DETAILED ACTION
Acknowledgements
This office action is in response to the claims filed November 19, 2024.
Claims 1-20 are pending.
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 .
Information Disclosure Statement(s)
The information disclosure statement (IDS) submitted on 11/19/2024 and 04/02/2025 were considered by the examiner.
Claim Objections
Claim 10 is objected to because of the following informalities: claim 10 recites “The computer implemented method as claimed in claim 8”. Claim 8 is a system claim and it appears claim 10 should instead depend from claim 9. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected to under 35 U.S.C 101 as not being directed to eligible subject matter based on the grounds set out in detail below:
Independent Claims 1, 9, and 11:
Eligibility Step 1 (does the subject matter fall within a statutory category?):
Independent claims 1 falls within the statutory category of machine.
Independent claim 9 falls within the statutory category of method.
Independent claim 11 falls within the statutory category of machine.
Eligibility Step 2A-1 (does the claim recite an abstract idea, law of nature, or natural phenomenon?): Independent claims 1, 9, and 11 (claim 1 being representative) claimed invention is directed to an abstract idea without significantly more.
The claim elements which set forth the abstract idea in the independent claims (claim 1 being representative) is:
diagnostic assessments
receive one or more samples from body of a person having information of that body;
determine one or more parameter based on the information from the one or more samples;
compare the determined one or more parameters with predefined parameters;
determine a health related information of the human body based on the comparison;
and determine a predictive analysis risk predictions, comorbidity alerts, decision support for doctors, corporates and government, based on the health related information;
send the health related information to the person, health organisations and other stake holders.
This abstract idea is “certain methods of organizing human activity” as it is managing personal behavior and following rules and instructions to determine and send diagnosis information for a patient (MPEP § 2106.04(a)(2), subsection II)
Eligibility Step 2A-2 (does the claim recite additional elements that integrate the judicial exception into a practical application?): For Independent claims 1, 9, and 11 judicial exception is not integrated into a practical application.
In Claim 1 the additional elements are:
A computer system comprising one or more medical instrument sensors
a memory unit configured to store machine-readable instructions
a processor
a communication network
one or more user devices
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional element (a) is recited as tools or equivalent to apply the abstract idea as “apply-it” to gather data
The additional element, (b), is recited as tools or equivalent to apply the abstract idea as “apply-it” to store data
The additional element (c) is executing the abstract idea and recited as tools or equivalent to apply the abstract idea as “apply-it” to analyze data
The additional element (d) is recited as tools or equivalent to apply the abstract idea as “apply-it” to communicate data
The additional element (e) is recited as tools or equivalent to apply the abstract idea as “apply-it” to communicate data
In Claim 9 there are no additional elements not already recited in independent claim 1 therefore purely treated as the abstract idea.
In Claim 11 the additional elements not already recited in the independent claim 1 are:
A portable medical device
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional element (a) is executing the abstract idea and recited as tools or equivalent to apply the abstract idea as “apply-it” to gather, store, and analyze data
Eligibility Step 2B (Does the claim amount to significantly more?): The independent claims do not include additional elements sufficient to amount to significantly more than the judicial exception because as analyzed above in step 2A prong 2 above, these additional elements, whether viewed individually or as an ordered combination, amount to no more than applying the abstract idea thus insufficient to provide “significantly more”. Therefore, the claim does not amount to significantly more and the claim is ineligible.
Dependent Claims 2-8, 10, and 12-20:
Eligibility Step 1 (does the subject matter fall within a statutory category?):
The dependent claims 2-8 fall within the statutory category of machine
The dependent claim 10 falls within the statutory category of method
The dependent claims 12-20 fall within the statutory category of machine.
Eligibility Step 2A-1 (does the claim recite an abstract idea, law of nature, or natural phenomenon?): Dependent claims 2-8, 10, and 12-20 claimed invention is directed to an abstract idea without significantly more. The claims continue to limit the independent claims 1, 9, and 11 abstract idea by (1) further limiting the types of samples and data, and (2) further the rules and instructions to analyze data. Therefore, the dependent claims inherit the same abstract idea which is “certain methods of organizing human activity” as it is managing personal behavior and following rules and instructions to determine and send diagnosis information for a patient (MPEP § 2106.04(a)(2), subsection II)
Eligibility Step 2A-2 (does the claim recite additional elements that integrate the judicial exception into a practical application?): For claims 2-8, 10, and 12-20 this judicial exception is not integrated into a practical application.
The dependent claims recite the additional elements below not already recited in the independent claims:
a group comprising spirometer, electrocardiography sensor, glucose ketone analyser, electronic blood pressure (BP) monitor, Lipid Profiler, creatinine monitor, HbA 1 C monitor, Hb monitor, urine analyser, cardiovascular analyser, thyroid, renal, liver function analyser, haemoglobin and white blood cell (WBC) analyser, cancer screening, communicable disease detector, cancer identifier, portable X-Ray, uric acid/UREA profiler, Thermometer, stethoscope, pulse oximeter, CBP analyser, mammogram.
a plurality of wheels and back strap
internet-enabled with an integrated 4G dongle
a laptop, a desktop PC, an AR/VR headset, a smartphone or a tablet, a patient database
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional element (a) are recited as tools or equivalent to apply the abstract idea as “apply-it” to gather data
The additional element (b) are recited as tools or equivalent to apply the abstract idea as “apply-it” to move computer system
The additional element (c) are recited as tools or equivalent to apply the abstract idea as “apply-it” to communicate data
The additional element (d) are recited as tools or equivalent to apply the abstract idea as “apply-it” to communicate data
Accordingly, the dependent claims as a whole do not integrate the recited abstract idea into a practical application (MPEP 2106.05(f) and 2106.04(d)(1).
Eligibility Step 2B (Does the claim amount to significantly more?): The dependent claims do not include additional elements sufficient to amount to significantly more than the judicial exception because as analyzed above in step 2A prong 2 above, these additional elements, whether viewed individually or as an ordered combination, amount to no more than applying the abstract idea thus insufficient to provide “significantly more”. Therefore, the claim does not amount to significantly more and the claim is ineligible.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, 3, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Lefkofsky (US20210118559A1).
As per claim 1, Lefkofsky teaches:
A computer system for diagnostic assessments, the computer system comprising: (abstract discloses, “laboratory diagnostic testing result associated with a speci men of a subject , the steps of receiving a clinomic profile of the subject , identifying a cohort of similar subjects based at least in part on the clinomic profile of the subject , providing the diagnostic testing results , clinomic profile , and the cohort of similar subjects to a smart output module to generate a personalized , precision medicine based laboratory diagnostic testing result as a smart output and display ing the smart output to a user.”)
one or more medical instrument sensors, wherein any medical instrument of the one or more medical instruments configured to: ([0096] discloses, “A device dataset 270 may store data elements generated from one or more devices utilized by or otherwise associated with the subject . For example , a diabetes subject may utilize various insulin delivery methods such as digital syringes , digital pens , digital insulin pumps , blood glucose meters , continuous glucose monitors , automated insulin delivery devices such as the artificial pancreas , and so forth . A subject with a cardiovascular condition may utilize a digital blood pressure machine , a heart monitor , and so forth . A subject with a stroke condition , for example , may utilize an orthotic , prosthetic , or other assistive device with digital monitoring features enabled . A subject who requires obesity care may enter information through a smartphone app , for instance , in order to track food and water intake , exercise , and weight - loss medication administration . Each device may be in operative communication with one or more aspects of the system 101 in order to transmit information from the device into the system for processing and storage into the device dataset 270.”)
receive one or more samples from body of a person having information of that body; ([0057] discloses, “The laboratory , for example , may support analysis of a subject's condition relating to a disease state . The laboratory 140 may be a laboratory for processing specimens 115 , such as saliva , blood , urine , stool , hair , tumor tissue , healthy tissue , or other collections of cells or fluids from a subject 102. A laboratory 140 may include an order reception and subject order creation process to receive a request from a physician to process a specimen 115 for testing , a specimen intake process to receive a specimen 115 and associate the order with the subject 102 , a specimen testing process to generate laboratory results of the order for the specimen 115 , an order satisfaction process to record the order as completed , and a laboratory reporting process to report out the laboratory results of subject 102.”)
determine one or more parameter based on the information from the one or more samples; ([0078] discloses, “The analysis library 180 may comprise analysis modules 180a - n . Each analysis module 180a - n may process a set of data from the data repository 160 in combination with one or more of the subject's lab result 103 and / or a set of data from the subject's clinomic data 104 to generate a smart output 190. Optionally each analysis module 180a - n may process a set of laboratory result data of one or more specimen 115 from the laboratory 140 alone or in addition to one or more of lab result 103 of a subject or clinomic data 104 to generate a smart output 190.” And see [0079] and see “Smart Output [0080] discloses, “Smart output 190 may comprise one or more of a personalized test result specific to the subject 102 ; a personalized threshold of evaluation specific to the subject 102 ; a representation of data , such as clinomic profiles , from a cohort of subjects similar to the subject 102 , including features or associations / insights within such data cohort ; an association of the test result 102 with a knowledge database , such as a database of drug - gene interactions , a database of promising treatments based on scientific evidence , and the like ; or an association of a prior test result with testing from the laboratory 140. The smart output 190 may take the form of a diagnosis and / or treatment report , a research use only report , or a presentation for further review by a molecular board . Smart output 190 may further comprise a graphical user interface for viewing any of the representations of personalized or precision medicine based laboratory results , evaluation thresholds , associations , insights , or the like . Test results may include results of biological , microbiological , serological , chemical , immunohematological , radioimmunological , hematological , biophysical , cytological , pathological , toxicological or other examination of materials derived from the human body for the purposes of providing information for the diagnosis , prevention or treatment of any disease or impairment of ,or the assessment of , the health of humans including determining drug use by humans.”)
a memory unit configured to store machine-readable instructions; ([0265] discloses, “The example computer system 600 includes a processing device 602 , a main memory 604 ( such as read only memory ( ROM ) , flash memory , dynamic random access memory ( DRAM ) such as synchronous DRAM ( SDRAM ) or DRAM , etc. ) , a static memory 606 ( such as flash memory , static random access memory ( SRAM ) , etc. ) , and a data storage device 618 , which communicate with each other via a bus 630.”) and see [0268])
and a processor operably connected with the memory unit, the processor obtaining the machine-readable instructions from the memory unit, and being configured by the machine-readable instructions to: (see [0268] and see [0043])
compare the determined one or more parameters with predefined parameters; ([0100] discloses, “FIG . 4 includes a flow chart illustrating an exemplary method 400 that may be performed by the FIG . 1 system , 101 that is consistent with at least some aspects of the present disclosure . In FIG . 4 , method 400 is orchestrated by an orchestration module 410 and begins with a process 412 for structuring received subject data for a specific subject , such as subject data received at data repository 160 , including lab result 103 and clinomic data 104. Next , the method includes a process 414 to examine the structured subject data and identify features from which to build a cohort of similar subjects based upon data associated with other subjects who have features in common with a specific subject for which a test has been performed . Then , the method includes a process 416 to compare structured subject data to the cohort such that a personalized smart output is derived for the specific subject . The method includes a process 418 to present the smart output ( e.g. , results of the comparison ) to a user ( e.g. , a physician ) in the form of a report or an interactive software interface . Finally , the method includes process 420 for associating therapies with results of the comparison at 418. In this way , any therapies which may improve or hinder the prognosis of the subject are visible to the treating physician and may be considered in generating a treatment plan for the subject . Blocks 422 and 424 represent other processes that may , for example be added to the end of the method shown in FIG . 4.”)
determine a health related information of the human body based on the comparison; (e.g. [0276] discloses, “. In this manner , analysis mod ule 180i may deliver one or more smart outputs to smart output 190. For example , a normal range of A1C level may be between 4 % and 5.6 % with higher levels suggesting a likelihood of being diabetic and levels exceeding 6.5 % suggesting an active diagnosis of diabetes . A subject's ethnicity may inform A1C measurements such that mean A1C levels may actually hover around 5.78 % for Cauca sians , 5.93 % for Hispanics , 6.00 % for Asians , 6.12 % for American Indians , and 6.18 % for Africans . Therefore , analysis module 180i may apply a correction factor to generate a smart output which accounts for racial differences in A1C levels as diagnostic testing is performed on a subject.”)
and determine a predictive analysis risk predictions, comorbidity alerts, decision support for doctors, corporates and government, based on the health related information; ([0051] discloses, “A clinomic profile , as used herein , may be generated for each subject from a diverse set of clinical information available within subject health records . Clinical information may be based upon fields which have been entered into an electronic medical record ( EMR ) or an electronic health record ( EHR ) by a physician , nurse , or other medical professional .” and see [0052] discloses, “A clinomic profile may include information about a subject across a variety of disease states . Molecular clinical information may also be part of a subject's clinomic profile . Molecular clinical information may be curated from genetic sequencing results . Sequencing may include next generation sequencing ( NGS ) and may be long - read , short read , or other forms of sequencing a subject's genome . Clinical information may also combine a variety of features together across varying fields of medicine , including : diag nosis , response to treatment regimens , genetic profiles , clinical and phenotypic characteristics , and / or other medi cal , geographic , demographic , clinical , molecular , or genetic features . For example , clinical information in the area of cancer may include demographics ( such as Year of Birth , Gender , Race / Ethnicity , Relevant Comorbidities , Smoking History ) , diagnosis ( Site ( Tissue of Origin ) , Initial Diagnosis Date , Initial Diagnosis , Histology , Histologic Grade , Meta static Diagnosis , Metastatic Diagnosis Date , Site ( s ) of Metastasis , Stage ( e.g. , TNM , ISS , DSS , FAB , RAI , Binet ) ) , assessments , labs & molecular pathology ( e.g. Type of Lab ( e.g. CBS , CMP , PSA , CEA ) , Lab Results and Units , Lab Event Date , Performance Status ( e.g. ECOG , Karnofsky ) , Performance Status Score , Performance Status Date , Molecular Pathology Test Event * , Gene / Biomarker / Assay , Gene / Biomarker / Assay Result ( e.g. Positive , Negative , Equivocal , Mutated , Wild Type , Molecular Pathology Method ( e.g. , IHC , FISH , NGS ) , Molecular Pathology Pro vider ) , Treatment ( e.g. Drug Name , Drug Start Date , Drug End Date , Dosage and Units , Drug Number of Cycles , Surgical Procedure Type , Surgical Procedure Date , Radia tion Site , Radiation Modality Radiation Start Date , Radiation End Date , Radiation Total Dose Delivered , Radiation Total Fractions Delivered ) , out comes ( e.g. Response to Therapy ( e.g. CR , PR , SD , PD ) , RECIST measurement , Outcome / Observation Date , Progression Date , Recurrence Date , Adverse Event to Therapy , Adverse Event Date of Presentation , Adverse Event Grade . Death Date , Last Follow - up Date , and Disease Status at Last Follow Up ) . Genetic profiles may be derived from RNA or DNA sequencing . Features derived from DNA and RNA sequencing may include genetic variants which are present in the sequenced specimen.” And see [0231] discloses, “A subject data store may include one or more feature modules which may comprise a collection of features available for every subject in the system 1000. These features may be used to generate and model the artificial intelligence classifiers in the system 1000. These features may include the features as described above with respect to the order processing pipeline . Including , the plurality of features present in the feature modules comprising features available within subject health records 814 , including information contained in the source subject , structured subject , structured clinomic data repository , and laboratory datasets , above , to include comprehensive collection of subject data.” And see [0232] discloses, “The system may include a data delivery pipeline to transmit clinical and molecular de - identified records in bulk . The system also may include separate storage for de identified and identified data to maintain data privacy and compliance with applicable laws or guidelines , such as the Health Insurance Portability and Accountability Act.” And see [0304]- [0308])
and a communication network configured to: send the health related information to one or more user devices held by the person, health organisations and other stake holders. ([0184] discloses, “The information acquired , processed , and generated by the content server 800 is stored on one or more of the network - based storage devices . The user can interact with the content server to access the information stored in the network - based storage devices , and the content server can receive user - supplied information , apply the one or more models stored in the network - based storage to the information , and to provide , in an electronic form , results of the model application to the user on a graphical user interface of the user device . The electronic information is transmitted in a standardized format over the computer network to the users that have access to the information . In this way , the users can readily adapt their medical diagnostic and treatment strategy in accordance with the system's predictions which can be automatically generated . Moreover , the system generates recommendations to users regarding subject diagnosis and treatment.” And see [0211] discloses, “Prediction store 850 may receive predictions for targets / objectives generated from objective modules 840 and store them for use in the system 800. Predictions may be stored in a structured format for retrieval by a user interface such as , for example , a webform - based interactive user interface which , in some embodiments , may include web forms 860a - n . Webforms may support GUIs that can be displayed by a computer to a user of the computer system for performing a plurality of analytical functions , including initiating or viewing the instant predictions from objective modules 840 or initiating or adjusting the cohort of subjects from which the objective modules 840 may perform ana lytics from . Electronic reports 870a - n may be generated and provided to the user via the graphical user interface ( GUI ) 865. It should be appreciated that the GUI 865 may be presented on a user device which is connected to the content server / prediction engine 800 via a network.”)
As per claim 2, Lefkofsky teaches:
The computer system as claimed in claim 1, wherein the one or more medical instruments may be selected from a group comprising spirometer, electrocardiography sensor, glucose ketone analyser, electronic blood pressure (BP) monitor, Lipid Profiler, creatinine monitor, HbA 1 C monitor, Hb monitor, urine analyser, cardiovascular analyser, thyroid, renal, liver function analyser, haemoglobin and white blood cell (WBC) analyser, cancer screening, communicable disease detector, cancer identifier, portable X-Ray, uric acid/UREA profiler, Thermometer, stethoscope, pulse oximeter, CBP analyser, mammogram. ([0637] discloses, “Types of Imaging Tests which May be Performed at Laboratory 140 or Processed at Analysis Engine 180 Further Include :and see [0644] discloses, “ 4. Mammogram”)
As per claim 3, Lefkofsky teaches:
The computer system as claimed in claim 1, wherein the one or more samples are selected from a group comprising blood, tissue, saliva, or urine or a combination thereof. ([0057] discloses, “The laboratory 140 may be a laboratory for processing specimens 115 , such as saliva , blood , urine , stool , hair , tumor tissue , healthy tissue , or other collections of cells or fluids from a subject 102.”)
As per claim 5, Lefkofsky teaches:
The computer system as claimed in claim 1, wherein the health related information is selected from a group comprising basic biometric data (including temperature), complete urine analysis, haemoglobin and white blood cell count, detailed cardiovascular function, blood vitamin analysis, detailed diabetes blood glucose levels, renal function test, thyroid test, hypertension, liver function test, pulmonary function test, prostate function test, Cancer Markers, Tumour Markers, Infection Markers, electrolyte measurement test, and infectious disease tests (e.g. [0276] discloses, “. In this manner , analysis mod ule 180i may deliver one or more smart outputs to smart output 190. For example , a normal range of A1C level may be between 4 % and 5.6 % with higher levels suggesting a likelihood of being diabetic and levels exceeding 6.5 % suggesting an active diagnosis of diabetes . A subject's ethnicity may inform A1C measurements such that mean A1C levels may actually hover around 5.78 % for Cauca sians , 5.93 % for Hispanics , 6.00 % for Asians , 6.12 % for American Indians , and 6.18 % for Africans . Therefore , analysis module 180i may apply a correction factor to generate a smart output which accounts for racial differences in A1C levels as diagnostic testing is performed on a subject.”)
As per claim 7, Lefkofsky teaches:
The computer system as claimed in claim 1, wherein the processor is further configured to: receive health information related to one or more patients for diagnostic assessments from doctors, hospitals or health organizations; ([0276] discloses, “In yet another example , analysis module 180i may request diagnostic results from subjects who also received diagnostic test results from the same laboratory and , if available , results for the same diagnostic tests from other laboratories to identify any bias that may be introduced introduced from that laboratory's specific processing of subject specimens.”)
allow any patient of the one or more patients to view, share and maintain health data, preserving health records digitally and chronologically; (e.g. [0302] discloses, “The status of each pathogen ( for example , whether it is detected in the patient specimen or not ) , may be included in a report delivered to the physician and / or patient .The report may be delivered to the physician and / or patient automatically upon completion of at least one assay ordered for the patient , or at another point in the assay and assay analysis workflow.” And see [0279] discloses, “Smart outputs may include adjustments to raw diagnostic testing results , evaluation thresholds , cohort reports or real time monitoring through software interface , or other such smart outputs which present a personalized diagnostic result for subject 102.” And see [0225] discloses, “the web portal may interface with one or more institution's EMR systems and retrieve results from a sub ject's records directly” and see [0183])
update information about any patient of the one or more patients thereby helping hospitals, medical stores and diagnostic centres ; (e.g. [0183] discloses, “A user , such as a health care provider or subject , is given remote access through the GUI to view , update , and analyze information about a subject's medical condition using the user's own local device ( e.g. , a personal computer or wireless handheld device ) . A user can interact with the system to instruct it to generate electronic records , update the electronic records , and perform other actions . The content server is configured to receive various information in different formats and it converts the information into the standardized format that is suitable for processing by mod ules operation on or in conjunction with the content server . Thus , information acquired from subjects ' electronic medi cal records ( EMR ) , unstructured text , genetic sequencing , imaging , and various other information can be converted into features that are used for training a plurality of machine learning models.”)
facilitate one or more information dialogs between patients, doctors, hospitals and all involved parties; ([0212] discloses, “The reports 870 can be provided to the user as part of a network - based subject management system that collects , converts and consolidates subject information from various physicians and health - care providers ( including labs ) into a standardized format , stores it in network - based storage devices , and generates messages comprising electronic reports once the reports are generated in accordance with embodiments of the present disclosure . In this way , a user ( e.g. , a physician , oncologist , or any other health care provider , or a subject , receives computer - generated predictions related to a likelihood of a subject's tumor metastasizing , a predicted location of the metastasis , and / or an associated timeline.”)
perform self-risk assessment tests for stress, and also examine risk to develop certain chronic diseases; and monitor prognosis and diagnosis of patients in real-time ([0009] discloses, “The raw test result may be a result from a medical test . Exemplary medical tests include, but are not limited to, tests to diagnose or predict the risk of a disease or other health condition , such as cancer , cardiovascular disease , diabetes and other endocrine diseases , skin disease , immune - mediated diseases , stroke , ratory disease , cirrhosis , high blood pressure , osteoporosis , mental illness , developmental disorders , digestive diseases , viruses , bacterial infections , fungus.” And see [0010] discloses, “Exemplary medical tests include , but are not limited to , a blood test , a biopsy test , an electrocardiography , an endoscopy , a pap test , a computed tomography , a bone marrow examination , a molecular test , a pulmonary function test , a physical examination , a lipid biopsy , a cardiac stress test , an esophageal motility test , a throat culture , an imaging scan or test , and so on .)” and see [0279] discloses, “Smart outputs may include adjustments to raw diagnostic testing results , evaluation thresholds , cohort reports or real time monitoring through software interface , or other such smart outputs which present a personalized diagnostic result for subject 102.” )
As per claim 8, Lefkofsky teaches:
The computer system as claimed in claim 1, wherein the one or more user devices are selected from, but not limited to, a laptop, a desktop PC, an AR/VR headset, a smartphone or a tablet. ([0258] discloses, “Mobile devices , such as cellular phones , laptop computers , tablets , and other mobile devices may install an application from the laboratory to implement methods and systems as described herein . A physician may utilize the application to begin an order , request specimen storage and mailing units , print mailing labels , track a subject's progress through the order processing pipeline , and review the reports order upon order fulfillment . Lab personnel may utilize the application to track an order that has been received , peri odically update the order status based upon fulfillment of certain conditions during order processing , and sign off on a completed report for release to ordering physician . The application may automatically supply notification to other lab personnel or the ordering physician of those condition fulfillments . Research participants may track a plurality of subjects who have registered with the research during execution of a clinical trial , including order fulfillment of laboratory results.”)
As per claims 9-15, they are method claims which repeats the same limitations of claims 1, 3, 7, and 8 the corresponding system claim, as a series of process steps as opposed to a collection of elements. Since the teaching Lefkofsky discloses the structural elements that constitute the system of claims 1, 3, 7, and 8, it is respectfully submitted that they perform the underlying process steps, as well. As such, the limitations of claims 9-15 are rejected for the same reasons given above for claims 1, 3, 7, and 8.
As per claim 16, Lefkofsky teaches:
A portable medical device for diagnostic assessments according to claim 14 wherein determined health related information of the human body is determined within about 15 minutes. ([0279] discloses, “Smart outputs may include adjustments to raw diagnostic testing results , evaluation thresholds , cohort reports or real time monitoring through software interface , or other such smart outputs which present a personalized diagnostic result for subject 102.” / real time is interpreted by examiner as within this timeframe)
As per claim 17, Lefkofsky teaches:
A portable medical device for diagnostic assessments according to claim 16 wherein the predictive analysis risk predictions include predictions of one: diabetes; health comorbidities; cardiovascular disorders; stress related illness; kidney disease; respiratory disorders; liver disease; cancer. ([0009] discloses, “The raw test result may be a result from a medical test . Exemplary medical tests include , but are not limited to , tests to diagnose or predict the risk of a disease or other health condition , such as cancer , cardiovascular disease , diabetes and other endocrine diseases , skin disease , immune - mediated diseases , stroke , ratory disease , cirrhosis , high blood pressure , osteoporosis , mental illness , developmental disorders , digestive diseases , viruses , bacterial infections , fungus infections , or urinary and reproductive system infections.”)
As per claim 18, Lefkofsky teaches:
A portable medical device for diagnostic assessments according to claim 17 wherein the plurality of medical instruments includes one or more of the following integrated components: Pulmonary Function/Spirometer; ECG; Glucose Ketone Analyzer; Electronic BP Monitor; Lipid Profiler; Creatinine Monitor; HbA1 C Monitor; Hb Monitor; Urine Analyser; Cardiovascular Monitor; Thyroid, Renal, Liver Function monitor; Hemoglobin and WBC; Immuno Anaylser; Uric Acid/UREA Profiler. ([0069] discloses, “The laboratory 140 may include radiography equipment to perform the above listed imaging scans such as…[…]… ECG monitor , treadmill , intravenous contrast delivery system brachytherapy machines , magnetostrictive transducers , ultrasonic disintegrator , and respective imaging method specific software.”)
As per claim 19, Lefkofsky teaches:
A portable medical device for diagnostic assessments according to claim 18 wherein the plurality of medical instruments includes one or more of the following external components: Cancer Detection; Communicable Disease Detection; Cancer Identifier; Portable X-Ray; Thermometer; Stethoscope; Pulse Oxymeter; CBP Analyser. ([0068 ] discloses, “The laboratory 140 may include equipment for the imaging of varying specimens. Imaging may include radio logical scanning such as radiography , fluoroscopy , projectional radiograph , magnetic resonance imaging , nuclear medicine , scintigraphy , ultrasound , elastography , tactile imaging , strain imagine , impulse imaging , photoacoustic imaging , tomography , X - ray , computed tomography , single photon emission computerized tomography ( SPECT ) , positron emission tomography , echocardiography , functional near - infrared spectroscopy , fusion imaging , magnetic par ticle imaging , pathology and other imaging equipment.” / examiner interprets computed tomography as an example of an instrument for cancer detection.)
As per claim 20, Lefkofsky teaches:
A portable medical device for diagnostic assessments according to claim 19 wherein the health related information comprises one or more of the following tests: Pulmonary Function Tests comprising one or more of: Obesity Parameters: BMI, BAI, SBMI , BFC, VFC, BA, BMR; Pulmonary Function Tests: FVC, MVV, SVC (Pre/Post); Other Parameters: SP02, Hb, Heart Rate; Liver Function Tests comprising one or more of: Obesity Parameters: BMI, BAI, SBMI BFC, VFC, BA, BMR; Liver Function Tests: Bilirubin, Urobilinogen; Kidney Function Tests comprising one or more of: Obesity Parameters: BMI, BAI, SBMI, BFC, VFC, BA, BMR; Kidney Function Tests: Creatinine, Uric Acid Renal; Other Parameters: Creatinine, Miro Albumin, Protein Urine Parameters: Micro Albumin, Protein, Creatinine; ([0297] discloses, “In one example , the patient may or may not have a liver function test result that indicates that the patient has liver failure ( for example , PT , INR , albumin , etc. ) . An assay detects the presence of one or more pathogens commonly associated with liver failure ( for example , hepatitis A , B , C , D , E , etc. ) . Any of the patient's liver function test results may be included in clinical data used to personalize the reporting of the pathogen detection results.” And see [0588] discloses, “A liver ( hepatic ) function panel is a blood test to check how well the liver is working . This test measures the blood levels of total protein , albumin , bilirubin , and liver enzymes . High or low levels may mean that liver damage or disease is present .Normal values for these tests are presented above.” And see [0472] discloses, “This panel measures the blood levels of albumin , blood urea nitrogen , calcium , carbon dioxide , chloride , creatinine , glucose , potassium , sodium , total bilirubin and protein , and liver enzymes ( alanine aminotransferase , alka line phosphatase , and aspartate aminotransferase ))” and see [0085] discloses, “For example , structured subject dataset 210 may include therapies information including molecularly - guided neoadjuvant and / or adjuvant therapies , immunotherapies , molecular therapies , CAR - T cell therapy , CRISPR therapies , checkpoint inhibitors , and / or personalized vaccines when a subject 102 is a cancer subject . In another example , source subject dataset 204 may include general subject data such as date of birth , gender , occupation , blood type , Rh , addresses , or telephone numbers ; home monitoring data such as blood glucose monitoring , blood pressure monitoring , weight ,body mass index , waist circumference , or height ; laboratory data such as glycated hemoglobin , total cholesterol , triglyc eride , high - density lipoprotein , low - density lipoprotein , thy roid stimulator hormone , microalbuminuria”)Infection Diseases comprising one or more of: Screening of Infectious Diseases: dengue, cholera, H1N1, Typhoid, Ebola, Chikungunya and Malaria; Cardiovascular Tests comprising one or more of: Complete Cardiac Profile: ECG, Heart Rate, BP, hsCRP*, K+*; Obesity Parameters: BMI, BAI, SBMI, BFC, VFC, BA, BMR; Complete Diabetes Profile: FBS, GRBS, HbA1C; Complete Lipid Profile: TC, HDL, TG, LDL, TC/HDL, VLDL; Diabetic Function Tests comprising one or more of: Obesity Parameters: BMI, BAI, SBMI, BFC, VFC, BA, BMR; Complete Diabetes Profile: FBS, GRBS, HbA1C; Other Parameters: Creatinine, Uric Acid; Complete Lipid Profile: TC, HDL, TG, LDL, TC/HDL, VLDL; And Cancer Screening Tests comprising one or more of: Cancer Screening: quick, low interference and minimal pain; Breast, Cervical, Gastro intestinal, Colorectal, Oral, Prostate. ([0644] discloses, “4. Mammogram” and see [0645] discloses, “Two types of mammograms are offered in the battle against breast cancer : Screening and diagnostic mammograms.”)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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 4 is rejected to under 35 U.S.C. 103 as being unpatentable over Lefkofsky (US20210118559A1) in view of Purpura (US6796473B2)
As per claim 4, Lefkofsky does not teach:
The computer system as claimed in claim 1, comprising a plurality of wheels and back strap for quick and easy mobility.
However, Purpura does teach:
The computer system as claimed in claim 1, comprising a plurality of wheels and back strap for quick and easy mobility. (Col. 2 lines 28-31 discloses, “In accordance with the teachings of the present invention, a laptop computer transport and Support System (LCTSS) for mobile environments is disclosed.” And see Col. 2 lines 51-56 discloses, “Dual sliding rods attached to a handle permit a user to pull the LCTSS on built-in wheels. Furthermore, the LCTSS includes adjustable shoulder straps permitting the LCTSS to be carried as a backpack, or which can be used as adjustable support straps when the LCTSS is attached to a user's seatback while in use as a Support System.”)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Lefkofsky’s teachings with Purpura’s teachings, the motivation being Lefkofsky discloses the importance of personalized medicine and the need for remote access of GUI to access medical information (e.g. see [0007] and see [0183]), therefore the combination with mobile movable computer with straps and wheels in Purpura would improve the ability to provide individualized care and remote care by increasing the mobility of the computer systems applied to gather and analyze data while ensuring HIPAA compliance utilizing computer elements that would not render the instant invention inoperable.
Claim 6 is rejected to under 35 U.S.C. 103 as being unpatentable over Lefkofsky (US20210118559A1) in view of McCombie et. al (hereinafter McCombie) (US11179105B2)
As per claim 6, Lefkofsky teaches the underlined portion :
The computer system as claimed in claim 1, wherein the communication network is wireless and internet-enabled with an integrated 4G dongle. ([0096] discloses, “Such communication processes may include communication over the World Wide Web , Wi - Fi , Bluetooth , internet of things , or other communication mediums.”)
However, Lefkofsky does not teach the underlined portion:
The computer system as claimed in claim 1, wherein the communication network is wireless and internet-enabled with an integrated 4G dongle.
However, McCombie does teach:
The computer system as claimed in claim 1, wherein the communication network is wireless and internet-enabled with an integrated 4G dongle. (Col. 11 lines 19-35 and see Col. 5 lines 5-16)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Lefkofsky’s teachings with McCombie’s teachings, the motivation being Lefkofsky discloses the importance of personalized medicine and the need for remote access of GUI to access medical information (e.g. see [0007] and see [0183]), therefore the combination with 4G dongle in McCombie would improve the ability to provide individualized care and remote care by increasing the mobility of the computer systems internet reach applied to gather and analyze data while ensuring HIPAA compliance utilizing computer elements that would not render the instant invention inoperable.
Prior Art not cited but made of record
US20210005327A1 – Anwar et. al
The present disclosure relates to personalized health , spe cifically molecular based health management and digital consultation . In particular , the present disclosure is directed to methods and systems for assessing the health status of an individual based on correlations between multi - omics measures ( e.g. , genomics , metabolomics , exposomics and proteomics ) and diseases or health risks as disclosed in pub lished research data . The disclosure also relates to methods and systems for customized counseling to individuals regarding health status and actionable measures to improve their health status
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ashley Elizabeth Evans whose telephone number is (571) 270-0110. The examiner can normally be reached Monday – Friday 8:00 AM – 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached on (571) 270-1813. The fax phone number for the organization where this application or proceeding is assigned 571-273-8300.
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/ASHLEY ELIZABETH EVANS/Examiner, Art Unit 3687
/MAMON OBEID/Supervisory Patent Examiner, Art Unit 3687