Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
The present office action represents the first action on the merits.
Claims 1-25 are pending.
Priority
This application claims priority to U.S. Provisional Patent Application No. 63/158,802 dated 12 April 2023, Japanese Application No. JP2023-068175 dated 19 April 2023, and U.S. Provisional Patent Application No. 63/574,876 dated 11 April 2024.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(I) because the following figure(s) is/are unreadable and/or are unsatisfactory for reproduction:
Fig. 7-9 (text in shaded areas)
The drawings are further objected to as failing to comply with 37 CFR 1.84(g) because following figure(s) do not conform to the margin requirements (note that the margin requirement includes text and that those figures in landscape are rotated accordingly to determine margins):
One inch (1”) left margin - Fig. 3-10, 13, 14;
One inch (1”) top margin – Fig. 4, 9, 12-15.
The drawings are further objected to as failing to comply with 37 CFR 1.84(p)(3) because following figure(s) contain text that is smaller than the permissible limit of 1/8”:
Fig. 7-9.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Subject Matter Free of Prior Art
The cited prior art of record fails to expressly teach or suggest, either alone or in combination, the features found within the following claims:
Claim 2 and its dependents:
The prior art of record does not teach the following contingency limitations which the Examiner notes require that the server must be capable of performing (see Ex parte RANDAL C. SCHULHAUSER, Appeal 2013-007847 (precedential)):
determine, if the first identification aspect does not match, whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared exact study name;
determine, if the exact study name does not match, whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared second identification aspect; and
determine, if the second identification aspect does not match, whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared keyword aspect.
The closest prior art:
Verstraete et al. (U.S. Pre-Grant Patent Publication No. 2023/0124321) teaches at Para. 0052-0054 determining ID matches between historical clinal trial recruitment data and claims data, but does not teach the nested contingencies of the claim.
Claim 6 and its dependents and Claim 23:
The prior art of record does not teach the following:
determine a proportion of payment corresponding to an entity relative to a total study payment;
determine a completeness score of each of the merged data entries.
The closest prior art:
Verstraete et al. (U.S. Pre-Grant Patent Publication No. 2023/0124321) teaches at Para. 0038, 0078 that payments to a particular facilitator (entity) is known, but does not teach determining the payment in proportion to the total clinical trial cost.
Griessbach et al. (Resource use and costs of investigator-sponsored randomized clinical trials in Switzerland, Germany, and the United Kingdom: a metaresearch study) teaches determining a total clinical trial cost, but does not teach the proportion of the total cost paid to an entity.
Manon et al. (U.S. Pre-Grant Patent Publication No. 2016/0147953) teaches creating a combined data set from historical clinical trial data and payer insurance data but does not disclose anything related to a score of the completeness of the combined data.
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 1-25 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.
Claims 1, 23, 24, and 25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claim recites a system, computer-implemented method, and non-transitory computer readable medium (“CRM”) for clinical trial data and payment data aggregation.
Step 2A1
The limitations of
Claim 1
retrieve a plurality of clinical trial records;
map each of the plurality of clinical trial records to one or more of a plurality of payment records from a payment database, manifesting a set of mapped records;
merge each of the plurality of clinical trial records with the one or more of the plurality of payment records based on the set of mapped records, forming a merged dataset comprising a plurality of merged data entries;
estimate imputed enrollees for each of the merged data entries;
aggregate one or more ranking factors for each of the merged data entries;
determine a ranking for each of the one or more ranking factors for each of the merged data entries;
determine a score for each of the merged data entries based on the rankings for each of the one or more ranking factors for each of the merged data entries; and
generate a visualizer based on at least the score for each of the merged data entries.
Claim 23
retrieving a plurality of clinical trial records;
mapping each of the plurality of clinical trial records to one or more of a plurality of payment records from a payment database, manifesting a set of mapped records, further comprising the steps of:
determining whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared first identification aspect;
determining, if the first identification aspect does not match, whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared exact study name;
determining, if the exact study name does not match, whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared second identification aspect; and
determining, if the second identification aspect does not match, whether each of the plurality of clinical trial records and the one or more of the plurality of payment records comprise a shared keyword aspect; and
merging each of the plurality of clinical trial records with the one or more of the plurality of payment records based on the set of mapped records, forming a merged dataset comprising a plurality of merged data entries;
estimating imputed enrollees for each of the merged data entries, further comprising the steps of:
determining a proportion of payment corresponding to an entity relative to a total study payment;
determining whether a study includes one or more foreign clinical operation sites; and
determining a completeness score of each of the merged data entries; and
aggregating one or more ranking factors for each of the merged data entries;
determining a ranking for each of the one or more ranking factors for each of the merged data entries;
determining a score for each of the merged data entries based on the rankings for each of the one or more ranking factors for each of the merged data entries, further comprising the steps of:
receiving a weight for each of the one or more ranking factors; and
applying the weight for each of the one or more ranking factors to each of the one or more rankings before determining the score for each of the merged data entries; and
generating a visualizer based on at least the score for each of the merged data entries.
Claim 24
retrieve a plurality of clinical trial records;
map each of the plurality of clinical trial records to one or more of a plurality of payment records from a payment database, manifesting a set of mapped records;
merge each of the plurality of clinical trial records with the one or more of the plurality of payment records based on the set of mapped records, forming a merged dataset comprising a plurality of merged data entries;
estimate imputed enrollees for each of the merged data entries;
aggregate one or more ranking factors for each of the merged data entries;
determine a ranking for each of the one or more ranking factors for each of the merged data entries;
determine a score for each of the merged data entries based on the rankings for each of the one or more ranking factors for each of the merged data entries; and
generate a visualizer based on at least the score for each of the merged data entries,
wherein the visualizer comprises a map component divided into a plurality of geographical regions,
wherein a disease prevalence heatmap is applied over the map component,
wherein each of geographical regions includes a discrete disease prevalence,
wherein the visualizer comprises a specialty selector comprising a plurality of specialties,
wherein actuation of one or more of the plurality of specialties generates a plurality of markers, and
wherein the plurality of markers includes a visible gradient, and
wherein the visible gradient is based on the score for each of the merged data entries.
Claim 25
retrieving a plurality of clinical trial records;
mapping each of the plurality of clinical trial records to one or more of a plurality of payment records from a payment database, manifesting a set of mapped records;
merging each of the plurality of clinical trial records with the one or more of the plurality of payment records based on the set of mapped records, forming a merged dataset comprising a plurality of merged data entries;
estimating imputed enrollees for each of the merged data entries;
aggregating one or more ranking factors for each of the merged data entries, the one or more ranking factors comprising at least one of a sponsor metric, a clinical efficacy metric, and a regulatory risks metric,
wherein the sponsor metric is a function of at least one of: a proportion of that times that a given clinical trial site is recruited by sponsors; and whether the given clinical trial site is a newly selected site,
wherein the clinical efficacy metric is a function of at least one of: whether a primary endpoint and a secondary endpoint of a given indication show correlation;
whether a placebo effect threshold is surpassed; whether the primary endpoint surpasses an efficacy threshold; and whether an expert-informed condition is met,
wherein the expert-informed condition is based on a plurality of sub-flags,
wherein each of the plurality of sub-flag are one of a high flag, a medium flag, and a low flag,
wherein the expert-informed condition is not met when at least one of a high flag threshold, medium flags threshold, and low flag threshold is surpassed, and
wherein the regulatory risks metric is a function of at least one of:
a chance of inspection for a given clinical trial site,
a quantity of citations associated with the given clinical trial site; and
a date of last inspection of the given clinical trial site;
determining a ranking for each of the one or more ranking factors for each of the merged data entries;
determining a score for each of the merged data entries based on the rankings for each of the one or more ranking factors for each of the merged data entries; and
generating a visualizer based on at least the score for each of the merged data entries.
, as drafted, are processes that, under the broadest reasonable interpretation, cover certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for recitation of generic computer components. That is, other than reciting a system, computer-implemented method, or CRM, the claimed invention amounts to managing personal behavior or interaction between people. For example, but for the system, computer-implemented method, or CRM, this claim encompasses a person analyzing data entries and outputting a visualization in the manner described in the identified abstract idea(s), supra. The Examiner notes that Applicant’s Background section of the Specification describes clinical trial data analysis as a human task. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of (Claims 1, 24) a server having at least one processor, at least one database, and at least one memory and a client device having at least one processor, at least one display, at least one memory, (Claim 23) a computer having a database, (Claim 25) a CRM/processing device that implement the identified abstract idea(s). The server, client device, computer, and/or CRM/processing device are not described by the applicant and are recited at a high-level of generality (i.e., generic computers performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claims 1, 23, 24, and 25 further recite the additional element of (1) a clinical trial database while Claim 1 recites the additional element of (2) bidirectional communication. The clinical trial database and bidirectional communication merely generally links the abstract idea(s) to a particular technological environment or field of use. MPEP 2106.04(d)(I) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application. Accordingly, even in combination, this additional element does not integrate the abstract idea into a practical application.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a server, client device, computer, and/or CRM/processing device to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”).
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of (1) a clinical trial database while Claim 1 recites the additional element of (2) bidirectional communication were determined to generally link the abstract idea to a particular technological environment or field of use. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide significantly more. Regarding the bidirectional communication, the Examiner also notes that the Applicant has described this as being known to those having skill in the art (Spec. Para. 0184) meaning it is also well-understood, routine, and conventional. Accordingly, even in combination, this additional element does not provide significantly more. As such the claim is not patent eligible.
Claims 2-22 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide as inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination:
Claim(s) 2 merely describe(s) determining additional data based on whether matching exists.
Claim(s) 3 merely describe(s) the type of identification.
Claim(s) 4 merely describe(s) extracting and matching keywords.
Claim(s) 5 merely describe(s) discovering keywords. Claim(s) 5 also includes the additional element of “a natural language processing model” which generally links the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(I) and MPEP 2106.05(A) indicate that merely “generally linking” the abstract idea to a particular technological environment or field of use cannot provide a practical application or significantly more.
Claim(s) 6, 8 merely describe(s) determining additional data.
Claim(s) 7 merely describe(s) adding payment data.
Claim(s) 9 merely describe(s) comparing data and determining whether data is complete or not based on the comparison.
Claim(s) 10 merely describe(s) calculating imputed enrollees from data.
Claim(s) 11 merely describe(s) receiving and applying weights to data.
Claim(s) 12, 13, 14, 15, 16 merely describe(s) how data is displayed.
Claim(s) 17, 18, 19, 20, 21 merely describe(s) the ranking factors.
Claim(s) 22 merely describe(s) how ranking factors are determined.
Claim Rejections - 35 USC § 102
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 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 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.
Claim(s) 1, 24, and 25 is/are rejected under 35 U.S.C. § 102(a)(1) or 35 U.S.C. § 102(a)(2) as being anticipated by Manon et al. (U.S. Pre-Grant Patent Publication No. 2016/0147953).
Note: the drawings contained within the ‘953 reference are of poor quality. The Examiner has attached the drawing to the present action, but doubts the resolution will be any better than the ‘953 publication. Applicant is directed to the publicly-available file wrapper for the associated application, which contains clearer drawings, including color drawings.
REGARDING CLAIM 1
Menon teaches the claimed system, comprising:
a server comprising at least one server processor, at least one server database, at least one server memory comprising computer-executable server instructions which, when executed by the at least one server processor, cause the server to: [Para. 0013, 0022 teaches a computing system (server) that implements the disclosed functionality.]
retrieve a plurality of clinical trial records from a clinical trial database; [item 108, 116, Fig. 1, Para. 0013, 0014, 0051 teaches that clinical trial historical data that is stored in a database is received from clinical trial organizations (a clinical trial database).]
map each of the plurality of clinical trial records to one or more of a plurality of payment records from a payment database, manifesting a set of mapped records; [item 109,111, Fig. 1, Para. 0013, 0052 teaches that payer insurance data is received (payment records). Para. 0014, 0053 teaches that the historical clinical trial data is integrated (mapped) with the insurance claims data.]
merge each of the plurality of clinical trial records with the one or more of the plurality of payment records based on the set of mapped records, forming a merged dataset comprising a plurality of merged data entries; [Para. 0014, 0053 teaches that the integrated data is combined to form a universal data set (a merged dataset), therefore all the payer insurance data (one or more of the plurality of payment records) is integrated (merged) with all the historical clinical trial data (each of the plurality of clinical trial records). The Examiner notes that there is no indication as to how the records are merged.]
estimate imputed enrollees for each of the merged data entries; [Para. 0051 teaches that the number of patients that participated in a clinical trial part of the historical clinical trial performance data which is part of the universal data set (merged data). The Examiner interprets the actual number of past clinical to indicate the estimated imputed enrollees.]
aggregate one or more ranking factors for each of the merged data entries; [Para. 0054 teaches that multiple KPIs (ranking factors) are determined from the universal data set.]
determine a ranking for each of the one or more ranking factors for each of the merged data entries; [Para. 0025, 0041, 0055 teaches that a score for each KPI is determined and that a ranked list for individual KPIs is determined.]
determine a score for each of the merged data entries based on the rankings for each of the one or more ranking factors for each of the merged data entries; and [Para. 0006, 0025, 0041 performance indicator score for particular physician is determined from weighted KPIs.]
a client device in bidirectional communication with the server, the client device comprising at least one device processor, at least one display, at least one device memory comprising computer-executable device instructions which, when executed by the at least one device processor, cause the client device to: [Para. 0028, 0040 teaches that clients (inclusive of a client device) receive reports which include the scores.]
generate a visualizer based on at least the score for each of the merged data entries. [Para. 0028, 0030, 0040 teaches that the client displays (generates a visualizer) the reports including the scores.]
REGARDING CLAIM(S) 24
Claim(s) 24 is/are analogous to Claim(s) 1, thus Claim(s) 24 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1.
Menon further teaches
wherein the visualizer comprises a map component divided into a plurality of geographical regions, [Fig. 4 teaches a map having counties.]
wherein a disease prevalence heatmap is applied over the map component, [Fig. 7, Para. 0046 teaches that patients diagnosed with a particular condition are overlayed on the map and that the colors of the map represent the number/density of diagnosed patients (i.e., a heatmap).]
wherein each of geographical regions includes a discrete disease prevalence, [Fig. 7, Para. 0046 teaches that each county has a color representing the number/density of diagnosed patients.]
wherein the visualizer comprises a specialty selector comprising a plurality of specialties, wherein actuation of one or more of the plurality of specialties generates a plurality of markers, and [Fig. 4, Para. 0041 teaches that the data investigators on the map can be filtered by therapeutic area (specialty) using a drop down menu (an actuation) and results in pins for the providers being displayed on the map.]
wherein the plurality of markers includes a visible gradient, and [Fig. 4, Para. 0041 teaches that the size and color of the pins varies (both visible gradients).]
wherein the visible gradient is based on the score for each of the merged data entries. [Fig. 4 teaches that the color of the pin indicates the investigator’s score.]
REGARDING CLAIM(S) 25
Claim(s) 25 is/are analogous to Claim(s) 1, thus Claim(s) 25 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1.
Menon further teaches
aggregating one or more ranking factors for each of the merged data entries, [Para. 0025 teaches that the KPIs, which are based on the universal data set are collected (aggregated).]
the one or more ranking factors comprising at least one of
a sponsor metric,
a clinical efficacy metric, and a
regulatory risks metric, [Para. 0032, 0038 teaches that KPIs include regulatory audits (a regulatory risks metric).]
wherein the sponsor metric is a function of at least one of:
a proportion of that times that a given clinical trial site is recruited by sponsors; and
whether the given clinical trial site is a newly selected site,
wherein the clinical efficacy metric is a function of at least one of:
whether a primary endpoint and a secondary endpoint of a given indication show correlation;
whether a placebo effect threshold is surpassed;
whether the primary endpoint surpasses an efficacy threshold; and
whether an expert-informed condition is met,
wherein the expert-informed condition is based on a plurality of sub-flags, wherein each of the plurality of sub-flag are one of a high flag, a medium flag, and a low flag, wherein the expert-informed condition is not met when at least one of a high flag threshold, medium flags threshold, and low flag threshold is surpassed, and
wherein the regulatory risks metric is a function of at least one of:
a chance of inspection for a given clinical trial site, [Para. 0038 teaches that regulatory audits indicate how frequently the investigator and thus an investigator’s site generated regulatory audits, which is an indicator of the chance of future regulatory audits (inspection).]
a quantity of citations associated with the given clinical trial site; and
a date of last inspection of the given clinical trial site;
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Graiver et al. (U.S. Pre-Grant Patent Publication No. 2018/0046780) which discloses a system for structuring clinical trials using NLP and for allowing patient’s to find clinical trials via the web.
Verstraete et al. (U.S. Pre-Grant Patent Publication No. 2023/0124321) which discloses a clinical trial site evaluation system that uses historical clinical trail data and patient claims data to train a machine learning model.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON S TIEDEMAN whose telephone number is (571)272-4594. The examiner can normally be reached 7:00am-4:00pm, off alternate Fridays.
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/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683