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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, the fee set forth in 37 CFR 1.17(e) has been timely paid, and the petition decision on 22 July 2025 for continuing prosecution was granted, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Accordingly, Applicant's submission filed on 08 July 2025 has been entered.
Response to Amendment
Claims 1-19 were previously pending in this application. The amendment filed 14 April 2025 has been entered and the following has occurred: Claims 1, 17, & 19 have been amended. No Claims have been cancelled or added.
Claims 1-19 remain pending in the application.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: claim limitations that contain language reciting “…module is configured to…” in claims 1, 3, & 6-16.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof (See Applicant’s Specification [0063] which describes the term “module” and imparts structural limitation of said components).
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The claims recite subject matter within a statutory category as a process (claim 17-18), machine (claims 1-16), and manufacture (claim 19) which recite steps of:
enable at least one of: a research participant; and a site manager to input one or more research participants' information by enrolment and retention module on at least one of: a research participant computing device; and a research site manager computing device over a network;
send the one or more research participants' information from the at least one of:
the research participant computing device; and the research site manager computing device to a cloud server and a central database by the enrolment and retention module over the network;
analyze the stored participant information using an artificial intelligence and machine learning model trained on historical trial data and generate a list of qualified participants based on outputs of an artificial intelligence model and specified inclusion/exclusion criteria, and wherein
the list generating module is further configured to filter the generated list of qualified research participants based on the availability of principal investigators for screening as determined by the appointment scheduling module;
enable the list of qualified research participants to input additional patients’ information by the appointment scheduling module on the research participant computing device;
enable the list of qualified research participants to schedule an appointment with the site manager for research study screening by the appointment scheduling module;
enabling the list of qualified research participants to send a request from the research participant's computing device to the research site manager's computing device for scheduling the appointment;
assign one or more principal investigators to screen the one or more research participants by the appointment scheduling module based on the one or more research participants' information;
enable one or more principal investigators to input screening data of the one or more research participants by a primary source data capturing module on the principal investigators computing device after screening the one or more research participants at a research site location in real-time;
collect the screening data in real-time and calculate accounts receivable from a sponsor by a financial module thereby send the screening data to a data review and reports generating module;
generate one or more screening reports by the data review and reports generating module as the amount of money that is owed to the research site location;
send the one or more screening reports to the invoice generating module and generate an invoice based on the one or more screening reports of the one or more research participants; and
send the invoice to the sponsor computing device and enable the sponsor to review the invoice generated based on the one or more screening reports of the one or more research participants.
These steps of inputting/sending one or more research participant’s information, analyzing the information, generating a list of qualified research participants, inputting additional patient information, scheduling an appointment, sending a request for scheduling the appointment, assigning one or more investigators to screen the participants, inputting screening data, collecting the screening data, calculating accounts receivable, generating one or more screening reports as the amount of money owed, sending one or more screening reports, generating an invoice, sending the invoice, and reviewing the invoice generated, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. MPEP 2106.04(a)(2)(II) describes various methods of organizing human activity including fundamental economic principles or practices, commercial or legal interactions, and/or managing personal behavior or relationships or interactions between people. Under BRI, the above steps fall into activity including commercial or legal interactions and/or managing personal behavior or relationships or interactions between people. That is, under BRI, the steps include determining candidacy for a clinical trial, performing activities on the candidates of the research trial, reporting said activities, generating an invoice based on said activities for the sponsor of the clinical trial, and adjudicating said invoice by the sponsor. Given the language of billing/invoices and generation/management of such commercial elements by the system, the system is effectively taking part on commercial or legal interactions between the various entities of the clinical research setting (sponsor, principal investigator, site manager, etc.). Furthermore, because the commercial or legal interactions are occurring between said entities, and the system is substantially managing the activities of recording clinical trial activities and generation of the invoices thereof, the system is effectively managing the personal behavior or relationships or commercial interactions between said entities. As such, the claims recite an abstract idea.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-16 & 18, reciting particular aspects of how the generation of screening data/reports, the analysis of candidate data, generation of an invoice, sending reminders to an entity, etc., may be performed in the mind but for recitation of generic computer components).
This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as recitation of one or more modules, a memory, one or more computing devices, a non-transitory computer-readable medium, one or more processors, program code, a network, a cloud server, a central database, an artificial intelligence module, and machine learning techniques amounts to invoking computers as a tool to perform the abstract idea, see applicant’s specification [0063] for module, [0107] for memories, [0049] for computing devices, [0107] for non-transitory computer-readable mediums, [0048] for processors, [0049] for networks, [0048] for cloud server, [0053] for central database, [0054] for an artificial intelligence module, [0054] for machine learning techniques, see MPEP 2106.05(f));
add insignificant extra-solution activity to the abstract idea (such as recitation of inputting/sending one or more research participants, inputting additional patient information, collecting screening data, sending one or more screening reports, sending one or more invoices, sending/receiving a request for scheduling an appointment amounts to mere data gathering; recitation of analyzing the patient information to generate a list of qualified candidates, filtering the generated list of qualified research participants based on the availability of principal investigators for screening as determined, generating one or more screening reports as money owed, assigning one or more researchers to the qualified participants, generating an invoice based on the screening report, reviewing the invoice generated amounts to selecting a particular data source or type of data to be manipulated; recitation of enabling various typical activities from generic computer technology, such as enabling review of data, etc. amounts to insignificant application, see MPEP 2106.05(g));
generally link the abstract idea to a particular technological environment or field of use (such as recitation of clinical research, see MPEP 2106.05(h)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-16 & 18, which recite limitations relating to a computer system, one or more modules, a cloud server, a central database, one or more computing devices, additional limitations which amount to invoking computers as a tool to perform the abstract idea, See MPEP 2106.05(f); claims 2-16 & 18, which recite limitations relating to receiving varying data, storing varying data, transmitting various messages/reminders, additional limitations which add insignificant extra-solution activity to the abstract idea which amounts to mere data gathering claims 2-16 & 18, which recite limitations relating to using varying received data to determine candidacy, forms of transmission, etc., additional limitations which add insignificant extra-solution activity to the abstract idea by selecting a particular data source or type of data to be manipulated, claims 2-16 & 18, additional limitations which generally link the abstract idea to a particular technological environment or field of use such as clinical trials). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as inputting/sending one or more research participants, inputting additional patient information, collecting screening data, sending one or more screening reports, sending one or more invoices, sending/receiving a request for scheduling an appointment, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); analyzing the patient information to generate a list of qualified candidates, generating one or more screening reports as money owed, assigning one or more researchers to the qualified participants, generating an invoice based on the screening report, and reviewing the invoice generated, filtering the generated list of qualified research participants based on the availability of principal investigators for screening as determined, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); maintaining one or more lists of qualified research participants and updating/filtering said list based on criteria, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); storing various received data, storing one or more screening reports, storing one or more invoices, storing computerized instructions in a computer readable medium, storing network instructions, etc., e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv)).
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-16 & 18, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields; claims 2-16 & 18, which recite limitations relating to receiving varying data, storing varying data, transmitting various messages/reminders, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); claims 2-16 & 18, which recite limitations relating to performing various computerized methods including efforts of receiving data, analyzing data, determining candidacy, reviewing billing, maintaining electronic credentials, generating screening reports, etc. e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); claims 6 & 13 which recite limitations relating to maintaining electronic credentials, signatures, permissions, etc., e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); claims 2-16 & 18, which recite limitations relating to storing computerized instructions, storing computerized data, storing one or more reports, storing one or more electronic credentials, etc., e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv)). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-19 are rejected under 35 U.S.C. 103 as being unpatentable over Das et al. (U.S. Patent Publication No. 2022/0084633), hereinafter “Das”, in view of Briegs et al. (U.S. Patent Publication No. 2006/0143047), hereinafter “Briegs”, in view of Rosenberg et al. (U.S. Patent Publication No. 2008/0270181), hereinafter “Rosenberg”, further in view of Green, Jr. et al. (U.S. Patent Publication No. 2011/0301982), hereinafter “Green”.
Claim 1 –
Regarding Claim 1, Das discloses a computer-implemented system for providing an optimized process in a clinical research comprising:
a non-transitory computer-readable storage medium storing instructions (See Das Par [0017] which discloses a non-transitory computer readable medium);
one or more processors coupled to the medium and configured to execute the instructions (See Das Par [0011] which discloses at least one processor and interface for communicating at least one data source) to implement a research process optimizing module on each of:
a research participant's computing device, a research site manager's computing device, and a principal investigator's computing device (See Das Par [0047] & [0093] & Fig. 1 which discloses multiple computer systems or users being connected at Fig. 1, El. 104 such as in Das Par [0093] the user including a user, i.e. participant, user/patient caregiver, operator, sponsor, or investigator of the clinical trial thereby suggesting a device being present for associated participant, operator (i.e. site manager, and an investigator), and
a sponsor's computing device (See Das Par [0047] & [0093] & Fig. 1 which discloses multiple computer systems or users being connected at Fig. 1, El. 104 such as in Das Par [0093] the user including a patient caregiver, operator, sponsor, or investigator of the clinical trial thereby suggesting a sponsor’s device being present), wherein the research process optimizing module is configured to collect, sort and process one or more research participants' information to provide the optimized process in the clinical research (See Das Par [0038] which discloses various participant/patient information that is able to be collected by the system, See Das Par [0058] which discloses an input to the system being candidate patient clinical variable (CV) data source as described in Das Par [0038] from a first plurality of candidate patients, and this candidate patient clinical variable data being input into the system in real time, or can include historic information, the inputs of system to server including one or more interface systems for receiving the input data; See Das Par [0047] & [0093] & Fig. 1 which discloses multiple computer systems or users being connected at Fig. 1, El. 104 such as in Das Par [0093] the user including a patient caregiver, operator, sponsor, or investigator of the clinical trial present, such that the interface systems that receive the input data can occur from any one of the devices of associated “users”), the research process optimizing module comprises:
an enrolment and retention module configured to enable, via the one or more processors, at least one of: a research participant; and a site manager to input the one or more research participants' information on at least one of: the research participant's computing device; and the research site manager computing device over a network (See Das Par [0038] which discloses various participant/patient information that is able to be collected by the system, See Das Par [0058] which discloses an input to the system being candidate patient clinical variable (CV) data source as described in Das Par [0038] from a first plurality of candidate patients, and this candidate patient clinical variable data being input into the system in real time, or can include historic information, the inputs of system to server including one or more interface systems for receiving the input data; See Das Par [0047] & [0093] & Fig. 1 which discloses multiple computer systems or users being connected at Fig. 1, El. 104 such as in Das Par [0093] the user including a patient caregiver, operator, sponsor, or investigator of the clinical trial present, such that the interface systems that receive the input data can occur from any one of the devices of associated “users”);
a list generating module configured to analyze the one or more research participants' information stored in the central database using artificial intelligence module, and machine learning techniques and generate a list of qualified research participants to participate in the clinical research (See Das Par [0035] which discloses receiving, storing, and analyzing candidate patients information to determine patients that may be eligible to participate in clinical trials such that the system can automatically identify candidate patients and provide a notice to the patient, their respective physician or caregiver; See Das Par [0006]-[0008] & [0053]-[0055] which discloses the use of a machine learning system (it is understood by Examiner that machine learning techniques are a subset of artificial intelligence and would therefore Das effectively disclosing the species of machine learning would also effectively disclose the genus of artificial intelligence, See MPEP 2131.02) using training data including patient health record data, for determining a first plurality, i.e. list, of candidate patients that meet clinical trial inclusion criteria) based on at least one of:
outputs of the artificial intelligence module, an exclusion criteria, an inclusion criteria (see Das Par [0002] which discloses the use of eligibility criteria or inclusion criteria and disqualifying criteria or exclusion criteria based on patient information; See Das Par [0014], [0017], & [0088] for embodiments regarding inclusion criteria and patient/subject information; See Das Par [0035] which discloses determination of eligibility based on eligibility or disqualifying criteria for a clinical trial and relationships between said criteria and the analyzed patient data; See Das Par [0006]-[0008] & [0053]-[0055] which discloses the use of a machine learning system (it is understood by Examiner that machine learning techniques are a subset of artificial intelligence and would therefore Das effectively disclosing the species of machine learning would also effectively disclose the genus of artificial intelligence, See MPEP 2131.02) using training data including patient health record data, for determining a first plurality, i.e. list, of candidate patients that meet clinical trial inclusion criteria);
a list generating module, implemented as processor-executable instructions (See Das Par [0006]-[0008] & [0053]-[0055] which discloses the use of a machine learning system, i.e. module for determining a first plurality, i.e. list, of candidate patients that meet clinical trial inclusion/exclusion criteria), configured to:
analyze the stored participant information using an artificial intelligence and machine learning model trained on historical trial data and generate a list of qualified participants based on outputs of an artificial intelligence model and specified inclusion/exclusion criteria (See Das Par [0035] which discloses receiving, storing, and analyzing candidate patients information to determine patients that may be eligible to participate in clinical trials such that the system can automatically identify candidate patients and provide a notice to the patient, their respective physician or caregiver; See Das Par [0006]-[0008] & [0053]-[0055] which discloses the use of a machine learning system (it is understood by Examiner that machine learning techniques are a subset of artificial intelligence and therefore Das effectively disclosing the species of machine learning would also effectively disclose the genus of artificial intelligence, See MPEP 2131.02) using training data including patient health record data and historical trial data as described in Das Par [0058] & [0060], for determining a first plurality, i.e. list, of candidate patients that meet clinical trial inclusion criteria; see Das Par [0002] which discloses the use of eligibility criteria or inclusion criteria and disqualifying criteria or exclusion criteria based on patient information; See Das Par [0014], [0017], & [0088] for embodiments regarding inclusion criteria and patient/subject information; See Das Par [0035] which discloses determination of eligibility based on eligibility or disqualifying criteria for a clinical trial and relationships between said criteria and the analyzed patient data; See Das Par [0006]-[0008] & [0053]-[0055] which discloses the use of a machine learning system (it is understood by Examiner that machine learning techniques are a subset of artificial intelligence and would therefore Das effectively disclosing the species of machine learning would also effectively disclose the genus of artificial intelligence, See MPEP 2131.02) using training data including patient health record data, for determining a first plurality, i.e. list, of candidate patients that meet clinical trial inclusion/exclusion criteria).
Das does not seem to disclose the following limitations in their entirety:
the list generating module is further configured to filter the generated list of qualified research participants based on the availability of principal investigators for screening as determined by the appointment scheduling module.
whereby the appointment scheduling module configured to enable the one or more research participants to send a request from the research participant's computing device to the research site manager's computing device for scheduling the appointment, the appointment scheduling module configured to assign one or more principal investigators for screening one or more research participants based on the one or more research participants' information;
an appointment scheduling module configured to enable the list of qualified research participants to input additional patients’ information on the research participant's computing device and to schedule an appointment with the site manager for research study screening
a primary source data capturing module configured to enable one or more principal investigators to input screening data of the one or more research participants on the principal investigator's computing device after screening the one or more research participants at a research site location in real-time;
a financial module configured to collect the screening data in real-time and calculate accounts receivable from a sponsor thereby send the screening data to a data review and reports generating module, wherein the data review and reports generating module configured to generate one or more screening reports as the amount of money that is owed to a research site location and send the one or more screening reports to an invoice generating; and
an invoice generating module configured to generate an invoice based on the one or more screening reports of the one or more research participants and send the invoice to the sponsor's computing device, the data review and reports generating module configured to enable the sponsor to review the invoice on the sponsor computing device;
However, Briegs discloses the following limitations:
whereby the appointment scheduling module configured to enable the one or more research participants to send a request from the research participant's computing device to the research site manager's computing device for scheduling the appointment (See Briegs Par [0110] which discloses site management and site contact modules such that the modules allow the establishment of planned visits that study subjects are expected to attend, and further describe what procedures are to be conducted at each visit, when the visits should occur, what drugs should be given and in what dosage, and so on, constituting a schedule request from participant to manager under BRI), the appointment scheduling module configured to assign one or more principal investigators for screening one or more research participants based on the one or more research participants' information (See Das Par [0014], [0017], & [0088] for embodiments regarding inclusion criteria and patient/subject information; See Das Par [0035] which discloses receiving, storing, and analyzing candidate patients information to determine patients that may be eligible to participate in clinical trials such that the system can automatically identify candidate patients and provide a notice to the patient, their respective physician or caregiver, and it is understood that assigning one or more clinical trials to the patient translates to also assigning a principal investigator corresponding to that clinical trial; See Briegs Par [0010], [0139], [0247], & [0274] which discloses the assignment of personnel to conduct the trial, and pre-study visits for evaluating and assessing the potential investigator; See Briegs Par [0364]-[0366] & [0370] which discloses reports being able to contain header information such as principal investigator that has been assigned to the study);
an appointment scheduling module configured to enable the list of qualified research participants to input additional patients’ information on the research participant's computing device and to schedule an appointment with the site manager for research study screening (See Briegs Par [0110] which discloses site management and site contact modules such that the modules allow the establishment of planned visits that study subjects are expected to attend, and further describe what procedures are to be conducted at each visit, when the visits should occur, what drugs should be given and in what dosage, and so on, constituting study screening under BRI; See Briegs Par [0364]-[0366] & [0370] which discloses reports being able to contain header information such as principal investigator that has been assigned to the study),
a primary source data capturing module configured to enable, via the one or more processors, one or more principal investigators to input screening data of the one or more research participants on the principal investigator's computing device after screening the one or more research participants at a research site location in real-time (See Briegs Par [0355] which discloses providing detailed reports about the subjects/participants involved in clinical experiments including those details found in Briegs Par [0356]; See Briegs Par [0364]-[0366] & [0370] which discloses reports being able to contain header information such as principal investigator that has been assigned to the study);
The disclosure of Briegs is directly applicable to the disclosure of Das because the disclosures share limitations and capabilities, such as being directed towards optimization of the clinical-trial settings, parameters, management, etc.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Das, which already discloses optimizing methods of determining candidate participants/patients for a clinical trial, to further include an appointment scheduling module configured to enable the one or more research participants to send a request from the research participant's computing device to the research site manager's computing device for scheduling the appointment, assign one or more principal investigators for screening one or more research participants based on the one or more research participants' information, enable the list of qualified research participants to input additional patients’ information on the research participant's computing device and to schedule an appointment with the site manager for research study screening and a primary source data capturing module configured to enable one or more principal investigators to input screening data of the one or more research participants on the principal investigator's computing device after screening the one or more research participants at a research site location in real-time, as disclosed by Briegs, because these embodiments allow for substantially optimized monitoring of clinical trial processes by monitoring the entities, status of entities, and/or actions involved with the clinical trial (See Briegs Par [0364]-[0366] & [0370]).
While the combined disclosure of Das and Briegs disclose determining eligible candidates for a clinical trial, performing screening on the candidates, generating one or more screening reports, and various back-end implementations surrounding the clinical-trial settings, parameters, management, etc., they do not seem to disclose the following limitations regarding financial and generation of an invoice based on said embodiments:
the list generating module is further configured to filter the generated list of qualified research participants based on the availability of principal investigators for screening as determined by the appointment scheduling module;
a financial module configured to collect, via the one or more processors, the screening data in real-time and calculate accounts receivable from a sponsor thereby send the screening data to a data review and reports generating module, wherein the data review and reports generating module configured to generate one or more screening reports as the amount of money that is owed to a research site location and send the one or more screening reports to an invoice generating; and
an invoice generating module configured to generate, via the one or more processors, an invoice based on the one or more screening reports of the one or more research participants and send the invoice to the sponsor's computing device, the data review and reports generating module configured to enable the sponsor to review the invoice on the sponsor computing device.
However, Rosenberg discloses the following limitations:
a financial module configured to collect, via the one or more processors, the screening data in real-time (See Rosenberg Par [0015], [0087], & [0089] which discloses facilitating site payments in a clinical trial based on different actions performed throughout the trial such as specifically mentioned in Rosenberg Par [0087] that may have been performed such that an invoice can be generated for a sponsor based on different medical tests or procedures performed such as at a certain site versus others) and calculate accounts receivable from a sponsor thereby send the screening data to a data review and reports generating module, wherein the data review and reports generating module configured to generate one or more screening reports as the amount of money that is owed to a research site location and send the one or more screening reports to an invoice generating module (See Rosenberg Par [0015], [0087], & [0089] which discloses facilitating site payments in a clinical trial based on different actions performed throughout the trial such as specifically mentioned in Rosenberg Par [0087] that may have been performed such that an invoice can be generated for a sponsor based on different medical tests or procedures performed such as at a certain site versus others); and
an invoice generating module configured to generate, via the one or more processors, an invoice based on the one or more screening reports of the one or more research participants and send the invoice to the sponsor's computing device, the data review and reports generating module configured to enable the sponsor to review the invoice on the sponsor computing device (See Rosenberg Par [0015], [0087], & [0089] which discloses facilitating site payments in a clinical trial based on different medical tests or procedures that may have been performed such that an invoice can be generated for a sponsor based on different medical tests or procedures performed such as at a certain site versus others).
The disclosure of Rosenberg is directly applicable to the combined disclosure of Das and Briegs because the disclosures share limitations and capabilities, such as being directed towards optimization of the clinical-trial settings, parameters, management, etc.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combined disclosure of Das and Briegs which already discloses determining eligible candidates for a clinical trial, performing screening on the candidates, generating one or more screening reports, and various back-end implementations surrounding the clinical-trial settings, parameters, management, etc., to further include a financial module configured to collect the screening data in real-time and calculate accounts receivable from a sponsor thereby send the screening data to a data review and reports generating module, wherein the data review and reports generating module configured to generate one or more screening reports as the amount of money that is owed to a research site location and send the one or more screening reports to an invoice generating module and calculate accounts receivable from a sponsor thereby send the screening data to a data review and reports generating module, wherein the data review and reports generating module configured to generate one or more screening reports as the amount of money that is owed to a research site location and send the one or more screening reports to an invoice generating module, as disclosed by Rosenberg, because this provides the capability of making payments that are based on triggers established by certain events, such as visits, as well as when optional services are performed, for substantially optimized and streamlined payment tracking (See Rosenberg Par [0015], [0087], & [0089]).
While Das, Briegs, and Rosenberg generally disclose the generation of a list of qualified participants for clinical trials/research and/or optimizing scheduling/resources for coordinating said clinical trials, Das, Briegs, and Rosenberg do not specifically disclose filtering said list of qualified participants based on said optimizing scheduling/resources for coordinating said clinical trials as given by:
the list generating module is further configured to filter the generated list of qualified research participants based on the availability of principal investigators for screening as determined by the appointment scheduling module.
However, Green discloses the list generating module is further configured to filter the generated list of qualified research participants based on the availability of principal investigators for screening as determined by the appointment scheduling module (See Green Par [0366]-[0367] which discloses through use of a scheduling module, a rule template can be applied to control available appointment times so that patients, clinicians rooms and equipment can only be scheduled, such that a clinician can create a rule that he or she will not be available during certain times, such that the list of patients, resources, etc., can only be scheduled during the availability of the clinician, thereby constituting filtering entities based on availability of a clinician via an appointment scheduling module; See Green Par [0444]-[0445] identifying qualifying patients, such as those discussed in Par [0366]-[0367], for clinical trial via a research partner web portal, such that a list of patients is generated that satisfy the criteria, such as those defined by the rule template also in Par [0366]-[0367], can be accessed by a clinical research work flow task manager to automate scheduling between the patients and sponsors/researcher as in Green Par [0476]). The disclosure of Green is directly applicable to the combined disclosure of Das, Briegs, and Rosenberg, because the disclosures share limitations and capabilities, such as being directed towards optimization of the clinical-trial management and clinical decision-making.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the already-combined disclosure of Das, Briegs, and Rosenberg, which already discloses the generation of a list of qualified participants for clinical trials/research and/or optimizing scheduling/resources for coordinating said clinical trials, to further include the list generating module is further configured to filter the generated list of qualified research participants based on the availability of principal investigators for screening as determined by the appointment scheduling module, as disclosed by Green, because a clinical research work flow task manager can subsequently automate scheduling between the patients and sponsors/researcher for those qualifying patients that satisfy all of the inclusion criteria (See Green Par [0444]-[0445] & [0476]).
Claim 2 –
Regarding Claim 2, Das, Briegs, Rosenberg, and Green disclose the system of claim 1 in its entirety. Das further discloses a system, wherein:
the one or more research participants' information comprises health history, medical reports, and diagnosis reports (See Das Par [0009]-[0010], [0012]-[0013], [0015]-[0016], [0018]-[0019], [0038], [0058]-[0059], [0096] which describe varying patient/participant information being uploaded and input to the system for eligibility considerations by the system).
Claim 3 –
Regarding Claim 3 Das, Briegs, Rosenberg, and Green disclose the system of claim 1 in its entirety. Das further discloses a system, wherein:
the enrolment and retention module is configured to send the one or more research participants’ information to a cloud server and a central database over the network (See Das Par [0009]-[0010], [0012]-[0013], [0015]-[0016], [0018]-[0019], [0038], [0058]-[0059], [0096] which describe varying patient/participant information being uploaded and input to the system for eligibility considerations by the system; See Das Par [0089] which disclosed the computing systems containing cloud-based and centralized systems for identifying and selecting a candidate patient for enrollment and various clinical variable data associated with said candidates).
Claim 4 –
Regarding Claim 4, Das, Briegs, Rosenberg, and Green discloses the system of claim 3 in its entirety. Das further discloses as system, wherein:
the cloud server and the central database is configured to store the one or more research participants' information (See Das Par [0009]-[0010], [0012]-[0013], [0015]-[0016], [0018]-[0019], [0038], [0058]-[0059], [0096] which describe varying patient/participant information being uploaded and input to the system for eligibility considerations by the system; See Das Par [0089] which disclosed the computing systems containing cloud-based and centralized systems for identifying and selecting a candidate patient for enrollment and various clinical variable data associated with said candidates).
Claim 5 –
Regarding Claim 5, Das, Briegs, Rosenberg, and Green disclose the system of claim 1 in its entirety. Das further discloses a system, wherein:
the one or more research participants' information comprises diagnosis and medical history, patients' demographic information (e.g., age, weight, gender, race, income, and geographic location), and health-related information (e.g., clinician documentation of observations, thoughts and actions, treatments administered, patient history, medication and allergy lists, vaccine administration lists, laboratory reports, X-rays, charts, progress notes, consultation reports, procedure notes, hospital reports, correspondence, and lest results) (See Das Par [0009]-[0010], [0012]-[0013], [0015]-[0016], [0018]-[0019], [0038], [0058]-[0059], [0096] which describe varying patient/participant information being uploaded and input to the system for eligibility considerations by the system such as ethnicity, hereditary medical information, genetic information, proteomic information, microbiome information, demographic information, environmental information, diet information, lifestyle, metabolic rate, patient demographic, measurements of vital signs, physiological monitor data, blood chemistry profile, the ward in which the patient stayed, diagnosis information, treatment information, lab test results, medication data, patient clinical outcome information, clinical notes, proteomic profile, microbiome profile, imaging information
Claim 6 –
Regarding Claim 6, Das, Briegs, Rosenberg, and Green disclose the system of claim 1 in its entirety. Briegs and Rosenberg further disclose a system, wherein:
the research process optimizing module comprises a user registration module configured to enable at least one of:
the research participants; the principal investigator; and the sponsor to register (See Briegs Par [0317] & [0335]-[0339] which discloses a user, such as a site monitors, logging onto their respective system, constituting accessing a device via credentials that have been previously registered under BRI; See Rosenberg Par [0101]-[0102] which discloses site managers, study personnel, etc., being able to log onto a website and see a list of information, queries, etc.) on at least one of:
the research participant computing device; the principal investigator computing device; and the sponsor computing device by providing (See Briegs Par [0317] & [0335]-[0339] which discloses a user, such as a site monitors, logging onto their respective system, constituting accessing a device via credentials that have been previously registered under BRI; See Rosenberg Par [0101]-[0102] which discloses site managers, study personnel, etc., being able to log onto a website and see a list of information, queries, etc.)) at least one of:
user identity credentials; principal investigator identity credentials; and sponsor identity credentials (See Briegs Par [0317] & [0335]-[0339] which discloses a user, such as a site monitors, logging onto their respective system, constituting accessing a device via credentials that have been previously registered under BRI; See Rosenberg Par [0101]-[0102] which discloses site managers, study personnel, etc., being able to log onto a website and see a list of information, queries, etc.)).
Claim 7 –
Regarding Claim 7, Das, Briegs, Rosenberg, and Green disclose the system of claim 1 in its entirety. Das further discloses a system, wherein:
the enrolment and retention module is configured to optimize and improve the experience and engagement of the one or more research participants in the clinical research (See Das Par [0047] & [0093] & Fig. 1 which discloses multiple computer systems or users being connected at Fig. 1, El. 104 such as in Par [0093] the user including a user, i.e. participant, user/patient caregiver, operator, sponsor, or investigator of the clinical trial thereby suggesting a device being present for associated participant, operator, and an investigator, and further describes external alerts being provided to the user such as upon the