DETAILED ACTION
Status of Claims
This action is in reply to the communication filed on 8 December, 2025.
Claims 1 and 10 have been amended.
Claims 3 and 12 have been cancelled.
Claims 1, 4 – 10 and 13 – 19 are currently pending and have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8 December, 2025 has been entered.
Claim Interpretation
The claims recite terms that invite interpretation. The claims recite a method for generating information related to a secondary clinical trial for a drug by acquiring and analyzing information obtained from a previously performed, primary clinical trial for the drug. The specification discloses that “it is significant to select appropriate subjects . . . in order to increase the success rate of clinical trials.” (See the specification as filed @ 0002, 0042) Information related to the secondary clinical trial may be provided in a report that includes information regarding a subject who is a candidate for the (secondary) clinical trial and biomarker information to be used for design of the (secondary) clinical trial. (@ 0036)
Subjects from the primary clinical trial may be selected for the secondary clinical trial for a drug based on the subject’s responsitivity to the drug, which is determined by analyzing information regarding the primary clinical trial for the drug, in particular, changes in biological elements related to candidate biomarkers observed on pathological slides of the subject taken before and after administration of the drug. (@ 0042, 0068) The term “responsitivity” is given its ordinary meaning: “A measure of the degree to which something is responsive”. Here, biomarkers indicate responsitivity based on their expression levels before/after administration of the drug. Subjects who are expected to have a high responsitivity to the drug may be selected. (@ 0131) The results from the primary clinical trial may also be used to set a criterion related to responsitivity to the drug for selecting subjects. (@ 0043) The criterion is disclosed as a “cut-off value corresponding to the at least one biomarker” used as a criterion for distinguishing responders from non-responders (@ 0065, 0066, 0126) The criterion may be set using a generic machine learning model. (@ 0151, 0161)
Information from the primary clinical trial includes a dataset, stored by a server, of various types of information acquired during the primary clinical trial, and responsitivity results from the drug. The system uses a generic pre-trained machine learning model to analyze pathological slide images in the dataset to identify “biological features” that predict responsitivity of the drug. (@ 0044) Biological features determined from the pathological slide images include “biological elements related to a biomarker” obtained from images taken before administration of the drug and after administration, and compared. (@ 0053, 0067) The system performs an association analysis between the treatment results (i.e. responsitivity) of a subject and the biomarkers, such as biomarker expression levels of a genome related to a mechanism of the drug. (@ 0063) A biomarker has a high association with the drug when the expression level of the biomarker shows a great change before and after the administration of the drug (@ 0100, 0142) – information indicating an association between the drug and each of the candidate biomarkers; determining a least one biomarker among the candidate biomarkers based on the first information and the second information. Nonetheless, the first information and second information described above is acquired from memory. (@ 0062)
As such, the broadest reasonable interpretation of the claims includes acquiring information regarding a primary clinical trial from a generic machine learning model; and information indicating drug to biomarker associations – i.e. biomarkers that predict drug responsitivity from a server memory. The criterion, or cut-off value may be calculated by examining the expression levels for responders and comparing that to non-responders. The information related to the secondary clinical trial includes identification information for one or more subjects who participated in the primary clinical trial, who also share a biomarker that has been associated with a drug response, where the biomarker has an expression level above (or below) the cut-off value (i.e. a criterion).
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.
The following rejection is formatted in accordance with MPEP 2106.
Claim 10 is representative. Claim 10 recites:
A method of analyzing a biomarker, the method comprising:
generating first information regarding a primary clinical trial previously performed on a certain drug by analyzing, using a machine learning model, pathological slide images of subjects in the primary clinical trial, wherein the analyzing comprises segmenting the pathological slide images into patch regions and detecting cells expressing candidate biomarkers using the machine learning model, wherein the first information includes expression levels of the candidate biomarkers, and the machine learning model is trained to detect the cells and quantify the expression levels of the candidate biomarkers in the cells;
acquiring second information indicating an association between the drug and each of candidate biomarkers, wherein the second information comprises at least one of an expression level of at least one genome related to a mechanism of the drug in a cell, a relationship between expression locations of the candidate biomarkers and a location at which the drug acts in a cell, and a genome oncogenic addiction related to a cell;
determining a least one biomarker among the candidate biomarkers based on the first information and the second information;
analyzing a relationship between survival times of the subjects in the primary clinical trial and the at least one biomarker based on a responsitivity to the drug indicated by the first information and the second information;
setting a criterion of the at least one biomarker, based on the relationship; and
generating information related to a secondary clinical trial based on the set criterion.
Claim 19 recites medium with instructions executed by a processor, and Claim 1 recites an apparatus that executes the steps of the method recited in Claim 10.
Claims 1, 4 – 10 and 13 – 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), and does not include additional elements that either: 1) integrate the abstract idea into a practical application, or 2) that provide an inventive concept – i.e. element that amount to significantly more than the abstract idea. The Claims are directed to an abstract idea because, when considered as a whole, the plain focus of the claims is on an abstract idea.
STEP 1
The claims are directed to an apparatus, a method and non-transitory computer readable medium which are included in the statutory categories of invention.
STEP 2A PRONG ONE
The claims, as illustrated by Claim 10, recite limitations that encompass an abstract idea within the “certain methods of organizing human activity” grouping –
managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions including:
generating first information regarding a primary clinical trial previously performed on a certain drug by analyzing, pathological slide images of subjects in the primary clinical trial, wherein the analyzing comprises segmenting the pathological slide images into patch regions and detecting cells expressing candidate biomarkers, wherein the first information includes expression levels of the candidate biomarkers;
acquiring second information indicating an association between the drug and each of candidate biomarkers, wherein the second information comprises at least one of an expression level of at least one genome related to a mechanism of the drug in a cell, a relationship between expression locations of the candidate biomarkers and a location at which the drug acts in a cell, and a genome oncogenic addiction related to a cell;
determining a least one biomarker among the candidate biomarkers based on the first information and the second information;
analyzing a relationship between survival times of the subjects in the primary clinical trial and the at least one biomarker based on a responsitivity to the drug indicated by the first information and the second information;
setting a criterion of the at least one biomarker, based on the relationship; and
generating information related to a secondary clinical trial based on the set criterion.
The claims recite a process for generating information related to selecting subjects to participate in a secondary clinical trial for a drug, from among subjects who participated in a primary clinical trial for the drug, and who meet a criterion related to drug responsitivity for a particular biomarker having a known association with the drug – i.e. generating information related to a secondary clinical trial. Selecting subject who meet a selection criteria comprises an abstract filtering process (See MPEP 2106.04(a)(2) II C). The specification discloses that selecting appropriate subjects for a clinical trial is significant to the clinical trial’s success. Indeed, this type of activity, i.e. selecting subjects for a clinical trial, includes conduct that would normally occur when designing such a trial. For example, it is routine for a clinical trial design to specify appropriate participants using exclusion and/or inclusion criteria. As such, the claims recite an abstract idea within the certain methods of organizing human activity grouping.
The claims, as illustrated by Claim 10, also recite limitations that encompass an abstract idea within the “mental processes” grouping – concepts performed in the human mind including observation, evaluation, judgment and opinion. The claims recite collecting and analyzing information to obtain a result, which is an ordinary mental process.
Collecting information, including when limited to particular content, is within the realm of abstract ideas, and analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, are mental processes within the abstract idea category (Electric Power Group v. Alstom S.A. (Fed Cir, 2015-1778, 8/1/2016).
The first information is acquired by analyzing pathological slides, and the second information is obtained from a memory. Determining a biomarker among the candidates is disclosed as selecting a biomarker that distinguishes between a responder and a non-responder – that is a biomarker that shows a significant change after application of the drug of interest distinguished responders from non-responders. Determining a criterion, or cut-off, is disclosed as observing the difference in responsitivity above and below the cut-off value (@ 0122). Similarly generating information related to a secondary trial is disclosed as selecting patients having the selected biomarker value over the criterion/cut-off/threshold. For example, patients may be selected who have a “TIL density” greater than or equal to the cut-off value. (@ 0126) Such comparisons, observations and judgments, are processes that, except for generic computer implementation steps, can be performed in the human mind. As such, the claims recite an abstract idea within the mental process grouping.
STEP 2A PRONG TWO and STEP 2B
The claims recite additional elements beyond those that encompass the abstract idea above including:
using a machine learning model for analyzing pathological slide images, and
the machine learning model is trained to detect the cells and quantify the expression levels of the candidate biomarkers in the cells.
However, these additional elements do not integrate the abstract idea into a practical application of that idea in accordance with the MPEP. (see MPEP 2106.05).
In particular, the claims apply established methods of machine learning to an abstract filtering process in a new data environment – i.e. applying a trained model to the pathological slide images. The specification broadly discloses the “machine learning-based analysis” or “AI-based biomarker analysis system”. There is no recitation of a particular kind of machine learning model, such as a neural network, random forest, decision tree, etc. Training the model is also generically disclosed and claimed. Machine learning limitations reciting broad, functionally described, well-known techniques executed by generic and conventional computing devices, as in the pending claims here, does not provide a practical application of, or an inventive concept to, the abstract diagnostic process. “Today we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under §101.” (Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. 2025)).
Claim 1 and 19 recite additional structural elements or combination of elements, other than the abstract idea per se, that amounts to no more than a recitation of generic computer structure (i.e. a computing apparatus/processor and memory, computer-readable medium). Each of the above components are disclosed in the specification as being purely conventional and/or known in the industry. Because the specification describes these additional elements in general terms, without describing particulars, Examiner concludes that the claim limitations may be broadly, but reasonably construed, as reciting well-understood, routine and conventional computer components and techniques. The specification describes the elements in a manner that indicates that they are sufficiently well-known that the specification does not need to describe the particulars in order to satisfy U.S.C. 112. Considered as an ordered combination the limitations recited in the claims add nothing that is not already present when the steps are considered individually. As such, the additional elements recited in the claim do not integrate the abstract idea into a practical application, nor do they provide significantly more than the abstract participant selection process, or an inventive concept.
The dependent claims add additional features including:
those that merely serve to further narrow the abstract idea above such as:
using the biomarker/cut-off as criterion to distinguish responders and non-responders (Claims 5, 14);
further limiting the type of information related to the secondary trial (Claims 6, 15);
further limiting the type of information related to the biomarker (Claims 7, 16);
those that recite additional abstract ideas such as:
determining cut-off values (Claims 4, 13);
collecting first and second slide images and set the criteria based on a change between them (Claims 8, 17);
those that recite well-understood, routine and conventional activity or computer functions such as:
outputting a report (Claims 9, 18);
those that recite insignificant extra-solution activities;
or those that are an ancillary part of the abstract idea.
The limitations recited in the dependent claims, in combination with those recited in the independent claims add nothing that integrates the abstract idea into a practical application, or that amounts to significantly more. These elements merely narrow the abstract idea, recite additional abstract ideas, or append conventional activity to the abstract process. As such, the additional element do not integrate the abstract idea into a practical application, or provide an inventive concept that transforms the claims into a patent eligible invention.
The apparatus claims are no different from the method claims in substance. “The equivalence of the method, system and media claims is readily apparent.” “The only difference between the claims is the form in which they were drafted.” (Bancorp). The method claims recite the abstract idea implemented on a generic computer, while the apparatus claims recite generic computer components configured to implement the same idea. Specifically, Claims 1, 4 – 9 and 19 merely add the generic hardware noted above that nearly every computer will include. The apparatus claim’s requirement that the same method be performed with a programmed computer does not alter the method’s patentability under U.S.C. 101 (In re Grams). Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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, 4 – 8, 10, 13 - 17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Polidori et al.: (US PGPUB 2005/0197785 A1) in view of Mock et al.: (US PGPUB 2014/0357660 A1) in view of Van Leeuwen et al.: (US PGPUB 2021/0366107 A1) and in view of Bacus: (US PGPUB 2001/0044124 A1).
CLAIMS 1, 10 and 19
Polidori discloses a system and method for analyzing subject data that includes the following limitations:
generating first information regarding a primary clinical trial previously performed on a drug, wherein the first information includes expression levels of candidate biomarkers; acquiring second information indicating an association between the drug and each of candidate biomarkers; (Polidori 0006, 0010, 0034, 0041, 0047 – 0052, 0067);
determining a least one biomarker among the candidate biomarkers based on the first information and the second information;
analyzing a relationship between [a response to therapy] of the subjects in the primary clinical trial and the at least one biomarker based on a responsitivity to the drug indicated by the first information and the second information; (Polidori 0034, 0050, 0052, 0053);
setting a criterion of the at least one biomarker, based on the relationship; (Polidori 0034, 0052, 0053); and
generating information related to a secondary clinical trial based on the set criterion; (Polidori 0053).
Polidori discloses a processor-readable medium and method for receiving data for subjects of a published clinical trial, and calculating values for a set of biomarkers indicative of the subjects’ responsiveness to a therapy (i.e. a metabolic parameters) using a regression analysis applied to the data. Values are calculated before the therapy is applied, and again after the therapy is applied; and then compared. A metabolic parameter is identified as a biomarker for a therapy when a larger change in the value of the biomarker from a baseline is correlated with a response to therapy such as a greater effectiveness of the therapy.
Polidori defines a biomarker as a characteristic that predicts a particular response to the therapy, such as effectiveness; for example, when a larger change in the value of the biomarker is correlated with greater effectiveness of the therapy (i.e. second information indicating an association between the drug and each of candidate biomarkers). The biomarker value may be used in numerous applications including as an inclusion or exclusion criteria to select a group of subject for the clinical trial, such that the clinical trial can target subject who are likely to respond well to the therapy.
With respect to the following limitations:
analyzing a relationship between survival times of the subjects in the primary clinical trial and the at least one biomarker based on a responsitivity to the drug indicated by the first information and the second information; (Mock 0112, 0133 – 0135, 0191, 0194, 0197, 0346, 0354 – 0356, 0372, 0377 – 0381).
Polidori discloses correlating a responsivity of the therapy (i.e. drug), based on expression levels of a biomarker before and after treatment with the therapy, with a response to the therapy, but does not disclose that the response includes survival times of the subjects. Mock discloses gene expression signatures of neoplasm responsiveness to therapy that includes linking (i.e. correlating) gene expression signatures (i.e. a biomarker) to a responsiveness to therapy that includes a length of survival after treatment. Subjects with a neoplasm determined to be responsive to the therapy are selected for further treatment. Mock applies a predictive model to determine the biomarkers that are correlated with survival time. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the clinical trial subject selection system of Polidori to include analyzing a relationship or correlation between survival times and the biomarker based on responsivity to the therapy, in accordance with the teaching of Mock, in order to allow for predicting the survival time of the subject after treatment.
With respect to the following limitations:
generating first information . . . by analyzing, using a machine learning model, pathological slide images of subjects in the primary clinical trial, and the machine learning model is trained to detect the cells and quantify the expression levels of the candidate biomarkers in the cells; (Van Leeuwen 0010 – 0015, 0022, 0073, 0074, 0082 – 0088, 0091);
wherein the analyzing comprises segmenting the pathological slide images into patch regions and detecting cells expressing candidate biomarkers using the machine learning model; (Van Leeuwen 0032, 0073, 0074, 0183, 0184).
Polidori/Mock discloses a biological characteristic measurement using any number of functional, biochemical, and physical techniques (@ 0033, 0041). Polidori/Mock discloses using statistical techniques such as regression analysis, correlation analysis (@ 0006, 0043, 0052), but does not expressly disclose a machine learning model that detects biological elements in pathological slides. Van Leeuwen discloses a digital pathology system that includes dividing the pathological image into sectors, and analyzing each sector of the pathological slide images with machine learning techniques to classify objects in the pathological slide images that represent the expression of a biomarker. The machine learning algorithm has been trained on a corpus of example digital pathology images that have been labelled by an expert, using well-known machine learning training techniques – i.e. supervised/ unsupervised learning, etc. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the clinical trial subject selection system of Polidori/Mock so as to have included analyzing pathological slides relative to treatment efficacy based on biomarker expression levels, in accordance with the teaching of Van Leeuwen, in order to allow for predicting the response to therapy based on a simple biopsy.
With respect to the following limitations:
wherein the association is determined based on at least one of an expression level of at least one genome related to a mechanism of the drug in a cancer cell, a relationship between expression locations of the candidate biomarkers and a location at which the drug acts, and a genome oncogenic addiction related to the cancer cell; (Bacus 0003, 0009 – 0017, 0022). (Bacus 0003, 0009 – 0017, 0022, 0033).
Polidori/Mock/Leeuwen discloses obtaining information relative to subjects of a primary clinical trial and selecting subjects for a secondary clinical trial based on subjects having a biomarker associated with therapy effectiveness. Polidori/Mock/Leeuwen does not disclose determining the association based on one of expression levels of a genome related to the drug, expression/action locations, and oncogenic addiction characteristics. Bacus teaches a system and method for determining the response to cancer therapy that includes using image analysis of pathological slides to assess the efficacy of therapeutic agents by detecting expression levels of biomarkers in images taken before and after treatment. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the clinical trial subject selection system of Polidori/Mock/Leeuwen so as to have included obtaining information from pathological slides relative to treatment efficacy based on biomarker expression levels, in accordance with the teaching of Bacus, in order to allow for predicting the response to therapy based on a simple biopsy.
CLAIMS 4 - 7 and 13 - 16
The combination of Polidori/Mock/Leeuwen/Bacus discloses the limitations above relative to Claims 1 and 10. Additionally, Polidori discloses the following limitations:
wherein the setting includes a cut-off value corresponding to the at least one biomarker to set the criterion related to the responsitivity to the drug; (Polidori 0052, 0053) – disclosing determining a biomarker as an inclusion or exclusion criteria;
wherein the at least one biomarker or the cut-off value is used as a criterion for distinguishing between a responder and a non-responder to the drug from among the subjects of the primary clinical trial; (Polidori 0052, 0053) – discloses distinguishing responders from non-responders;
wherein the information related to the secondary clinical trial includes at least one of information regarding at least one subject of the secondary clinical trial and information related to the at least one biomarker to be used for design of the secondary clinical trial; (Polidori 0053) – disclosing selecting subjects for a clinical trial.
wherein the information related to the at least one biomarker includes at least one of an identifier of the at least one biomarker, a cut-off value corresponding to the at least one biomarker, predictive power information related to the responsitivity of the at least one biomarker to the drug, a list in which the at least one biomarker is arranged according to a certain criterion, and a relationship between the at least one biomarker and a result of the primary clinical trial; (Polidori 0034, 0041, 0043, 0051 – 0053) – disclosing identifying a biomarker and it respective criteria for inclusion or exclusion.
CLAIMS 8 and 17
The combination of Polidori/Mock/Leeuwen/Bacus discloses the limitations above relative to Claims 1 and 10. Additionally, Bacus discloses the following limitations:
acquiring, for each of the subjects of the primary clinical trial, a first pathological slide image of a tissue collected before administration of the drug and a second pathological slide image of a tissue collected after the administration of the drug; (Bacus 0003, 0016, 0017, 0026, 0033).
Polidori/Mock/Leeuwen discloses obtaining information relative to subjects of a primary clinical trial and selecting subjects for a secondary clinical trial based on subjects having a biomarker associated with therapy effectiveness. Bacus teaches a system and method for determining the response to cancer therapy that includes using image analysis of pathological slides taken before and after treatment, to assess the efficacy of therapeutic agents by detecting changes in expression levels of biomarkers in the images. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the clinical trial subject selection system of Polidori/Mock/Leeuwen so as to have included obtaining information from pathological slides relative to treatment efficacy based on biomarker expression levels, in accordance with the teaching of Bacus, in order to allow for predicting the response to therapy based on a simple biopsy.
With respect to the following limitation:
wherein the setting includes setting the criterion related to the responsitivity to the drug based on a change between the first pathological slide image and the second pathological slide image; (Polidori 0011, 0033, 0034, 0052, 0053).
Polidori discloses setting a criteria related to responsitivity based on changes in biomarker levels measured using experimental or clinical tests to produce a test result using any number of functional, biochemical and physical techniques (@ 0033). Polidori does not disclose setting the criterion based on image analysis, however, as shown above, Bacus does. It would have been obvious to one of ordinary skill to include well-known pathological image analysis techniques representing any number of functional, biochemical and physical techniques disclosed in Bacus.
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Polidori et al.: (US PGPUB 2005/0197785 A1) in view of Mock et al.: (US PGPUB 2014/0357660 A1) in view of Van Leeuwen et al.: (US PGPUB 2021/0366107 A1) and in view of Bacus: (US PGPUB 2001/0044124 A1) in view of Walton: (US PGPUB 2014/0046926 A1).
CLAIMS 9 and 18
The combination of Polidori/Mock/Leeuwen/Bacus discloses the limitations above relative to Claims 1 and 10. With respect to the following limitations:
outputting a report including the information related to the secondary clinical trial on a display; (Walton 0003, 0061, 0070, 0132, 0133, 0140, 0150).
Polidori/Mock/Leeuwen/Bacus discloses selecting subjects from a first clinical trial who have a biomarker of interest, for a second clinical trial (i.e. information related to a secondary clinical trial), but does not disclose displaying the results in a report. The specification discloses that the report may be an image output to the user terminal. Walton discloses a system and method for searching a genomic database that includes identifying patient who match a clinical trial’s inclusion criteria, including genetic characteristics, and displaying a report of the results. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the clinical trial subject selection system of Polidori/Mock/Leeuwen/Bacus so as to have included outputting a report for display, in accordance with the teachings of Walton, in order to allow for human review.
Response to Arguments
Applicant's arguments filed 8 December, 2025 have been fully considered but they are not persuasive.
The §101 Rejection
Applicant asserts that the claims recite patent-eligible subject matter by “generating information for assisting the design of the secondary clinical trial”; resulting in “the improvement of a success rate of clinical trials” and “promoting the approval of companion diagnostics”. Applicant asserts that a clinical trail success rate may be improved by analyzing biomarkers to predict responders or non-responders.
Initially, Examiner notes that “companion diagnostics” are not addressed in the claims. With respect to improving the success rate of the clinical trial, Examiner notes that the term “success” is not defined by the specification. The National Institute of Health defines a clinical trial success rate as the percentage of trials that result in “a new drug registration”. As such, improving the success rate, as described here, is not a technological problem “that is necessarily rooted in the computer technology itself.” The problem of selecting appropriate candidates for a clinical trial is a business problem, even though the proposed solution uses computer technology as a tool.
Applicant asserts that the claims “solve a real problem with a claimed solution that improves the analyzing a biomarker, as well as, the success rate of clinical trials, and that is necessarily rooted in the computer technology itself.”
No computer function created the problem related to selecting candidates for a clinical trial, and no computer functionality is improved here. Further the purported improving the analysis of a biomarker merely improves the abstract idea itself. It is unclear to the Examiner, and the Applicant does not explain, how the problem of selecting clinical trial candidates is “necessarily rooted in the computer technology itself.”
Applicant further asserts a practical application involving all of the steps in the method, which indicates that they all are additional limitations to be analyzed under Step 2 Prong Two and Step 2B. In particular, Applicant asserts that the claims provide for “generating information for assisting design of the secondary clinical trial” based on the results of the primary clinical trial. But designing a clinical trial is an age old process, and assisting in that design merely organizes that human activity; improving, not some technological process, but the abstract idea itself. Applicant also asserts that the claims “improve the success rate of clinical trials”; however, this is not commensurate with the scope of the claims. The secondary trial information that is generated is not applied to a secondary trial to realize such an improvement in success rate. No information is given that discloses how such an improvement would be determined. Further, when clinical trials have a low success rate because participants were not properly screened for inclusion or exclusion criteria, it is not because of some technological process that is in need of improvement. Selecting information for analysis is abstract.
Applicant asserts that the claims “solve a real problem . . . that is necessarily rooted in the computer technology itself”, as in DDR Holdings. The problem - “selecting appropriate subjects to participate in a clinical trial” – is not a technological problem, nor does the Applicant point to any place in the specification that describes such a problem. The claims gather information about a primary clinical trial using known techniques and determine a biomarker and cut-off value that secondary trial participants should have.
The §103 Rejections
Applicant asserts that Polidori/Leeuwen does not disclose analyzing a relationship to survival times. Examiner agrees. However, on further search and consideration, a new grounds of rejection is made in view of Mock et al.
Applicant traverses Examiner taking Official Notice in rejections Claims 8 and 19. Without acquiescing that “controlling a display to output a report” is not common knowledge, Official Notice is no longer relied on.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PGPUB 2015/0307947 A1 to Basu et al. discloses a system and method for preparing and displaying a report comprising subject eligible for a clinical trial based on expression levels of biomarkers.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to John A. Pauls whose telephone number is (571) 270-5557. The Examiner can normally be reached on Mon. - Fri. 8:00 - 5:00 Eastern. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773.
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/JOHN A PAULS/Primary Examiner, Art Unit 3683
Date: 24 January, 2026