DETAILED ACTION
Status
This communication is in response to the application filed on 9 October 2025 and preliminary amendment filed on 19 December 2025. Claims 169-188 are pending and presented for examination.
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 .
Priority
Applicant’s claim for the benefit under 35 U.S.C. 119(e) to U.S. Provisional Application No. 63/705,860, filed on 10 October 2024, is acknowledged.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), fourth paragraph:
Subject to the [fifth paragraph of 35 U.S.C. 112 (pre-AIA )], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 170-172 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 170 recites “wherein the parameter of the clinical trial comprises power, alpha, a sample size, an endpoint of the trial, or any combination thereof”; however, the term “alpha” is not used or apparently described in the specification. The only mentions of “alpha” (or any apparent derivations of the term) is Applicant ¶ 0102 (as submitted) indicating that “In some embodiments, the disease, the disorder, or the medical condition comprises … Alpha 1-antitrypsin deficiency, … [or] Hypoalphalipoproteinemia (Tangier disease)”. Therefore, there is a lack of written description regarding “alpha” being a parameter that is or can be determined.
Claims 171-172 depend from claim 170, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 171-172 are also lacking written description support.
Claims 169-188 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Independent claim 169 recites “d) selecting, by the first user via the first user interface on the electronic display, a prioritization function that assigns ranked values to each of the plurality of treatment outcomes, wherein the ranked values are selected by the first user based at least in part on (1) subject-level efficacies and subject-level adverse effects of individual treatment outcomes of the plurality of treatment outcomes on the subject and (2) a personalized preference of the subject”; however, it is indefinite what limitation is present. The claim phrasing indicates a user selection of a function that assigns a ranked value to a treatment outcome, but this is “based … on” either efficacies or adverse effects on the subject, or “a personalized preference of the subject”.
First, the only antecedent basis for the term “the subject” would appear to be “a treatment set of subjects” and/or “a reference set of subjects”. So as a first issue, it is indefinite whether “the subject” is referring to a treatment subject or a reference subject. A possible third interpretation may be that “the subject” is actually supposed to be referring to the first user; however, the treatment outcomes are recited as being “on the subject”, so this may appear less likely than a subject from either the treatment or reference sets.
Second, it is indefinite what limitation is presented by the choice of the first user selection being required to be based on (1) efficacies and adverse effects, and (2) a personalized preference of the subject. It would appear that since the first user is making the selection, literally anything that is NOT based on efficacies and adverse effects would apparently be considered as being based on a/the “personalized preference of the subject” – the selection itself apparently indicates some understanding or belief that it is a personal preference.
Third, it is not explained how “the first user” would possibly know what the “personalized preference of the subject” would be. If the first user is a subject from the treatment or reference set, then it is supposed that they can choose whatever they may please – it is a “personalized preference” since they chose whatever selection is entered; however, if the first user is NOT a treatment or reference subject, there is no indication the examiner has found regarding how they would possibly know the preferences of the subject.
Fourth, there is “a dataset for a treatment set of subjects and a reference set of subjects” – implying that there is more than one person, or at least one person (i.e., subject) as a treatment subject and one as a reference subject. But there could be MANY persons in the dataset and/or in the treatment set or reference set. Therefore, as a fourth basis of indefiniteness, there is no indication of how “the subject” is identified so that it would be possible to know what their respective “personalized preference” (of the subject) would be.
Fifth, element d) of claim 169 recites “selecting, by the first user … a prioritization function”; however, dependent claim 177 (which ultimately, or indirectly depends from claim 169 recites “wherein d) further comprises receiving the user input, thereby generating the prioritization function at least in part based on the user input”. This presents a chicken-and-egg conundrum – it appears physically impossible to select the prioritization function if or when the input is generating the function since it must be in existence in order to select it; however, if it is merely generated based on the user input, then it can’t be selected by that same input. Therefore, as a fifth basis of indefiniteness, it is indefinite at claim 169 whether the prioritization function is being selected or not, or whether the input is merely some basis for generating a prioritization function.
Sixth, independent claim 169 includes treatment outcomes (at least at elements “a)”, “b)”, “c)”, and “d)”) and simulated outcomes (at least at elements “e)” and “f)”), as well as benefit scores (at least at elements “f)” and “g)”). Applicant ¶ 0038 (as submitted, 0037 as published) says “In many clinical settings, particularly in randomized trials of experimental therapies, multiple outcomes, or endpoints, are of interest”, so the light of the specification apparently indicates an outcome of a trial or treatment as an endpoint. This would appear to agree with the meaning(s) indicated by the pertinent prior art below. HOWEVER, later, in Applicant ¶ 0039 (as submitted, 0038 as published), says “The methods and systems provided herein may be applied to designing many aspects of a clinical trial using the NTB as a primary endpoint, for example, calculating the number of human subjects (e.g., sample size) required for the trial.” Dependent claim 170 recites an endpoint as a possible parameter of the clinical trial, and dependent claim 175 recites an endpoint as a possible variable. Therefore, as a sixth basis of indefiniteness, it is indefinite throughout the claims (including claim 169) what would be considered a parameter, a variable, and/or an endpoint.
Claims 170-188 depend from claim 169, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 170-188 are also indefinite.
Claim 170 recites “wherein the parameter of the clinical trial comprises power, alpha, a sample size, an endpoint of the trial, or any combination thereof”; however, the term “alpha” is not used or apparently described in the specification. Therefore, it is indefinite as to what “alpha” would possibly mean as a parameter that is or can be determined.
Claims 171-172 depend from claim 170, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 171-172 are also indefinite for this reason.
Claim 170 recites “wherein the parameter of the clinical trial comprises power, alpha, a sample size, an endpoint of the trial, or any combination thereof”; however, the term “power” is apparently indefinite. The only apparent antecedent basis for “power” is parent claim 169 referring to “simulated trial power scores”, but the power scores are at least part of the basis for determining the parameter at parent claim 169, and therefore not the parameter itself. The specification also discusses the power scores, but also indicates “power as a function of total sample size” (Applicant ¶ 0017), and discusses “power” (Applicant ¶ 0041), and that “the method provided herein comprises determining a function of sample size and power (e.g., g., a power function)” and again that” the power of the trial is a function of the sample size” (Id.). Therefore, it is indefinite as to what “power” would mean as a determined parameter.
Claims 171-172 depend from claim 170, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 171-172 are also indefinite for this reason.
Claims 176 and 181-182 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim 176 depends indirectly from independent claim 169 and recites “wherein d) further comprises receiving a user input through the computing device” – referring to step d) at parent claim 169 that says “d) selecting, by the first user via the first user interface on the electronic display” and element c) at claim 169 indicates “a first user interface on a first electronic display of the first computing device”. Therefore, parent claim 169 already requires receiving the selection through the computing device. As such, claim 176 fails to further limit the subject matter of the claim upon which it depends.
Claim 181 depends indirectly from independent claim 169 and recites “wherein the user input represents a candidate subject of the clinical trial”. Claim 182 similarly recites “where the user input represents a subject of the clinical trial”. However, parent independent claim 169 recites that the user input is “selecting, by the first user … a prioritization function that assigns ranked values to each of the plurality of treatment outcomes” – not a candidate subject or a subject. Therefore, it appears that claims 181 and 182 each cancel the selection of the prioritization function and replaces it with a selection of a candidate subject. As such claims 181 and 182 fail to include all the limitations of the claim upon which it depends.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 169-188 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see the following Subject Matter Eligibility (“SME”) analysis:
For analysis under SME Step 1, the claims herein are directed to a method, which would be classified under one of the listed statutory classifications (SME Step 1=Yes).
For analysis under revised SME Step 2A, Prong 1, independent claim 169 recites a method of using a graphical user interface to assist in determination of a clinical study parameters, comprising: a) obtaining a dataset for a treatment set of subjects and a reference set of subjects, wherein the treatment set of subjects receives a clinical intervention during the clinical trial and the reference set of subjects does not receive the clinical intervention during the clinical trial, and wherein the dataset comprises a plurality of treatment outcomes for the treatment set of subjects and the reference set of subjects during the clinical trial; b) receiving, on a first computing device, the plurality of treatment outcomes for the treatment set of subjects and the reference set of subjects, wherein the plurality of treatment outcomes are transmitted over a computer network; c) presenting to a first user, via a first user interface on a first electronic display of the first computing device, a representation of the plurality of treatment outcomes; d) selecting, by the first user via the first user interface on the electronic display, a prioritization function that assigns ranked values to each of the plurality of treatment outcomes, wherein the ranked values are selected by the first user based at least in part on (1) subject-level efficacies and subject-level adverse effects of individual treatment outcomes of the plurality of treatment outcomes on the subject and (2) a personalized preference of the subject; e) performing, by a computer processor, a plurality of simulated clinical trials using the dataset and the prioritization function, thereby producing a set of simulated outcomes; f) processing the set of simulated outcomes to generate a set of simulated net treatment benefit scores and a set of simulated trial power scores, wherein the processing comprises performing a set of pairwise comparisons between a first subject selected from the treatment set of subjects and a second subject selected from the reference set of subjects for each of the simulated outcomes in the set of simulated outcomes; g) determining a parameter for the clinical trial based on the set of simulated net treatment benefit scores and the set of simulated trial power scores; and h) presenting to a second user, via a second user interface on a second electronic display of a second computing device, a report comprising the parameter for the clinical trial
The dependent claims (claims 170-188) appear to be encompassed by the abstract idea of the independent claims since they merely indicate trial parameters (claim 170), sample size (claim 171), the trial endpoint as ranked or prioritized endpoints (claim 172), modeling variables of simulated trials (claim 173-174), what the variables comprise (claim 175), receiving user input (claim 176), generating the prioritization function based on the user input (claim 177), determining dependency of treatment outcomes or threshold of clinical relevance based in part on the user input (claims 178-179), the user input being on a set of pairwise clinical scenarios (claim 180), the user input represents a candidate subject or a subject of the clinical trial (claims 181-182), including at least 10, 50, or 100 pairwise clinical scenarios (claim 183), the pairwise scenarios comprise administering clinical intervention (claim 184) such as a drug treatment (claim 185), the first and second users and computing devices are the same (claim 186), what the treatment outcome comprises (claim 187), and/or what the simulated net treatment benefit scores comprise (claim 188).
The underlined portions of the claims are an indication of elements additional to the abstract idea (to be considered below).
The claim elements may be summarized as the idea of simulating a clinical trial to help determine a possible trial parameter; however, the Examiner notes that although this summary of the claims is provided, the analysis regarding subject matter eligibility considers the entirety of the claim elements, both individually and as a whole (or ordered combination). This idea is within the following grouping(s) of subject matter:
Mathematical concepts (e.g., relationships, formulas, equations, and/or calculations) based on selecting a prioritization function, then simulating a clinical trial where the simulation necessarily performing the calculation of simulated outcomes and the benefit and power scores;
Certain methods of organizing human activity (e.g. … commercial or legal interactions such as … business relations; and/or managing personal behavior or relationships between people such as social activities, teaching, and following rules or instructions) since the clinical trial and simulated clinical trial is/are a/the relationship between persons (the subject test groups and differences in outcomes); and
Mental processes (e.g., concepts performed in the human mind such as observation, evaluation, judgment, and/or opinion) since the simulation does not require any apparent level of granularity, accuracy, or precision; therefore, such relatively imprecise calculations could be performed mentally.
Therefore, the claims are found to be directed to an abstract idea.
For analysis under revised SME Step 2A, Prong 2, the above judicial exception is not integrated into a practical application because the additional elements do not impose a meaningful limit on the judicial exception when evaluated individually and as a combination. The additional elements are using a graphical interface, activity on a first computing device, the plurality of treatment outcomes [being] transmitted over a computer network; presenting via a first user interface on a first electronic display of the first computing device, the selecting of a function being via the first user interface on the electronic display, and performing activities by a computer processor. These additional elements do not reflect an improvement in the functioning of a computer or an improvement to other technology or technical field, effect a particular treatment or prophylaxis for a disease or medical condition (there is no specific medical disease or condition, much less a treatment or prophylaxis for one), implement the judicial exception with, or by using in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing (there is no transformation/reduction of a physical article), and/or apply or use the judicial exception in some other meaningful way beyond generically linking use of the judicial exception to a particular technological environment.
The claims appear to merely apply the judicial exception, include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform the abstract idea. The additional elements appear to merely add insignificant extra-solution activity to the judicial exception and/or generally link the use of the judicial exception to a particular technological environment or field of use.
For analysis under SME Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as indicated above, are merely “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity
There is no indication the Examiner can find in the record regarding any specialized computer hardware or other “inventive” components, but rather, the claims merely indicate computer components which appear to be generic components and therefore do not satisfy an inventive concept that would constitute “significantly more” with respect to eligibility. Applicant ¶ 0111 (as submitted, 0103 as published) says “a computing system comprises a computer device, including but not limited to a mobile computer, smartphone, smartwatch, tablet, electronic notebook, laptop, or any combination thereof” – i.e., generic or general purpose computers are encompassed as the conceived computers.
The individual elements therefore do not appear to offer any significance beyond the application of the abstract idea itself, and there does not appear to be any additional benefit or significance indicated by the ordered combination, i.e., there does not appear to be any synergy or special import to the claim as a whole other than the application of the idea itself.
The dependent claims, as indicated above, appear encompassed by the abstract idea since they merely limit the idea itself; therefore the dependent claims do not add significantly more than the idea.
Therefore, SME Step 2B=No, any additional elements, whether taken individually or as an ordered whole in combination, do not amount to significantly more than the abstract idea, including analysis of the dependent claims.
Please see the Subject Matter Eligibility (SME) guidance and instruction materials at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility, which includes the latest guidance, memoranda, and update(s) for further information.
NOTICE
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.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 169-188 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bhattacharya et al. (U.S. Patent Application Publication No. 2021/0241866, hereinafter Bhattacharya)
Claim 169: Bhattacharya discloses a method of using a graphical user interface to assist in determination of a clinical study parameters (see Bhattacharya at least at, e.g., ¶ 0588, “a design platform 11300 with an interface 11310 for configuring and managing the platform 10404 with respect to optimizing site selection for patient recruitment for a clinical trial … Embodiments of the interface 11310 may be a graphical user interface (GUI) that has one or more input fields 11314 for inputting or selecting selection parameters. The input fields 11314 may be sliders, text boxes, moveable components, and/or other GUI user input widgets”; citation hereafter by number only), comprising:
a) obtaining a dataset for a treatment set of subjects and a reference set of subjects, wherein the treatment set of subjects receives a clinical intervention during the clinical trial and the reference set of subjects does not receive the clinical intervention during the clinical trial, and wherein the dataset comprises a plurality of treatment outcomes for the treatment set of subjects and the reference set of subjects during the clinical trial (0197, “a platform for evaluation and comparison of trial designs for treatments for subjects. As used herein, treatments may include procedures, diagnostic tests, devices, diets, placebos, drugs, vaccines, and the like. Treatments may include combinations of drugs, devices, procedures and/or therapies. References to subjects throughout this disclosure should also be understood to be references to people, animals, plants, organisms and other living elements”, 0302, “Population models may define characteristics of subjects in a clinical trial. A trial design may define aspects of subjects that should be included in a trial. A trial design may define inclusion and exclusion criteria for subjects based on characterizations of demography, disease status, and the like”);
b) receiving, on a first computing device, the plurality of treatment outcomes for the treatment set of subjects and the reference set of subjects, wherein the plurality of treatment outcomes are transmitted over a computer network (0273, “trained via supervised learning”, including treatment effect, and “the clinical trial training set may account for the outcomes of past clinical trial designs”);
c) presenting to a first user, via a first user interface on a first electronic display of the first computing device, a representation of the plurality of treatment outcomes 0267, “User inputs may be compared to historical data, such as data stored in data facility 138 (FIG. 1), e.g., previous designs, inputs, and/or outcomes”);
d) selecting, by the first user via the first user interface on the electronic display, a prioritization function that assigns ranked values to each of the plurality of treatment outcomes, wherein the ranked values are selected by the first user based at least in part on (1) subject-level efficacies and subject-level adverse effects of individual treatment outcomes of the plurality of treatment outcomes on the subject and (2) a personalized preference of the subject (0738, “Designs with scores that are comparable may be presented and/or recommended to a user and ranked or filtered according to the score. In embodiments, the proxy score may be computed during one or more collaborative session for design analysis. In such embodiments, the proxy score may be based at least in part on one or more user preferences detected through one or more interactive interfaces”);
e) performing, by a computer processor, a plurality of simulated clinical trials using the dataset and the prioritization function, thereby producing a set of simulated outcomes (0424, “In embodiments, the apparatus may include a data processing circuit 5708 structured to interpret/obtain design data 5702 of a clinical trial design. In some embodiments the design data 5702 may be outputs of simulation data of trial designs”);
f) processing the set of simulated outcomes to generate a set of simulated net treatment benefit scores and a set of simulated trial power scores, wherein the processing comprises performing a set of pairwise comparisons between a first subject selected from the treatment set of subjects and a second subject selected from the reference set of subjects for each of the simulated outcomes in the set of simulated outcomes (0197, “a platform for evaluation and comparison of trial designs for treatments for subjects. As used herein, treatments may include procedures, diagnostic tests, devices, diets, placebos, drugs, vaccines, and the like. Treatments may include combinations of drugs, devices, procedures and/or therapies”, where comparison of treatments, such as for drugs and/or placebos includes pairwise comparison of subjects for outcomes);
g) determining a parameter for the clinical trial based on the set of simulated net treatment benefit scores and the set of simulated trial power scores (0232, “the apparatus may include a data processing circuit 406 structured to interpret/obtain design data 402 of a clinical trial design. In some embodiments the design data 402 may be outputs of simulation data of trial designs. The data processing circuit 406 may transform the design data 402 into a format suitable for use by the various circuits in the apparatus. For example, the design data 402 may be received by the data processing circuit 406 and determine and identify performance parameters in the data”); and
h) presenting to a second user, via a second user interface on a second electronic display of a second computing device, a report comprising the parameter for the clinical trial (0373, “reporting may be based on the types and/or number of interactions observed. In some cases reporting may provide a summary of how interactions were interpreted and used to determine preferences and/or recommended designs”).
Claim 170: Bhattacharya discloses the method of claim 169, wherein the parameter of the clinical trial comprises power, alpha, a sample size, an endpoint of the trial, or any combination thereof (0201, “Parameters may include …endpoints”, 0204 and 0633, “Parameters may include: … statistical power, incremental statistical power”, 0293, “experimental design data may include data, parameters, variables, and the like related to sample size”).
Claim 171: Bhattacharya discloses the method of claim 170, wherein the sample size is at most about 500, at most about 400, at most about 300, at most about 200, at most about 100, or at most about 50 subjects (0204, “Parameters may include: … number of patients, incremental number of patients”, 0305, “ population 3002 may include data representing individual subjects (virtual patients) …. The distribution of characteristics may be consistent with real-world data for a specific population or sub-population. The virtual population may include data for hundreds”).
Claim 172: Bhattacharya discloses the method of claim 170, wherein the endpoint of the trial comprises a plurality of ranked or prioritized endpoints (0818, “.The first data entry may be related to the “Plan” for the clinical trial. As shown in FIG. 181(a), entries related to the “Plan” may include general aspects defining types of designs. Data entry may include specifying a Target Population, Control Arm, Treatment Arm, Endpoints and the like for the study” – where, since “Endpoints” are specified, this indicates a plurality, and that they have been prioritized since specified).
Claim 173: Bhattacharya discloses the method of claim 169, further comprising modeling a set of variables of the plurality of simulated clinical trials (0424, “the design data 5702 may be outputs of simulation data of trial designs”, 0586, 0588, 0592, 0597, simulated clinical trials, 0552 and 0633, “any of the parameters and variables described herein may be incremental parameters and variables”, .0800, “enable comparing designs across multiple variables, (e.g., finding “similar designs” for a plurality of criteria)”)
Claim 174: Bhattacharya discloses the method of claim 173, further comprising modeling the set of variables of the plurality of simulated clinical trials based on historical data (0267, “User inputs may be compared to historical data, such as data stored in data facility 138 (FIG. 1), e.g., previous designs, inputs, and/or outcomes, having similar criteria as that defined by the user input”).
Claim 175: Bhattacharya discloses the method of claim 173, wherein the set of variables comprises a dropout rate of the plurality of simulated clinical trials, endpoint, a priority of the plurality of treatment outcomes, a structure of dependency of the plurality of treatment outcomes, a variance, a threshold of clinical relevance, or any combination thereof (0294, “scenario data may include one or more mathematical or numerical models and methods that are related and/or describe one or more of human behavior, disease progress, drug behavior, and the like. Scenarios may include a combination of environmental variables that provide a specification or guidelines for generating virtual patient populations for a design study. Human behavior inputs may include … dropout rates”).
Claim 176: Bhattacharya discloses the method of claim 175, wherein d) further comprises receiving a user input through the computing device (0224, “Optimality of designs may be redefined automatically, semi-automatically, in response to user input, and/or the like”).
Claim 177: Bhattacharya discloses the method of claim 176, wherein d) further comprises receiving the user input, thereby generating the prioritization function at least in part based on the user input (0297, “Ratings and/or priority may be provided by a user”).
Claim 178: Bhattacharya discloses the method of claim 176, wherein d) further comprises receiving the user input, thereby determining the dependency of the plurality of treatment outcomes at least in part based on the user input (0224, “Optimality of designs may be redefined automatically, semi-automatically, in response to user input, and/or the like”, 0297, “Ratings and/or priority may be provided by a user”).
Claim 179: Bhattacharya discloses the method of claim 176, wherein d) further comprises receiving the user input, thereby determining the threshold of clinical relevance at least in part based on the user input (0224, “Optimality of designs may be redefined automatically, semi-automatically, in response to user input, and/or the like”, 0297, “relevancy score may be computed as function of the ratings and priority score such that the higher the ratings and/or priority score the higher the relevancy score. Models that score below a threshold may be flagged or removed such that they are not simulated”).
Claim 180: Bhattacharya discloses the method of claim 176, wherein d) further comprises receiving the user input on a set of pairwise clinical scenarios (0245, “the set of scenario-design permutations may be pruned to remove permutations that are determined to have poor performance parameters or are predicted to not meet the criteria. In some cases, a database of previous simulations may be compared to the set of permutations to identify preliminary predictions”, 0431, “a framework for sensitivity analysis may compare how different combinations of design choices and scenarios affect performance criteria”).
Claim 181: Bhattacharya discloses the method of claim 180, wherein the user input represents a candidate subject of the clinical trial (0292, “.The trial design space may include one or more parameters that are … subject selection, demography, blinding of subjects”, etc., 0303, “the population model may be evaluated (with a random value for selection) to identify a new subject and the subject may be selected based on inclusion/exclusion criteria of the trial”).
Claim 182: Bhattacharya discloses the method of claim 180, where the user input represents a subject of the clinical trial (0292, “.The trial design space may include one or more parameters that are … subject selection, demography, blinding of subjects”, etc., 0303, “the population model may be evaluated (with a random value for selection) to identify a new subject and the subject may be selected based on inclusion/exclusion criteria of the trial”).
Claim 183: Bhattacharya discloses the method of claim 180, wherein the set of pairwise clinical scenarios comprise at least 10, at least 50, or at least 100 sets of pairwise clinical scenarios (0366, “A heatmap provides an interface to quickly visually compare, evaluate, and select designs. In embodiments a heatmap may provide for tens, hundreds, or even thousands of different designs with respect to tens, hundreds, or even thousands of different parameters or scenarios”).
Claim 184: Bhattacharya discloses the method of claim 183, wherein the pairwise clinical scenarios comprise administration of the clinical intervention in the subject (.
Claim 185: Bhattacharya discloses the method of claim 184, wherein the clinical intervention comprises an experimental drug treatment (0197, “treatments may include procedures, diagnostic tests, devices, diets, placebos, drugs, vaccines, and the like. Treatments may include combinations of drugs, devices, procedures and/or therapies”, 0202, “Parameters may include design type, dose of drug, frequency of drug, maximum duration, patient inclusion/exclusion criteria, randomization type, and the like. The design space may include all possible permutations of the parameters. For example, one design type may be configured with different doses of a drug and different frequency of the administration of the drug. The design space may include all possible permutations of the different doses of the drug for all the different frequencies of the administration of the drug”, 0293, experimental).
Claim 186: Bhattacharya discloses the method of claim 169, wherein the first computing device and the second computing device are the same, and wherein the first user and the second user are the same (0373 and 0707, “reports” and “reporting” as indications of the data and analysis being provided to the user via the computer).
Claim 187: Bhattacharya discloses the method of claim 169, wherein the plurality of treatment outcomes comprises a member selected from the group consisting of event-free survival time, progression-free survival time, overall survival time, another time to event, efficacy, safety, quality of life, an adverse event, a score, and a biomarker (0303, “A population model may include subject models that include various subject characteristics such as demography data, survival models (control and treatment), dropout rate (control and treatment), expected responses, and the like”, see also 0304 indicating survival models, 0313, “determining, for the outcome of the trial, the estimator of the trial design 3208, and scoring the design”).
Claim 188: Bhattacharya discloses the method of claim 169, wherein the set of simulated net treatment benefit scores comprises a member selected from the group consisting of event-free survival time, progression-free survival time, overall survival time, another time to event, efficacy, safety, quality of life, an adverse event, a score, a biomarker, a reaction, a side effect, and a toxicity of the clinical intervention (0303, “A population model may include subject models that include various subject characteristics such as demography data, survival models (control and treatment), dropout rate (control and treatment), expected responses, and the like”, see also 0304 indicating survival models, 0313, “determining, for the outcome of the trial, the estimator of the trial design 3208, and scoring the design”).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
What is a parameter or variable? From GCP-Service International, downloaded via the Archive.org WayBack Machine on 6 August 2026 at https://web.archive.org/web/20210724051607/https://www.gcp-service.com/what-is-a-parameter-or-variable/, dated 24 July 2021, indicating “a variable is something that can be measured – like the blood pressure for example. Let us assume as the main objective of our study, we are interested if the investigational product is decreasing the blood pressure over time. What we can do to answer our question easily, is to measure the blood pressure once in the beginning of the trial and then again, after the patient used the product, after three months. We can compare these values or variables directly. So, variables in general are quantities which vary between distinct individuals, in this case patients.” (at the first paragraph) and “Now that we know what a variable is, how does it differ from a parameter? Parameters are what biostatisticians use for the statistical analysis. They do not relate to actual measurements but to quantities defining a theoretical model. If we look at our example with the blood pressure, here we would calculate the change in blood pressure from the beginning to the end of our trial, for the two treatments. What we compare now between the two treatments are parameters. They cannot be measured directly and were computed from measured variables” (at the third paragraph). The Examiner notes the enclosed copy has the Archive.org header for the first page in order to capture the document date, where pages 2, 3, and 4 are page captures that include the text and graphics with an overlap of approximately a line in order to show continuity.
Altman et al., Statistics notes: variables and parameters. BMJ. 1999 Jun 19;318(7199):1667. doi: 10.1136/bmj.318.7199.1667. PMID: 10373171; PMCID: PMC1116021. Downloaded 6 August 2026 from https://pmc.ncbi.nlm.nih.gov/articles/PMC1116021/pdf/1667.pdf, indicating “Information recorded about a sample of individuals (often patients) comprises measurements such as blood pressure, age, or weight and attributes such as blood group, stage of disease, and diabetes. Values of these will vary among the subjects; in this context blood pressure, weight, blood group and so on are variables. Variables are quantities which vary from individual to individual. By contrast, parameters do not relate to actual measurements or attributes but to quantities defining a theoretical model. The figure shows the distribution of measurements of serum albumin in 481 white men aged over 20 with mean 46.14 and standard deviation 3.08 g/l. For the empirical data the mean and SD are called sample estimates. They are properties of the collection of individuals.”
National Cancer Institute, Endpoint definition, downloaded 7 August 2026 from https://www.cancer.gov/publications/dictionaries/cancer-terms/def/endpoint, indicating that “In clinical trials, an event or outcome that can be measured objectively to determine whether the intervention being studied is beneficial. The endpoints of a clinical trial are usually included in the study objectives. Some examples of endpoints are survival, improvements in quality of life, relief of symptoms, and disappearance of the tumor.”
FDA Facts: Biomarkers and Surrogate Endpoints, downloaded 7 August 2026 from https://www.fda.gov/about-fda/innovation-fda/fda-facts-biomarkers-and-surrogate-endpoints, dated 21 December 2017, indicating that “A clinical trial’s ‘endpoints’ are measurements of what happens to people in the trial. When a trial is intended to evaluate the efficacy and safety of a new medical product or a new use of an approved product, its endpoints usually measure benefit” (at p. 2).
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/SCOTT D GARTLAND/
Primary Examiner, Art Unit 3685
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