DETAILED ACTION
Notice to Applicant
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is in response to the amendment filed 2/27/26. 1-4, 9 ,11-12,16-22, 24, 26 and 28 have been canceled. Claims 29-48 are new and pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114 was filed in this application after a decision by the Patent Trial and Appeal Board, but before the filing of a Notice of Appeal to the Court of Appeals for the Federal Circuit or the commencement of a civil action. 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examination under 37 CFR 1.114 and the fee set forth in 37 CFR 1.17(e) has been timely paid, the appeal has been withdrawn pursuant to 37 CFR 1.114 and prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant’s submission filed on 2/27/26 has been entered.
Drawings
The replacement drawings were received on 2/27/26. These drawings are acceptable.
Claim Rejections - 35 USC § 112
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.
Claims 36 and 45 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 36 and 45 recite: “identifying.. one or more additional clinical trials for which the subject fails to satisfy fewer than a threshold number of inclusion criteria, and treating each such additional clinical trial as relevant to the subject, and included in the set of relevant clinical trials, when the subject fails to meet the inclusion criteria by less than the threshold number of inclusion criteria.”
It is unclear what applicant intends to claim with the current claim language, and what steps are being performed. More specifically, the phrase “fails to satisfy fewer than a threshold number of inclusion criteria” is unclear to the examiner. If a subject fails to satisfy fewer than a threshold number, do they satisfy more than a threshold number of inclusion criteria? (i.e. they would already qualify for consideration for a trial based on meeting more than the threshold number of inclusion criteria)
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 29-48 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e, a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
35 USC 101 enumerates four categories of subject matter that Congress deemed to be appropriate subject matter for a patent: processes, machines, manufactures and compositions of matter. As explained by the courts, these “four categories together describe the exclusive reach of patentable subject matter. If a claim covers material not found in any of the four statutory categories, that claim falls outside the plainly expressed scope of Section 101 even if the subject matter is otherwise new and useful.” In re Nuijten, 500 F.3d 1346, 1354, 84 USPQ2d 1495, 1500 (Fed. Cir. 2007). Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter? Applicant’s claims fall within at least one of the four categories of patent eligible subject matter because claims 38-46 are drawn to a system; claims 29-37 are drawn to a method; claims 47-48 are directed to an article of manufacture (CRM with instructions for performing a method).
Determining that a claim falls within one of the four enumerated categories of patentable subject matter recited in 35 USC 101 (i.e., process, machine, manufacture, or composition of matter) in Step 1 does not complete the eligibility analysis. Claims drawn only to an abstract idea, a natural phenomenon, and laws of nature are not eligible for patent protection. As described in MPEP 2106, subsection III, Step 2A of the Office’s eligibility analysis is the first part of the Alice/Mayo test, i.e., the Supreme Court’s “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts.” Alice Corp. Pty. Ltd. v. CLS Bank Int'l,134 S. Ct. 2347, 2355, 110 USPQ2d 1976, 1981 (2014) (citing Mayo, 566 U.S. at 77-78, 101 USPQ2d at 1967-68).
The United States Patent and Trademark Office (USPTO) has prepared revised guidance (2019 Revised Patent Subject Matter Eligibility Guidance) for use by USPTO personnel in evaluating subject matter eligibility. The 2019 Revised Patent Subject Matter Eligibility Guidance revises the procedures for determining whether a patent claim or patent application claim is directed to a judicial exception (laws of nature, natural phenomena, and abstract ideas) under Step 2A of the USPTO’s Subject Matter Eligibility Guidance in two ways. First, the 2019 Revised Patent Subject Matter Eligibility Guidance explains that abstract ideas can be grouped as, e.g., mathematical concepts, certain methods of organizing human activity, and mental processes. Second, this guidance explains that a patent claim or patent application claim that recites a judicial exception is not ‘‘directed to’’ the judicial exception if the judicial exception is integrated into a practical application of the judicial exception. A claim that recites a judicial exception, but is not integrated into a practical application, is directed to the judicial exception under Step 2A and must then be evaluated under Step 2B (inventive concept) to determine the subject matter eligibility of the claim.
Step 2A asks: Does the claim recite a law of nature, a natural phenomenon (product of nature) or an abstract idea? If so, is the judicial exception integrated into a practical application of the judicial exception? A claim recites a judicial exception when a law of nature, a natural phenomenon, or an abstract idea is set forth or described in the claim. While the terms “set forth” and “describe” are thus both equated with “recite”, their different language is intended to indicate that there are different ways in which an exception can be recited in a claim. For instance, the claims in Diehr set forth a mathematical equation in the repetitively calculating step, while the claims in Mayo set forth laws of nature in the wherein clause, meaning that the claims in those cases contained discrete claim language that was identifiable as a judicial exception. The claims in Alice Corp., however, described the concept of intermediated settlement without ever explicitly using the words “intermediated” or “settlement.” A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.
In the instant case, claims 29-48 recite(s) a method, product and system for certain methods of organizing human activities, which is subject matter that falls within the enumerated groupings of abstract ideas described in the 2019 Revised Patent Subject Matter Eligibility Guidance. Certain methods of organizing human activities includes fundamental economic practices, like insurance; commercial interactions (i.e. legal obligations, marketing or sales activities or behaviors, and business relations). Organizing human activity also encompasses managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions.) The recited method and system are drawn to evaluating and ranking clinical trials for treatment options. (i.e. managing personal behavior or relationships or interactions)
In particular, the claims recite a method, product and system (Claims 29, 38, and 47) to:
automatically establishing… a subject profile defining the subject according to a plurality of features, wherein establishing a subject profile comprises an automated process by the clinical decision support system to identify and extract clinical data about the subject from the clinical database;
automatically identifying… a set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and comprises a plurality of inclusion criteria that are satisfied by features of the plurality of features of the subject profile;
automatically assigning…a weighting score to each of the plurality of therapies corresponding to the identified set of clinical trials, wherein each weighting score is based on at least: (i) a satisfaction score indicating a degree of satisfaction of the inclusion criteria by the plurality of features of the subject profile; (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical benefit; and (iii) a supplemental effect score comprising a measure of one or more known negative side effects associated with the clinical trial, wherein the measure of a known negative side effect comprises one or more of a frequency and severity of the negative side effect;
automatically ranking… the therapies corresponding to the set of clinical trials;;
receiving…an adaptation of one or more of the plurality of inclusion criteria for the plurality of clinical trials, wherein the adaptation comprises relaxing an inclusion criterion that excludes the subject from eligibility for at least one of the plurality of clinical trials;
automatically re-identifying … based on the received adaptation, a revised set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and comprises a plurality of inclusion criteria that are satisfied by features of the plurality of features of the subject profile, and wherein the revised set of clinical trials comprises, due to relaxation of the inclusion criterion, one or more clinical trials that were not previously identified;
automatically assigning… a weighting score to at least the one or more clinical trials that were not previously identified;
automatically ranking, based on the assigned weighting scores, the therapies found within the revised set of clinical trials, wherein the ranking includes one or more therapies from the one or more clinical trials that were not previously identified
This judicial exception is not integrated into a practical application because the claim language does not recite any improvements to the functioning of a computer, or to any other technology or technical field (See MPEP 2106.04(d)(1); see also MPEP 2106.05(a)(I-II)). Moreover, the claims do not integrate the judicial exception into a practical application because the claimed invention does not: apply the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)); effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)); or apply or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment see MPEP 2106.05(e). (Considerations for integration into a practical application in Step 2A, prong two and for recitation of significantly more than the judicial exception in Step 2B)
While abstract ideas, natural phenomena, and laws of nature are not eligible for patenting by themselves, claims that integrate these exceptions into an inventive concept are thereby transformed into patent-eligible inventions. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2354, 110 USPQ2d 1976, 1981 (2014) (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 71-72, 101 USPQ2d 1961, 1966 (2012)). Thus, the second part of the Alice/Mayo test is often referred to as a search for an inventive concept. Id. An “inventive concept” is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself. Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination. See Mayo, 566 U.S. at 91, 101 USPQ2d at 1973 (rejecting “the Government’s invitation to substitute Sections 102, 103, and 112 inquiries for the better established inquiry under Section 101”). As made clear by the courts, the “‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the Section 101 categories of possibly patentable subject matter.” Intellectual Ventures I v. Symantec Corp.,838 F.3d 1307, 1315, 120 USPQ2d 1353, 1358 (Fed. Cir. 2016) (quoting Diamond v. Diehr, 450 U.S. at 188–89, 209 USPQ at 9).
As described in MPEP 2106, subsection III, Step 2B of the Office’s eligibility analysis is the second part of the Alice/Mayo test, i.e., the Supreme Court’s “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts.” Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. _, 134 S. Ct. 2347, 2355, 110 USPQ2d 1976, 1981 (2014) (citing Mayo, 566 U.S. 66, 101 USPQ2d 1961 (2012)). Step 2B asks: Does the claim recite additional elements that amount to significantly more than the judicial exception? The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The additional steps amount to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). Examples of insignificant extra-solution activity include mere data gathering, selecting a particular data source or type of data to be manipulated, and insignificant application.
In the instant case the additional step(s) of: automatically outputting the ranking of the therapies for the subject via a user interface of the clinical decision support system…; automatically outputting the ranking of the therapies for the subject…, wherein the output ranking further comprises, for each ranked therapy, at least one expected benefit of the therapy and at least one potential risk associated with the therapy (2nd time) as recited in claims 29, 38, and 47 amount to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering)
Exemplary claims 29, 38 and 47 also recite additional limitation(s), including: “a processor,“ “a clinical database,” “a clinical trials database comprising information about a plurality of clinical trials each comprising a plurality of inclusion criteria, a corresponding therapy, and outcome data,” and “a user interface.”
Moreover, the generic nature of the computer system used to carryout steps of the recited method is underscored by the system description in the instant application, which discloses: “The system 100 may comprise a computing device, such as desktop, laptop or tablet computer, a smartphone, a server, a network of computing devices, or any other apparatus or system having suitable processing functionality.” (see PG-pub- par. 32). ” The specification further explains: he processor 102, 604 can comprise one or more processors, processing units, multi-core processors or modules that are configured or programmed to control apparatus and/or the system 100 in the manner described herein. In particular implementations, the processor 102, 604 can comprise a plurality of software and/or hardware modules that are each configured to perform, or are for performing, individual or multiple steps of the method described herein. (par. 68)
Such language underscores that the applicant's perceived invention/ novelty focuses on the computerized implementation of the abstract idea, not the underlying structure of the additional (generic) components.
Because Applicant’s claimed invention recites a judicial exception that is not integrated into a practical application and does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself, the claimed invention is not patent eligible.
Claims 30-37 are dependent from Claim 29, include(s) all the limitations of clam 29. However, the additional limitations of the claims 30-37 fail to recite significantly more than the abstract idea. More specifically, the additional limitations further define the abstract idea with additional steps or details regarding data types; or the additional steps amount to insignificant extra solution activities. Therefore, claim(s) 30-37 are also rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claims 39-46 are dependent from Claim 38, include(s) all the limitations of claim 38. However, the additional limitations of the claims 39-46 fail to recite significantly more than the abstract idea. More specifically, the additional limitations further define the abstract idea with additional steps or details regarding data types; or the additional steps amount to insignificant extra solution activities. Therefore, claim(s) 39-46 are also rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim 48 is dependent from Claim 47, include(s) all the limitations of clam 47. However, the additional limitations of the claim 47 fails to recite significantly more than the abstract idea. More specifically, the additional limitations further define the abstract idea with additional steps or details regarding data types; or the additional steps amount to insignificant extra solution activities. Therefore, claim(s) 48 is also rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 29-36; 38-45; and 47-48 is/are rejected under 35 U.S.C. 103 as being unpatentable over by Petak et al (US 2016/0224760-hereinafter Petak) and further in view of Boissel (WO 2011/124385 A1), in further view of Dalton et al (US 20100076786 A1) and in further view of Katz (US 20080109455 A1)
Claims 29 and 48 Petak teaches a method for ranking a plurality of therapies for a subject suffering from cancer, and non-transitory computer-readable storage medium having computer instructions thereon that when executed by a processor of a clinical decision support system (par. 115; par. 116), cause the processor to perform a method comprising:
automatically establishing, by the clinical decision support system using a clinical database, a subject profile defining the subject according to a plurality of features; (par. 47-48 The system consists of registration modules for different users (healthy users, patients, par. 67-patient profiles)
automatically identifying, by the clinical decision support system using a clinical trials database comprising information about a plurality of clinical trials, a set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and comprises a plurality of inclusion criteria that are satisfied by features of the plurality of features of the subject profile; (par. 54. Users may access and search the trial calculator to identify available trials based on search criteria. Physicians may use the trial calculator to refer a patient to the identified trial, or a patient may use the trial calculator as a mechanism for requesting participation in the trial)
automatically assigning, by the clinical decision support system, a weighting score to each of the plurality of therapies corresponding to the identified set of clinical trials, wherein each weighting score is based on at least one of: (i) a satisfaction score indicating a degree of satisfaction of the inclusion criteria by the plurality of features of the subject profile; and (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical benefit (par. 8- it relates to assigning ranks to treatment options based on their expected efficacy and side effects and clinical experience.; par. 41- A “best” decision according the adaptive database can be defined as the treatment with the most clinical experience, highest evidence or least side effects,)
automatically ranking by the clinical decision support system based on the assigned weighting score (par. 235-238-weighting parameters) therapies corresponding to the set of clinical trials; (par. 58- group of people linked together in a network for treatment of human diseases, to assign preference rank to treatment option based on the similarity of the given patient's case to cases treated by the users…ranking is based on the efficacy of treatments on patients, which are most similar to the case. Similarity is based on the number of matching parameters. This way the first therapy is the most effective in patients, which are most similar to this case);
receiving, via the user interface of the clinical decision support system, an adaptation of one or more of the plurality of inclusion criteria for the plurality of clinical trials, wherein the adaptation comprises relaxing an inclusion criterion that excludes the subject from eligibility for at least one of the plurality of clinical trials; (par. 43-45 receive variable input; par. 189)
automatically re-identifying, by the clinical decision support system based on the received adaptation, a revised set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and comprises a plurality of inclusion criteria that are satisfied by features of the plurality of features of the subject profile, and wherein the revised set of clinical trials comprises, due to relaxation of the inclusion criterion, one or more clinical trials that were not previously identified; (par. 54-Users may access and search the trial calculator to identify available trials based on search criteria; par. 164-consideration of first line and second line clinical trials; par. 248-when a new clinical trial with matching inclusion and exclusion criteria is entered is entered by any user of the system; par. 265-altering criteria)
automatically assigning, by the clinical decision support system, a weighting score to at least the one or more clinical trials that were not previously identified; (par. 133-135; par. 190-Physicians who have patients in their database who could benefit from the novel therapies are alerted. For these patients the therapy ranking has to be repeated);
automatically ranking, by the clinical decision support system based on the assigned weighting scores, the therapies found within the revised set of clinical trials, wherein the ranking includes one or more therapies from the one or more clinical trials that were not previously identified; and (par. 133-135; par. 190-Physicians who have patients in their database who could benefit from the novel therapies are alerted. For these patients the therapy ranking has to be repeated);
Claims 29 and 47 further recites: automatically outputting the ranking of the therapies for the subject wherein the output further comprises, for each ranked therapy, at least one expected benefit of the therapy and at least one potential risk associated with the therapy.
Petak discloses providing ranked therapies (Par. 130-133: third step is to rank therapies with the system based on the clinical experience with same molecular profile and molecular evidence, as exemplified in Table 1…the ranking of the therapies are both based by the clinical experience of the same group of patients (same molecular profile, same drivers genes, same tumor type) and evidence (published and system generated evidence calculators supporting the most likely driver, target and drug) for each ranked therapy, at least one expected benefit of the therapy. wherein the therapies include immunotherapies for cancer (par. 109: The ranking of the immunotherapies is based on the clinical experience of patients with the same Human Leukocyte Antigen (HLA) and antigen expression profile; fig. 6; Table 1; Fig. 7- ranking treatment by response/expected benefit Table 1).
Petak does not expressly disclose automatically outputting via user interface wherein the output further comprises, for each ranked therapy, at least one potential risk associated with the therapy. Boissel discloses outputting via user interface wherein the output further comprises, for each ranked therapy, at least one potential risk associated with the therapy. (pg. 5, par. 3, par. 7:outputting an indicator of the benefit from treatment comprises displaying whether said treatment is suitable for said patient. Optionally, said outputting comprises displaying one, e.g. from a plurality of treatments, or a plurality of treatments that are suitable for said patient, optionally ranked according to their predicted benefit for the patient. Optionally, said outputting may further comprise displaying in graphical form the benefit predicted for a population of individuals (e.g. a virtual realistic population) from said treatment, and indicating how the benefit for said patient compares with the benefit for said population) At the time of filing, it would have been obvious to one of ordinary skill in the art to modify the system and method of Petak with the teaching of Boisel to output information regarding treatment benefit and risks with the motivation of providing improved systems and information for predicting treatment outcomes in new patients or in new populations as well as for drug candidates before in vivo administration. (pg. 1, par. 4)
Claims 29 and 47 further recite: establish, by automatically identifying and extracting clinical data from a clinical database, a subject profile defining a subject suffering from cancer and comprising a plurality of features.
Petak discloses establishing a user/subject profile (par.12- the medical experience register storing medical experience data from a plurality of users, wherein the data from each user is encoded and includes anonymous, patient-specific physical, biological and clinical data and; a clinical evidence register, the clinical evidence register storing result data from at least a subset of the plurality of users, the result data including anonymous molecular and clinical profiles of respective prior patient) but Petak does not expressly disclose automatically identifying and extracting clinical data from a clinical database, to establish a subject profile defining a subject suffering from cancer and comprising a plurality of features.
Dalton discloses automatically identifying and extracting clinical data from a clinical database, to establish a subject profile defining a subject suffering from cancer and comprising a plurality of features. (abstract; par. 32- The datamart 102 can be created by combining patient data from the variety of sources that have patient data, because there are generally multiple sources of patient data for each patient. This combination can be performed using a centralized repository 104 that includes a staging system 106, which periodically copies, cleanses, aggregates and transforms data from information sources 26 into the staging system 106.; Fig. 7; Par. 51- extracting relevant information from a medical record for a patient; storing the relevant information in a patient profile separate from the medical record and accessible by a user of a networked device; augmenting the patient profile including generating patient centric information, the patient centric information including information that is not part of the medical record) At the time of filing, it would have been obvious to one of ordinary skill in the art to further modify the system/method of Petak and Boissell in combination with the teaching of Dalton to include extracting and identifying clinical data to establish a patient profile with the motivation of providing a comprehensive personalized patient profile to facilitate matching to patient-centric options for care, clinical trials for which the patient is eligible, drug treatment regimens directly related to each patient's specific condition. (Dalton: abstact.)
Claims 29 and 47 further recite: wherein each weighting score is based on at least and (iii) a supplemental effect score comprising a measure of one or more known negative side effects associated with the clinical trial, wherein the measure of a known negative side effect comprises one or more of a frequency and severity of the negative side effect
Petak discloses a system/method wherein each weighting score is based on at least one of: (i) a satisfaction score indicating a degree of satisfaction of the inclusion criteria by the plurality of features of the subject profile; and (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical benefit. (par. 8- it relates to assigning ranks to treatment options based on their expected efficacy and side effects and clinical experience.; par. 41- A “best” decision according the adaptive database can be defined as the treatment with the most clinical experience, highest evidence or least side effects).
Petak does not disclose, but Katz teaches a method and system for assessing treatments and clinical trials, wherein each weighting score (par. 44-45; par. 128; fig. 6; par. 132) is based on at least (i) a satisfaction score indicating a degree of satisfaction of the inclusion criteria by the plurality of features of the subject profile (Fig. 2; par. 48-49: individual suitability scores).; (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical and (par. 117-123: consideration of efficacy: demonstrating that the experimental drug is useful in treating MDD in pediatric and adolescent subjects, and that there are no unacceptable safety risks. The efficacy measure is made by using a standardized assessment tool that is used to measure depression before, during, and after treatment. The safety determination is made using a standard battery of tests that are performed before, during and after treatment.) (iii) a supplemental effect score comprising a measure of one or more known negative side effects associated with the clinical trial, wherein the measure of a known negative side effect comprises one or more of a frequency and severity of the negative side effect (par. 121-122-safety assessment and adverse events tracking: Safety will be assessed by 1) adverse event monitoring, 2) vital signs, 3) laboratory evaluations, 4) serum pregnancy tests, 5) ECGs, and 6) physical examinations. Measurements will be made at baseline and four and eight weeks after randomization to therapy; par. 128 inclusion/exclusion criteria comprise about 100 points of the 275 point overall ideal subject suitability score. Safety criteria contribute 75 points to the ideal subject suitability score, while efficacy criteria contribute 100 points)
At the time of filing, it would have been obvious to one of ordinary skill in the rat to modify the system/ method of Petak , Boissel, and Dalton in combination with the teaching of Katz to consider all three of (i) a satisfaction score; (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical and (iii) a supplemental effect score comprising a measure of one or more known negative side effects associated with the clinical trial in evaluating and ranking clinical trial therapies. As suggested by Katz, one would have been motivated to include this feature to facilitate the improvement of data quality generated during drug and medical device clinical trials, and to ensure the safety of the human subjects (Katz: par. 7)
claim 30 Petak teaches the method of claim 29, further comprising ranking the identified set of clinical trials, and the identified revised set of clinical trials, based on clinical benefits achieved by each clinical trial. (Table par. 133-134: based upon clinical benefits or response rate)
Claim 31. Petak teaches a clinical decision support system and method, wherein the clinical benefits achieved by a clinical trial are defined by one or more of: i) a measure of the progression-free survival of participants in the clinical trial; ii) a measure of the overall survival of participants in the clinical trial; and iii) a measure of the response rate of participants in the clinical trial. (Table 1; par. 133- the drugs (rows) can be re-ranked by any of the columns, to rank first the drugs with the best response rate (PR, partial response and CR, complete response) or diseased control (SD, stable disease included), PFS (progression free survival) etc. in any of the categories (same molecular alteration, target tumor type etc.) or by the highest evidence)
Claim 32. Petak teaches a clinical decision support system/ method further comprising ranking the identified set of clinical trials, and the identified revised set of clinical trials, based on at least one of: (i) a similarity of features of the subject to corresponding features of participants of the clinical trials; and (ii) a level of information available regarding the clinical trials..(par. 131-the ranking of the therapies are both based by the clinical experience of the same group of patients (same molecular profile, same drivers genes, same tumor type) and evidence (published and system generated evidence calculators supporting the most likely driver, target and drug; see also 132-134 for other ranking parameters)
Claims 33 and 48. Petak teaches a clinical decision support system and method, further comprising grouping the ranked therapies into two or more groups, the grouping based on one or more of: (i) biological similarities between the ranked therapies; and (ii) similarities between features of the subject profile and features of profiles of participants in the set of clinical trials. (Abstract; par. 235-236- similarity is a component of grouping patients, therapies and rankings)
Claim 34 Petak does not expressly disclose, but Boissel teaches a method , wherein automatically outputting the ranking of the therapies for the subject comprises outputting the two or more groups. (pg. 3, par. 6: generally to output or display multiple
treatments (e.g. as treatment options; for use in comparison). Such methods that integrate multiple treatments are particularly useful for physicians or personnel involved in drug discovery, drug development and healthcare economics.)
At the time of filing, it would have been obvious to one of ordinary skill in the art to modify the system and method of Petak with the teaching of Boisel to output information regarding treatment benefit and risks with the motivation of providing improved systems and information for predicting treatment outcomes in new patients or in new populations as well as for drug candidates before in vivo administration. (pg. 1, par. 4)
Claim 35 Petak teaches a method wherein a clinical trial is relevant to the subject if a threshold number of inclusion criteria are satisfied by features of the subject profile. (Fig. 7-shows rankings by distinguishing between partial and perfect matches (i.e. a threshold or relevant features))
Claim 36 Petak teaches a method wherein automatically identifying the set of relevant clinical trials comprises identifying, by the clinical decision support system, one or more additional clinical trials for which the subject fails to satisfy fewer than a threshold number of inclusion criteria, and treating each such additional clinical trial as relevant to the subject, and included in the set of relevant clinical trials, when the subject fails to meet the inclusion criteria by less than the threshold number of inclusion criteria. ( See rejection under 35 USC 112(b); adapting criteria: par. 43-45 receive variable input; par. 189; identifying trials based on adaptation: par. 54-Users may access and search the trial calculator to identify available trials based on search criteria; par. 164-consideration of first line and second line clinical trials; par. 248-when a new clinical trial with matching inclusion and exclusion criteria is entered is entered by any user of the system; par. 265-altering criteria)
Claim 38 Petak teaches a clinical decision support system comprising:
a clinical database comprising clinical data about a subject suffering from cancer (par. 47: genetic and environmental factors are linked to cancer risk since these factors in the users' medical history are automatically linked to cancer (and type and molecular profile of cancer) and the age of the users when (if) cancer is diagnosed in the users;; par. 48-If a user is diagnosed with a disease—e.g. cancer—the user becomes a patient user. Any new patient user can also register; par. 68; par. 127 getting data from EHR systems)
a clinical trials database comprising information about a plurality of clinical trials each comprising a plurality of inclusion criteria, a corresponding therapy, and outcome data (par. 53-receiving clinical outcome data; par. 67-outcome data used in ranking: Physician 3's use of the system necessarily results in Patient C's outcome/response to be input to the system to adapt the rankings of the treatments of the same molecular and clinical profile with drug “b”; (par. 54. Users may access and search the trial calculator to identify available trials based on search criteria. Physicians may use the trial calculator to refer a patient to the identified trial, or a patient may use the trial calculator as a mechanism for requesting participation in the trial)
a user interface- (par. 114-users can access the system on their own personal computer, tablet or portable communication devices (smartphones) or other comparable interfaces. These devices provide the communication interface to provide input and receive output)
a processor (par. 12-13) configured to:
establish a subject profile for defining a subject suffering from cancer
according to a plurality of features (par. 47-48 The system consists of registration modules for different users (healthy users, patients, par. 67-patient profiles)
identify a set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and has inclusion criteria that are satisfied by features of the plurality of features of the subject profile; (par. 54. Users may access and search the trial calculator to identify available trials based on search criteria. Physicians may use the trial calculator to refer a patient to the identified trial, or a patient may use the trial calculator as a mechanism for requesting participation in the trial)
assign a weighting score to each of the plurality of therapies corresponding to the identified set of clinical trials, (par. 8- it relates to assigning ranks to treatment options based on their expected efficacy and side effects and clinical experience.; par. 41- A “best” decision according the adaptive database can be defined as the treatment with the most clinical experience, highest evidence or least side effects,)
rank by the clinical support system the therapies based on a weighting score (par. 235-238-weighting parameters) corresponding to the set of clinical trials; and (par. 58- group of people linked together in a network for treatment of human diseases, to assign preference rank to treatment option based on the similarity of the given patient's case to cases treated by the users…ranking is based on the efficacy of treatments on patients, which are most similar to the case. Similarity is based on the number of matching parameters. This way the first therapy is the most effective in patients, which are most similar to this case )
receiving, via the user interface of the clinical decision support system, an adaptation of one or more of the plurality of inclusion criteria for the plurality of clinical trials, wherein the adaptation comprises relaxing an inclusion criterion that excludes the subject from eligibility for at least one of the plurality of clinical trials; (par. 43-45 receive variable input; par. 189)
automatically re-identifying, by the clinical decision support system based on the received adaptation, a revised set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and comprises a plurality of inclusion criteria that are satisfied by features of the plurality of features of the subject profile, and wherein the revised set of clinical trials comprises, due to relaxation of the inclusion criterion, one or more clinical trials that were not previously identified; (par. 54-Users may access and search the trial calculator to identify available trials based on search criteria; par. 164-consideration of first line and second line clinical trials; par. 248-when a new clinical trial with matching inclusion and exclusion criteria is entered is entered by any user of the system; par. 265-altering criteria)
automatically assigning, by the clinical decision support system, a weighting score to at least the one or more clinical trials that were not previously identified; (par. 133-135; par. 190-Physicians who have patients in their database who could benefit from the novel therapies are alerted. For these patients the therapy ranking has to be repeated);
automatically ranking, by the clinical decision support system based on the assigned weighting scores, the therapies found within the revised set of clinical trials, wherein the ranking includes one or more therapies from the one or more clinical trials that were not previously identified; and (par. 133-135; par. 190-Physicians who have patients in their database who could benefit from the novel therapies are alerted. For these patients the therapy ranking has to be repeated);
receiving, via the user interface of the clinical decision support system, an adaptation of one or more of the plurality of inclusion criteria for the plurality of clinical trials, wherein the adaptation comprises relaxing an inclusion criterion that excludes the subject from eligibility for at least one of the plurality of clinical trials; (par. 43-45 receive variable input; par. 189)
automatically re-identifying, by the clinical decision support system based on the received adaptation, a revised set of clinical trials that are relevant to the subject, wherein each clinical trial in the set of relevant clinical trials corresponds to at least one therapy and comprises a plurality of inclusion criteria that are satisfied by features of the plurality of features of the subject profile, and wherein the revised set of clinical trials comprises, due to relaxation of the inclusion criterion, one or more clinical trials that were not previously identified; (par. 54-Users may access and search the trial calculator to identify available trials based on search criteria; par. 164-consideration of first line and second line clinical trials; par. 248-when a new clinical trial with matching inclusion and exclusion criteria is entered is entered by any user of the system; par. 265-altering criteria)
automatically assigning, by the clinical decision support system, a weighting score to at least the one or more clinical trials that were not previously identified; (par. 133-135; par. 190-Physicians who have patients in their database who could benefit from the novel therapies are alerted. For these patients the therapy ranking has to be repeated);
automatically ranking, by the clinical decision support system based on the assigned weighting scores, the therapies found within the revised set of clinical trials, wherein the ranking includes one or more therapies from the one or more clinical trials that were not previously identified; and (par. 133-135; par. 190-Physicians who have patients in their database who could benefit from the novel therapies are alerted. For these patients the therapy ranking has to be repeated);
Claim 38 further recites: output, via the user interface, the ranking of the therapies for the subject wherein the output further comprises, for each ranked therapy, at least one expected benefit of the therapy and at least one potential risk associated with the therapy; wherein the therapies include immunotherapies for cancer.
Petak discloses providing ranked therapies (Par. 130-133: third step is to rank therapies with the system based on the clinical experience with same molecular profile and molecular evidence, as exemplified in Table 1…the ranking of the therapies are both based by the clinical experience of the same group of patients (same molecular profile, same drivers genes, same tumor type) and evidence (published and system generated evidence calculators supporting the most likely driver, target and drug) for each ranked therapy, at least one expected benefit of the therapy. wherein the therapies include immunotherapies for cancer (par. 109: The ranking of the immunotherapies is based on the clinical experience of patients with the same Human Leukocyte Antigen (HLA) and antigen expression profile; fig. 6; Table 1; Fig. 7- ranking treatment by response/expected benefit Table 1).
Petak does not expressly disclose outputting via user interface wherein the output further comprises, for each ranked therapy, at least one potential risk associated with the therapy. Boissel discloses outputting via user interface wherein the output further comprises, for each ranked therapy, at least one potential risk associated with the therapy. (pg. 5, par. 3, par. 7: outputting an indicator of the benefit from treatment comprises displaying whether said treatment is suitable for said patient. Optionally, said outputting comprises displaying one, e.g. from a plurality of treatments, or a plurality of treatments that are suitable for said patient, optionally ranked according to their predicted benefit for the patient. Optionally, said outputting may further comprise displaying in graphical form the benefit predicted for a population of individuals (e.g. a virtual realistic population) from said treatment, and indicating how the benefit for said patient compares with the benefit for said population) At the time of filing, it would have been obvious to one of ordinary skill in the art to modify the system and method of Petak with the teaching of Boisel to output information regarding treatment benefit and risks with the motivation of providing improved systems and information for predicting treatment outcomes in new patients or in new populations as well as for drug candidates before in vivo administration. (pg. 1, par. 4)
Claim 38 further recites: establish, by automatically identifying and extracting clinical data from a clinical database, a subject profile defining a subject suffering from cancer and comprising a plurality of features.
Petak discloses establishing a user/subject profile (par.12- the medical experience register storing medical experience data from a plurality of users, wherein the data from each user is encoded and includes anonymous, patient-specific physical, biological and clinical data and; a clinical evidence register, the clinical evidence register storing result data from at least a subset of the plurality of users, the result data including anonymous molecular and clinical profiles of respective prior patient) but Petak does not expressly disclose automatically identifying and extracting clinical data from a clinical database, to establish a subject profile defining a subject suffering from cancer and comprising a plurality of features.
Dalton discloses automatically identifying and extracting clinical data from a clinical database, to establish a subject profile defining a subject suffering from cancer and comprising a plurality of features. (abstract; par. 32- The datamart 102 can be created by combining patient data from the variety of sources that have patient data, because there are generally multiple sources of patient data for each patient. This combination can be performed using a centralized repository 104 that includes a staging system 106, which periodically copies, cleanses, aggregates and transforms data from information sources 26 into the staging system 106.; Fig. 7; Par. 51- extracting relevant information from a medical record for a patient; storing the relevant information in a patient profile separate from the medical record and accessible by a user of a networked device; augmenting the patient profile including generating patient centric information, the patient centric information including information that is not part of the medical record) At the time of filing, it would have been obvious to one of ordinary skill in the art to further modify the system/method of Petak and Boissel in combination with the teaching of Dalton to include extracting and identifying clinical data to establish a patient profile with the motivation of providing a comprehensive personalized patient profile to facilitate matching to patient-centric options for care, clinical trials for which the patient is eligible, drug treatment regimens directly related to each patient's specific condition. (Dalton: abstract.)
Claim 38 further recites: wherein each weighting score is based on at least
Petak discloses a system/method wherein each weighting score is based on at least one of: (i) a satisfaction score indicating a degree of satisfaction of the inclusion criteria by the plurality of features of the subject profile; and (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical benefit. (par. 8- it relates to assigning ranks to treatment options based on their expected efficacy and side effects and clinical experience.; par. 41- A “best” decision according the adaptive database can be defined as the treatment with the most clinical experience, highest evidence or least side effects).
Petak does not disclose, but Katz teaches a method and system for assessing treatments and clinical trials, wherein each weighting score (par. 44-45; par. 128; fig. 6; par. 132) is based on at least (i) a satisfaction score indicating a degree of satisfaction of the inclusion criteria by the plurality of features of the subject profile (Fig. 2; par. 48-49: individual suitability scores).; (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical and (par. 117-123: consideration of efficacy: demonstrating that the experimental drug is useful in treating MDD in pediatric and adolescent subjects, and that there are no unacceptable safety risks. The efficacy measure is made by using a standardized assessment tool that is used to measure depression before, during, and after treatment. The safety determination is made using a standard battery of tests that are performed before, during and after treatment.) (iii) a supplemental effect score comprising a measure of one or more known negative side effects associated with the clinical trial, wherein the measure of a known negative side effect comprises one or more of a frequency and severity of the negative side effect (par. 121-122-safety assessment and adverse events tracking: Safety will be assessed by 1) adverse event monitoring, 2) vital signs, 3) laboratory evaluations, 4) serum pregnancy tests, 5) ECGs, and 6) physical examinations. Measurements will be made at baseline and four and eight weeks after randomization to therapy; par. 128 inclusion/exclusion criteria comprise about 100 points of the 275 point overall ideal subject suitability score. Safety criteria contribute 75 points to the ideal subject suitability score, while efficacy criteria contribute 100 points)
At the time of filing, it would have been obvious to one of ordinary skill in the rat to modify the system/ method of Petak , Boissel, and Dalton in combination with the teaching of Katz to consider all three of (i) a satisfaction score; (ii) an outcome score indicating an extent to which the clinical trial achieved a clinical and (iii) a supplemental effect score comprising a measure of one or more known negative side effects associated with the clinical trial in evaluating and ranking clinical trial therapies. As suggested by Katz, one would have been motivated to include this feature to facilitate the improvement of data quality generated during drug and medical device clinical trials, and to ensure the safety of the human subjects (Katz: par. 7)
claim 39 Petak teaches a clinical decision support system according to claim 38, wherein the processor is further configured to rank the identified set of clinical trials, and the identified revised set of clinical trials, based on clinical benefits achieved by each clinical trial. (Table par. 133-134: based upon clinical benefits or response rate)
Claim 40. Petak teaches a clinical decision support system and method, wherein the clinical benefits achieved by a clinical trial are defined by one or more of: (i) a measure of the progression-free survival of participants in the clinical trial; (ii) a measure of the overall survival of participants in the clinical trial; and (iii) a measure of the response rate of participants in the clinical trial. (Table 1; par. 133- the drugs (rows) can be re-ranked by any of the columns, to rank first the drugs with the best response rate (PR, partial response and CR, complete response) or diseased control (SD, stable disease included), PFS (progression free survival) etc. in any of the categories (same molecular alteration, target tumor type etc.) or by the highest evidence)
Claim 41. Petak teaches a clinical decision support system/ method, further wherein the processor is further configured to rank the identified set of clinical trials, and the identified revised set of clinical trials, based on at least one of: (i) a similarity of features of the subject to corresponding features of participants of the clinical trials; and (ii) a level of information available regarding the clinical trials.(par. 131-the ranking of the therapies are both based by the clinical experience of the same group of patients (same molecular profile, same drivers genes, same tumor type) and evidence (published and system generated evidence calculators supporting the most likely driver, target and drug; see also 132-134 for other ranking parameters)
Claim 42 Petak teaches the system of claim 38, wherein the processor is further configured to group the ranked therapies into two or more groups, the grouping based on one or more of: (i) biological similarities between the ranked therapies; and (ii) similarities between features of the subject profile and features of profiles of participants in the set of clinical trials. (Abstract; par. 235-236- similarity is a component of grouping patients, therapies and rankings)
Claim 43 Petak does not expressly disclose, but Boissel teaches a system, wherein automatically outputting the ranking of the therapies for the subject comprises outputting the two or more groups. (pg. 3, par. 6: generally to output or display multiple
treatments (e.g. as treatment options; for use in comparison). Such methods that integrate multiple treatments are particularly useful for physicians or personnel involved in drug discovery, drug development and healthcare economics.)
At the time of filing, it would have been obvious to one of ordinary skill in the art to modify the system and method of Petak with the teaching of Boisel to output information regarding treatment benefit and risks with the motivation of providing improved systems and information for predicting treatment outcomes in new patients or in new populations as well as for drug candidates before in vivo administration. (pg. 1, par. 4)
Claim 44 Petak teaches a system, wherein a clinical trial is relevant to the subject if a threshold number of inclusion criteria are satisfied by features of the subject profile. (Fig. 7-shows rankings by distinguishing between partial and perfect matches (i.e. a threshold or relevant features))
Claim 45 Petak discloses a system, wherein automatically identifying the set of relevant clinical trials comprises identifying one or more additional clinical trials for which the subject fails to satisfy fewer than a threshold number of inclusion criteria, and treating each such additional clinical trial as relevant to the subject, and included in the set of relevant clinical trials, when the subject fails to meet the inclusion criteria by less than the threshold number of inclusion criteria. ( See rejection under 35 USC 112(b); adapting criteria: par. 43-45 receive variable input; par. 189; identifying trials based on adaptation: par. 54-Users may access and search the trial calculator to identify available trials based on search criteria; par. 164-consideration of first line and second line clinical trials; par. 248-when a new clinical trial with matching inclusion and exclusion criteria is entered is entered by any user of the system; par. 265-altering criteria)
Claim(s) 37 and 46 is/are rejected under 35 U.S.C. 103 as being unpatentable over by Petak et al (US 2016/0224760-hereinafter Petak), Boissel (WO 2011/124385 A1), Dalton et al (US 20100076786 A1) and Katz (US 20080109455 A1) as applied to claims 29 and 38, and in further view of Holohan (US 20170242979 A1).
Claims 37 and 46 Petak does not disclose, but Holohan teaches screening for and eliminating subjects who may have treatment allergies based on information obtained about them (par. 103; par. 110) At the time of the effective filing date, it would have been obvious to one of ordinary skill in the art to modify the system and method of Petak, Boissel, Dalton and Katz in combination with the teaching of Holohan to include identifying that the subject is allergic to a therapy; and wherein automatically identifying the set of clinical trials comprises eliminating from the set of clinical trials any of the plurality of clinical trials that comprise the therapy to which the subject is allergic. One would have been motivated to include this feature to protect patient/subject safety, and reduce potential sponsor liability.
Response to Arguments
Applicant's arguments filed 2/27/26 have been fully considered but they are not persuasive.
(A) Applicant argues the drawing rejections of Figs. 1-6.
In response, the applicant’s arguments are not persuasive. The drawing objections have been maintained.
(B) Applicant argues that the claims are patent eligible, because the claims are not drawn to “certain methods of organizing human activity…”
In response, the examiner disagrees. Moreover, while the previous claims have been canceled, and new claim have been, the claimed subject matter is substantially the same as that previously presented in the appealed claim set.
The applicant’s arguments regarding the claim rejection under 35 USC 101 are unpersuasive, and the matter has been decided in the PTAB decision mailed on 12/31/2025.
The additional limitations are noted, and have been addressed in the current claim rejections. However, insofar as the additional claim limitations recite an iteration of the previously claimed steps recited in claims 1-4, 9, 11-12, 16-22, 24, 26, and 28, the claims are not deemed patent eligible, for the reasons set forth in the Examiner’s Answer mailed on 1/23/2025, and in the PTAB decision affirming these rejections, mailed on 12/31/25.
(C) Applicant argues that the newly added claims are not taught by the prior art.
In response, the examiner disagrees. Moreover, while the previous claims have been canceled, and new claim have been, the claimed subject matter is substantially the same as that previously presented in the appealed claim set.
The applicant’s arguments regarding the claim rejection under 35 USC 103 are unpersuasive, and the matter has been decided in the PTAB decision mailed on 12/31/2025.
The new claims are noted, and have been addressed in the current claim prior art rejections. However, insofar as the additional claim limitations recite an iteration of the previously claimed steps in claims 1-4, 9, 11-12, 16-22, 24, 26, and 28, the claims are not allowable/patentable over the prior art, for the reasons set forth in the Examiner’s Answer mailed on 1/23/2025, and in the PTAB decision affirming these rejections, mailed on 12/31/25.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Püntmann et al (Püntmann I, Schmacke N, Melander A, Lindberg G, Mühlbauer B. “EVITA: a tool for the early evaluation of pharmaceutical innovations with regard to therapeutic advantage.” BMC Clin Pharmacol. 2010 Mar 16;10:5, 11 pages; doi: 10.1186/1472-6904-10-5. PMID: 20233429)-discloses a system which does not evaluate a new compound per se but in an approved indication in comparison with existing therapeutic strategies.
Dranitsaris et al (US 20100204920 A1) discloses the development of an individualised treatment regimen for a patient based on an evaluation of the risk(s) associated with a disease and/or associated with known treatment options. In order to evaluate these risk(s), the system utilises clinical data from a plurality of patients having the disease in question. The clinical data includes information for each of the plurality of patients relating to the presence, absence and/or severity of one or more negative events.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rachel L Porter whose telephone number is (571)272-6775. The examiner can normally be reached on M-F, 10-6:30.
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RACHEL L. PORTER
Primary Examiner
Art Unit 3684
/Rachel L. Porter/Primary Examiner, Art Unit 3626