the regimens are preferred.” (Spec). Under the broadest reasonable interpretation Yancey’s report could be captured in local hospital surveillance of microbial resistance (re: clm. 18, … wherein the report is captured in the patient's electronic medical record via API or is captured in local and international surveillance databases.). Yancey teaches the limitations of claim 18.
Regarding claim 19, Lipkin et al. teaches a kit connected to a computer, stating in their specification:
“Kits of the subject invention may include any of the above-mentioned reagents, as well as reference/control sequences that can be used to compare the test sequence information obtained, by for example, suitable computing means based upon an input of sequence information.” (Spec, re: clm. 19, … comprising a kit having connectivity through the Cloud, an App, a computer, artificial intelligence (AI) or through other electronic means.). Lipkin et al. teaches the limitations of claim 19.
Regarding claim 20, Kaur et al. teaches in their architecture section: “The complete system is hosted on Ubuntu 16.04 operating system using the apache web server.” (re: clm. 20, … wherein the API integration is implemented in computer system selected from a server computer…). Kaur et al. teaches the limitations of claim 20.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN T STUBBS whose telephone number is (571)272-0340. The examiner can normally be reached M-F 8-5 EST.
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/J.T.S./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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