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, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 6, 2026 has been entered.
Status of Claims
Claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 are currently pending. Claims 3-4, 6-7, 10, 16, 21-22, 26 and 28 have been canceled. Claims 1, 11-15, 17-20, 24-25, and 29-30 have been amended.
Examiner notes there is no prior art rejection for claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 at this time.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on May 6, 2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments, see page 11 regarding 35 USC 112(a) and 112(b) have been fully considered and are persuasive. The previous rejections of claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 under 35 USC 112(a) and claims 11-13, 17-20, 23-25 under 35 USC 112(b) have been withdrawn.
Applicant's arguments on pages 12-18 regarding 35 USC 101 filed May 6, 2026 have been fully considered but they are not persuasive.
Claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30, under their broadest reasonable interpretation, are directed to the abstract idea of mental processes and/or data analysis, including collecting information, comparing data against criteria, determining eligibility, and generating predictions based on that evaluation. See MPEP § 2106.04(a)(2). The limitations reciting retrieval of patient records from a distributed EMR/EHR database, executing queries, applying a similarity comparison, determining eligible patients over discrete epochs, generating a longitudinal trajectory of patient eligibility, generating candidate enrollment counts and corresponding probability values, and combining those values to produce a predicted enrollment, collectively amount to the type of information gathering, evaluation, and prediction that may be performed in the human mind or by a person with pen and paper, even if more efficiently carried out by a computer. Accordingly, the claims are directed to an abstract idea under Step 2A, Prong One of the 2019 Revised Patent Subject Matter Eligibility Guidance. See MPEP § 2106 and MPEP § 2106.04.
Applicant argues that the claims cannot be practically performed in the human mind because they recite retrieving data from a distributed EMR/EHR database. This argument is not persuasive. The mere recitation of a computer, database, or electronic record source does not, by itself, remove the claim from the realm of abstraction where the focus of the claim remains on the analysis of information and generation of a prediction. The claims do not recite any specific technological improvement to the computer, database architecture, network structure, or data retrieval mechanism. Rather, they invoke generic computer implementation to perform the abstract idea. See MPEP § 2106.05(f).
Applicant further contends that the claims integrate the alleged judicial exception into a practical application because they allegedly improve digital health record-based clinical trial enrollment prediction. This argument is not persuasive. Under Step 2A, Prong Two, the claims do not recite an improvement to the functioning of a computer or to any other technology or technical field. See MPEP § 2106.05(a). The claims do not identify a particular machine, a particular transformation, a specific way of improving computer operation, or any other meaningful limitation that integrates the abstract idea into a practical application. Instead, the claims merely use generic computer components to perform a predictive analysis on patient data. The claims are directed to the result of analyzing information, not to a technological solution rooted in computer technology.
Applicant’s reliance on the specification is also unpersuasive. While the specification may describe problems associated with enrollment prediction and may characterize the invention as useful in the clinical trial context, the eligibility analysis must be based on what the claims recite, not on the problem statement or aspirational advantages described in the specification. A claim does not become patent eligible merely because it is applied in a useful field or because it addresses a real-world problem. See MPEP § 2106.05(a). Here, the claims recite a method of evaluating patient records and generating enrollment predictions, which is an abstract analytical task, not a technical improvement.
Applicant’s citations to external references describing the difficulty of clinical trial recruitment are likewise not persuasive as to eligibility. The fact that the underlying problem may be difficult or important does not render the claimed subject matter patent eligible. Nor do such references establish that the claimed limitations amount to an improvement to computer functionality or any other technology. Instead, the cited materials support only that enrollment prediction is a useful and challenging endeavor.
Applicant’s reliance on Ex parte Desjardins and recent USPTO memoranda is also unavailing. Unlike claims that recite a specific improvement to how a machine learning model operates or a particular technological mechanism, the present claims do not recite an improvement to the operation of the computer itself, to the database architecture, or to the EMR/EHR system. Rather, the claims use conventional computing tools to perform data retrieval, eligibility comparison, counting, and prediction. Such use of generic computer implementation does not amount to a practical application under MPEP § 2106.05(a), (f), or (g).
Even if the claims are considered to recite an abstract idea, the claims do not include additional elements that amount to significantly more than the judicial exception itself. See MPEP § 2106.05. The additional claim elements are recited at a high level of generality and merely instruct the use of generic computing devices and data structures to perform the abstract idea. There is no indication that the claims recite an inventive concept, unconventional arrangement, or non-routine combination sufficient to transform the abstract idea into patent-eligible subject matter. See MPEP § 2106.05(d), (e), and (f). A conclusory assertion that the claims are implemented using distributed EMR/EHR data and eligibility-based processing is insufficient to demonstrate that the ordered combination is anything other than conventional computerization of an abstract predictive task.
For at least the foregoing reasons, the claims, considered as a whole, are directed to a judicial exception without significantly more. Accordingly, the rejection of claims 1, 3, 4, 10-15, 17, and 19-28 under 35 U.S.C. § 101 is maintained.
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 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
In the instant case, claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, and 27 are directed to methods (i.e. processes), while claim 29 is directed to a system (i.e. a machine) and claim 30 is directed to a non-transitory computer-readable medium (i.e. a manufacture). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A- Prong 1
Independent claims 1, 29, and 30 recite steps that, under their broadest reasonable interpretations, cover Mental Processes, e.g. concepts performed in the human mind (including an observation, evaluation, judgement, opinion). Specifically, claim 1 recites:
A computer-implemented method for generating site-specific clinical trial enrollment predictions of a clinical trial, the method comprising:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, for each clinical trial site in a first set of one or more clinical trial sites, a corresponding set of patient records from a corresponding plurality of patient records for the respective clinical trial site, each patient record in the corresponding set of patient records comprising a plurality of time-stamped clinical values corresponding to a set of eligibility criteria for the clinical trial wherein retrieval comprises: executing a set of queries that apply a similarity comparison, for each patient record in the plurality of patient records, between the plurality of time-stamped clinical values and the set of eligibility criteria for the clinical trial;
B) generating, for each clinical trial site in the first set of clinical trial sites, a longitudinal trajectory of patient eligibility by processing the corresponding set of patient records for the clinical trial site to determine a number of eligible patients at the clinical trial site for each epoch in a plurality of discrete epochs in a first time period
C) for each clinical trial site in the first set of clinical trial sites, generating, from the longitudinal eligibility trajectory of patient eligibility, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal trajectory of patient eligibility; and
D) for each site-specific enrollment dataset, processing the dataset by combining the candidate enrollment counts with their corresponding probability values to produce a site-specific predicted enrollment for the clinical trial site for the second time period.
Similarly, claim 29 recites:
A computer system comprising:
one or more processors; and
a non-transitory computer-readable medium including computer-executable instructions that, when executed by the one or more processors, cause the processors to perform a method for generating site-specific clinical trial enrollment predications for a clinical trial, the method comprising:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, for each clinical trial site in a first set of one or more clinical trial sites, a corresponding set of patient records from a corresponding plurality of patient records for the respective clinical trial site, each patient record in the corresponding set of patient records comprising a plurality of time-stamped clinical values corresponding to a set of eligibility criteria for the clinical trial wherein retrieval comprises: executing a set of queries that apply a similarity comparison, for each patient record in the plurality of patient records, between the plurality of time-stamped clinical values and the set of eligibility criteria for the clinical trial;
B) generating, for each clinical trial site in the first set of clinical trial sites, a longitudinal trajectory of patient eligibility by processing the corresponding set of patient records for the clinical trial site to determine a number of eligible patients at the clinical trial site for each epoch in a plurality of discrete epochs in a first time period
C) for each clinical trial site in the first set of clinical trial sites, generating, from the longitudinal eligibility trajectory of patient eligibility, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal trajectory of patient eligibility; and
D) for each site-specific enrollment dataset, processing the dataset by combining the candidate enrollment counts with their corresponding probability values to produce a site-specific predicted enrollment for the clinical trial site for the second time period.
Similarly, claim 30 recites:
a non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to perform a method for generating site-specific clinical trial enrollment predications for a clinical trial, the method comprising:
A) retrieving from a distributed electronic medical record (EMR) or electronic health record (EHR) database, for each clinical trial site in a first set of one or more clinical trial sites, a corresponding set of patient records from a corresponding plurality of patient records for the respective clinical trial site, each patient record in the corresponding set of patient records comprising a plurality of time-stamped clinical values corresponding to a set of eligibility criteria for the clinical trial wherein retrieval comprises: executing a set of queries that apply a similarity comparison, for each patient record in the plurality of patient records, between the plurality of time-stamped clinical values and the set of eligibility criteria for the clinical trial;
B) generating, for each clinical trial site in the first set of clinical trial sites, a longitudinal trajectory of patient eligibility by processing the corresponding set of patient records for the clinical trial site to determine a number of eligible patients at the clinical trial site for each epoch in a plurality of discrete epochs in a first time period
C) for each clinical trial site in the first set of clinical trial sites, generating, from the longitudinal eligibility trajectory of patient eligibility, a site-specific enrollment dataset for a second time period different from the first time period, the generating comprising:
(i) identifying a set of candidate enrollment counts, and
(ii) for each candidate enrollment count in the set of candidate enrollment counts, determining a corresponding probability value derived from the longitudinal trajectory of patient eligibility; and
D) for each site-specific enrollment dataset, processing the dataset by combining the candidate enrollment counts with their corresponding probability values to produce a site-specific predicted enrollment for the clinical trial site for the second time period.
But for the recitation of generic computer components like non-transitory computer-readable storage medium, processor, and electronic medical record (EMR) or electronic health record (EHR) database, the italicized steps, when considered as a whole, are directed to the abstract idea of mental processes and/or data analysis. The claim recites elements, bolded above, which covers performance of the limitation that can be concepts performed in the mind of a person, with pen and paper (e.g., a person with pen and paper can draw graphs and make determinations from it) or using a generic computer (see MPEP 2106.04(a)(2) Ill C) to perform a judicial exception has been shown to be abstract.
Dependent claims 2, 5, 8-9, 11-15, 17-20, 23-25, and 27 inherit the limitations that recite an abstract idea from their dependence on claims 1, 29, or 30, respectively, and thus these claims also recite an abstract idea under the Step 2A- Prong 1 analysis. In addition, claims 2, 5, 8-9, 11-15, 17-20, 23-25, and 27 recite additional limitations that further describe and limit the abstract idea identified in the independent claims. Examiner notes that claims 12, 13, 17 and 18 are also abstract as reciting a mathematical concept (mathematical relationships and/or calculations). See MPEP 2106.04(a)(2).
Claim 2 recites wherein determining the longitudinal trajectory comprises, for a respective patient in the first plurality of patient records: determining by natural language processing the corresponding plurality of time-stamped clinical values that is valid for a respective epoch in the plurality of discrete epochs for the respective patient from an EMR or an EHR of the respective patient, or determining by natural language processing at least one time-stamped clinical value in a corresponding plurality of clinical values that is valid for the respective epoch for the respective patient from unstructured data in the EMR or EHR of the respective patient.
Claim 5 recites wherein retrieval of the plurality of time-stamped clinical values further comprises: queries querying structured clinical data in the EMR or EHR for a respective patient in the plurality of patients with a string-matching algorithm to identify a time-stamped clinical value that is valid for an epoch in the plurality of discrete epochs for the respective patient, or applying a large language model to the EMR or EHR for a respective patient in the plurality of patients to identify a time-stamped clinical value that is valid for an epoch in the plurality of epochs for the respective patient.
Claim 8 recites wherein the set of eligibility criteria comprises at least one exclusion criterion.
Claim 9 recites wherein the clinical trial is for treatment of a cancer condition and the set of eligibility criteria comprises a diagnosis of the cancer condition, administration of one or more prior therapies for the cancer condition, absence or presence of one or more biomarkers, one or more demographic parameters, or any combination thereof.
Claim 11 recites wherein the A) retrieving of claim 1 further comprises, for a respective patient in the plurality of patients, clustering medical entries from a EMR or a EHR for the respective patient by date and assigning a corresponding earliest eligibility date for the clinical trial based on a date associated with a clustered medical entry that is an earliest indication that the respective patient met the set of eligibility criteria for the clinical trial.
Claims 12 recites wherein the plurality of time-stamped clinical values for the plurality of patients associated with the first set of one or more clinical trial sites spans the first time period, and a respective site-specific predictive enrollment metric for the first set of one or more clinical trial sites is calculated as a measure of central tendency for the number of patients identified, in each epoch of the first time period, as satisfying the set of eligibility criteria applied in step A) of claim 1.
Claim 13 recites wherein the measure of central tendency is a mean of the number of patients identified as satisfying the set of eligibility criteria applied in step A) of claim 1.
Claim 14 recites wherein the plurality of time-stamped clinical values for the plurality of patients associated with the first set of one or more clinical trial sites spans the first time period, and a respective site-specific predictive enrollment metric for the first set of one or more clinical trial sites is determined as a trend in the number of patients identified at the first set of one or more sites over a subset of the first time period.
Claim 15 recites wherein a respective site-specific predicted enrollment metric for the first set of one or more clinical trial sites represents an expected number of patients, identified in the longitudinal trajectory of patient eligibility as newly satisfying the clinical trial eligibility criteria relative to a preceding epoch, over the first time period.
Claim 17 recites wherein a respective site-specific predicted enrollment for the second time period is obtained by forming a statistical distribution of possible enrollment counts
Claim 18 recites wherein the statistical distribution is a Poisson distribution established using a factor of the respective site-specific predicted enrollment as the mean of the Poisson distribution.
Claim 19 recites further comprising repeating steps A) through D) of claim 1 for each respective additional set of one or more clinical trial sites in a plurality of additional sets of one or more clinical trial sites, thereby predicting a corresponding site-specific predicted enrollment for the first time period or the second time period for each respective additional set of one or more clinical trial sites.
Claim 20 recites further comprising: ranking the first set of one or more clinical trial sites and each respective additional set of one or more clinical trial sites in the plurality of additional sets of one or more clinical trial sites based on the corresponding site-specific predicted enrollment for the clinical trial at the corresponding site-specific clinical trial site, or selecting a group of clinical trial sites for the clinical trial based on a comparison between the site-specific predicted enrollment metric for the first set of one or more clinical trial sites and the corresponding predicted site-specific enrollment metric for each respective additional set of one or more clinical trial sites.
Claim 23 recites wherein the first set of one or more clinical trial sites is a single clinical trial site, and each respective additional set of one or more clinical trial sites in the plurality of additional sets of one or more clinical trial sites is a single respective clinical trial site.
Claim 24 recites further comprising: updating the set of eligibility criteria with one or more revised eligibility criteria for the clinical trial; and repeating steps A) through D) of claim 1, thereby predicting a corresponding site-specific predicted enrollment for the first time period or the second time period for the updated set of eligibility criteria.
Claim 25 recites further comprising selecting an eligibility criterion for the clinical trial based on a comparison between a site-specific predicted enrollment for the eligibility criteria prior to the update and the corresponding site-specific predicted enrollment for each respective updated set of eligibility criteria.
Claim 27 recites further comprising opening recruitment for the clinical trial or administering a treatment in the clinical trial to a patient.
Step 2A- Prong 2
The judicial exception is not integrated into a practical application. In particular, independent claims 1, 29, and 30 do not include additional elements that integrate the abstract idea into a practical application. Claims 1, 29, and 30 each include the additional elements of computer system, processors, memory, electronic medical record (EMR) or electronic health record (EHR) database, and non-transitory computer-readable medium. These additional elements, when considered in the context of each claim as a whole, merely serve to automate the gathering of data, analysis and making determinations. The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). See Applicant’s specification para. [77-78] regarding computer systems. The database is also recited at a high-level of generality (i.e., as generic data collections access by computers) such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1, 29, and 30 are directed to an abstract idea without a practical application.
The judicial exception recited in dependent claims 2, 5, 8-9, 11-15, 17-20, 23-25, and 27 is also not integrated into a practical application under a similar analysis as above because they are performed with the same additional elements identified in the independent claims in addition to natural language processing and large language model that appear to be software and are also recited at a high level of generality.
Step 2B
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 integration of the abstract idea into a practical application, the additional computer system, processors, memory, electronic medical record (EMR) or electronic health record (EHR) database, and non-transitory computer-readable medium are generic in nature and recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). See Applicant’s specification para. [77-78] regarding computer systems. Analyzing these additional elements as an ordered combination adds nothing that is not already present when considering the elements individually; the overall effect of the various computing devices in combination is to automate the gathering of data, analysis and making determinations that could otherwise be achieved as a mental process. Thus, when considered as a whole and in combination, claims 1-2, 5, 8-9, 11-15, 17-20, 23-25, 27 and 29-30 directed to an abstract idea and thus not patent eligible.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAHID R MERCHANT whose telephone number is (571)270-1360. The examiner can normally be reached M-F 7:30-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Namrata Boveja can be reached at 571-272-8105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
Prosecution Insights