DETAILED ACTION
This action is made in response the remarks filed on May 7, 2026. This action is made final.
Claims 1-22 are pending. No claims have been amended. Claims 1, 11-14 and 16-18 are independent claims.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed May 7, 2026 have been fully considered but they are not persuasive.
As to the 101 rejection, Applicant argues the claims are not directed to a method of organizing human activity. However, the Examiner respectfully disagrees.
MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The Examiner submits that the identified claim elements represent a series of rules or instructions that a person or persons, with or without the aid of a computer, would follow to assessing a patient’s risk in a drug regimen. The Examiner notes that Applicant’s Background describes the assessing of drug characteristics and drug interaction as a human task (see Spec. [0003]). Furthermore, the Examiner submits that healthcare itself is inherently represents the organization of human activity. Applicant has not pointed to anything in the claims that fall outside of this characterization. Applicant’s arguments with respect to an improvement is further addressed below. Because the claim elements fall under a series of rules or instructions that a person or persons would follow to assess a patient’s risk of a drug regimen, the claimed invention is directed to an abstract idea.
Applicant further argues the claims are integrated into a practical application by improving the field of pharmacological management of patients. However, the examiner respectfully disagrees.
MPEP 2106.04(d)(1) states “the word ‘improvements’ in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B.” Here, there is no improvement to the computer, as the claims are confined to a general-purpose computer and no improvement of the functioning of the computer itself results from the implementation of Applicant’s claim. At best, the claims merely implement the abstract idea using a computer as a tool. Furthermore, there is not an improvement to another technology. The field of pharmacological management of patients is not reasonably understood to be a problem arising in the technology, but rather a problem in patient healthcare, specifically related to their medications. At best, the claimed invention is using a computer as a tool and any purported improvement is an improvement of the abstract idea. Because neither type of improvement is present in the claims, an improvement to technology is not present and there is no practical application.
Applicant further argues the previous cited references fail to teach “calculating an aggregated risk factor score representative of each of two or more risk factors associated with a patient’s drug regimen, wherein the two or more risk factors are selected from the group comprising: 1) number of active ingredients in the drug regimen, 2) anticholinergic burden of the active ingredients in the drug regimen,
3) sedative burden of the active ingredients in the drug regimen,
4) QT-interval prolongation risk of the active ingredients in the drug regimen,
5) competitive inhibition of the active ingredients in the drug regimen, wherein competitive inhibition includes any pharmacokinetic interaction including: interactions between active ingredient inhibitors and active ingredient substrates, interactions between active ingredient inducers and active ingredient substrates, and interactions between active ingredient substrates of the same isoenzyme with different affinities, and
6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient's genetic variations”. However, the examiner respectfully disagrees.
Notably, the claims are silent as to how the risk scores are calculated outside of being representative of two or more of the risk factors from the group. Accordingly, where the prior art teaches calculating an aggregated risk factor taking into consideration two or more risks related to the active ingredients, anticholinergic adverse effects, sedative adverse effects, QT interval prolongation, competitive inhibition, or interaction based on patient’s genetic variations, then it meets the claimed limitation.
Von Schweber teaches a method and apparatus for the evaluation, presentation, and modification of healthcare regimens wherein various compound factors are evaluated and one or more adverse effects are determined based on the compound conditional probabilities (e.g. see Abstract). Von Schweber further teaches the assessment of the regimen can be performed at any level of composition and provides various examples including, but not limited to pair-wise drug interactions, tachycardia risks, risks of drowsiness, regimens as it relates to genetic and genomic data, risk of heart palpitations, etc. (e.g., see [0009], [0010], [0032], [0036]-[0096], [0103]). As such, Von Scheweber teaches the various risk factors of the claimed limitation.
Applicant’s argument that the examiner has failed to provide the particular types of risk factors any patentable weight is not persuasive as the examiner has cited relevant art teaching the one or more claimed risk factors.
As such, the previous grounds of rejection are maintained.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-22 recite methods of assessing a risk of a drug regimen, which is within the statutory category of a process.
Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. ___ (2014). Claims 1-22, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
MPEP 2106 Step 2A – Prong 1:
The bolded limitations of:
Claims 1 and 11-13 (claim 1 being representative)
calculating an aggregated risk factor score representative of each of two or more risk factors associated with a patient's drug regimen, wherein the two or more risk factors are selected from the group comprising: 1) number of active ingredients in the drug regimen, 2) anticholinergic burden of the active ingredients in the drug regimen, 3) sedative burden of the active ingredients in the drug regimen, 4) QT-interval prolongation risk of the active ingredients in the drug regimen, and 5) competitive inhibition of the active ingredients in the drug regimen, wherein competitive inhibition includes any pharmacokinetic interaction including: interactions between active ingredient inhibitors and active ingredient substrates, interactions between active ingredient inducers and active ingredient substrates, and interactions between active ingredient substrates of the same isoenzyme with different affinities, and 6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient's genetic variations; and combining the aggregated risk factor scores calculated for each of said two or more risk factors to provide a quantitative personalized medication risk score that is representative of the patient's risk for an adverse drug event
Claim 14
determining a patient’s risk of an adverse drug event based at least on the patient’s drug regimen, comprising: a database containing two or more of the following data sets related to the patient's risk factors: (1) number of active ingredients in the drug regimen, (2) anticholinergic burden of the active ingredients in the drug regimen, (3) sedative burden of the active ingredients in the drug regimen, (4) QT-interval prolongation risk of the active ingredients in the drug regimen, and (5) competitive inhibition of the active ingredients in the drug regimen, and (6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient's genetic variations; and a calculating module, which applies algorithms to said two or more data sets and calculates a quantitative personalized medication risk score that is representative of the patient's risk for an adverse drug event.
Claims 16-18 (claim 16 being representative)
A method of reducing a risk of an adverse drug event in a patient, wherein the patient has been prescribed a drug regimen that includes at least a first drug and a second drug, the method comprising: calculating a quantitative personalized medication risk score that is representative
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of the patient's risk for an adverse drug event by combining aggregated risk factor scores representative of each of two or more risk factors associated with the patient's drug regimen, wherein the two or more risk factors are selected from the group consisting of:
1) number of active ingredients in the drug regimen, 2) anticholinergic burden of the drug regimen, 3) sedative burden of the drug regimen, 4) QT-interval prolongation risk of the drug regimen, and 5) competitive inhibition of the drug regimen; and 6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient's genetic variations; and adjusting the patient's drug regimen by performing one or more steps of:(a) removing the first drug and/or the second drug from the patient's drug regimen; (b) reordering which of the first drug and the second drug is taken first by the patient; (c) changing the timing of when the first drug and/or the second drug are taken by the patient; (d) changing time of day when the first drug and/or the second drug are taken by the patient; (e) replacing the first drug and/or the second drug of the patient's drug regimen with one or more alternate drugs of the same class and/or category as the first drug and/or the second drug; (f) reducing the dosage of the first drug and/or the second drug from an initial dosage to a reduced dosage; (g) increasing the dosage of the first drug and/or the second drug from an initial dosage to an increased dosage; (h) performing a surgical procedure; and (i) adding at least a third drug to the patient's drug regimen.
as presently drafted, under the broadest reasonable interpretation, covers a method of organizing human activity (i.e., managing personal behavior including following rules or instructions). For example, but for the noted computer elements, the claim encompasses a person following rules or instructions to assess and process data in the manner described in the abstract idea, such as a person assesses various patient drug data and patient characteristics to determine the patient’s overall risk of an adverse event in their medication regimen. The examiner further notes that “methods of organizing human activity” includes a person’s interaction with a computer (see October 2019 Update: Subject Matter Eligibility at Pg. 5). If the claim limitation, under its broadest reasonable interpretation, covers managing persona behavior or interactions between people but for the recitation of generic computer components, then it falls within the “method of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
MPEP 2106 Step 2A – Prong 2:
This judicial exception is not integrated into a practical application because there are no meaningful limitations that transform the exception into a patent eligible application. The additional elements merely amount to instructions to apply the exception using generic computer components (“a non-transitory computer-readable medium” and "a database” all recited at a high level of generality). Although they have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." (See MPEP 2106.04(d)(I) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claims only manipulate abstract data elements as part of performing the abstract idea. They do not set forth improvements to another technological field or the functioning of the computer itself and instead use computer elements as tools in a conventional way to improve the functioning of the abstract idea identified above. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. None of the additional elements recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
At the levels of abstraction described above, the claims do not readily lend themselves to a finding that they are directed to a nonabstract idea. Therefore, the analysis proceeds to step 2B. See BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016) ("The Enfish claims, understood in light of their specific limitations, were unambiguously directed to an improvement in computer capabilities. Here, in contrast, the claims and their specific limitations do not readily lend themselves to a step-one finding that they are directed to a nonabstract idea. We therefore defer our consideration of the specific claim limitations’ narrowing effect for step two.") (citations omitted).
MPEP 2106 Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons as presented in Step 2A Prong 2. Moreover, the additional elements recited are known and conventional generic computing elements (“a non-transitory computer-readable medium” and "a database” see Specification Fig. 17, [0161], [00166] describing the various components as general purpose, common, standard, known to one of ordinary skill, and at a high level of generality, and in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy the statutory disclosure requirements). Therefore, these additional elements amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept that amounts to significantly more. See MPEP 2106.05(f).
The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, translating, and displaying data—see Specification above as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these computer functions).
Dependent Claims
The limitations of dependent but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented. Claim 2, 3, 5-10, 15, 19. and 21-22 merely recites calculating the risk using various patient/medication data, claim 4 merely recites visually providing the risk score, claim 19 merely recites further adjusting the regime to reduce the risk, which covers a method of organizing human activity (i.e., managing personal behavior including following rules or instructions).
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 (i.e., changing from AIA to pre-AIA ) 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) 1, 3-20, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Von Schweber et al. (USPPN: 2010/0223068; hereinafter Von Schweber) in further view of Hoffman et al. (USPPN: 2014/0358576; hereinafter Hoffman).
As to claim 1, Von Schweber teaches A non-transitory computer-readable medium with instructions stored thereon, that when executed by a processor (e.g., see Abstract, Fig. 8, [0128] teaching a method/apparatus/machine-readable medium), perform a method comprising:
calculating an aggregated risk factor score representative of each of two or more risk factors associated with a patient’s drug regimen (e.g., see Abstract, Fig. 1, [0040]-[0051] teaching various regime risk evaluation methods including aggregating a risk of two or more components of the regimen), wherein the two or more risk factors are selected from the group comprising:
number of active ingredients in the drug regimen, 2) anticholinergic burden of the active ingredients in the drug regimen, 3) sedative burden of the active ingredients in the drug regimen, 4) QT-interval prolongation risk of the active ingredients in the drug regimen, 5) competitive inhibition of the active ingredients in the drug regimen, wherein competitive inhibition includes any pharmacokinetic interaction including: interactions between active ingredient inhibitors and active ingredient substrates, interactions between active ingredient inducers and active ingredient substrates, and interactions between active ingredient substrates of the same isoenzyme with different affinities, and 6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient’s genetic variations (e.g., see Fig. 1, [0035], [0096], [0102] teaching calculating aggregated risk factor of multiple risk factors associated with a patient’s drug regimen); and
While Von Schweber teaches combining risk factors to provide a quantitative personalized medication risk score that is representative of the patient’s risk for an adverse drug event (e.g., see Fig. 1) and further teaches calculating multiple aggregated risk factor scores, Von Schweber fails to explicitly teach combining the aggregated risk factor scores calculated for each of said two or more risk factors.
However, in the same field of endeavor of assessing patient risks associated with medical products, Hoffman teaches combining the aggregated risk factor scores calculated for each of said two or more risk factors to provide a quantitative personalized medication risk score that is representative of the patient’s risk for an adverse drug event (e.g., see [0089] teaching calculating an overall risk score of a patient of all medications the patient is using).
Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman).
As to claim 3, the rejection of claim 1 is incorporated. Von Schweber fails to teach combining the aggregated risk factor scores calculated for each of said two or more risk factors to further provide a data set representative of a patient population’s risk of an adverse drug event.
However, in the same field of endeavor of assessing patient risks associated with medical products, Hoffman teaches combining the aggregated risk factor scores calculated for each of said two or more risk factors to further provide a data set representative of a patient population’s risk of an adverse drug event (e.g., see [0016], [0089] teaching calculating an overall risk score of all medications a patient is using, the patient being for a particular patient, patient group, or population).
Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman).
As to claim 4, the rejection of claim 1 is incorporated. Von Schweber further teaches providing the quantitative personalized medication risk score as a visual representation of a relative risk of each of said risk factors with respect to each other (e.g., see Fig. 1 wherein a personalized risk score is provided as a visual representation displaying relative risks with respect to one another).
As to claim 5, the rejection of claim 1 is incorporated. Von Schweber further teaches wherein calculating the aggregated risk factor score representative of the number of active ingredients in the drug regimen comprises importing a data set comprising patient-specific drug regimens, converting said data into respective active ingredients, quantifying the number of active ingredients each patient-specific regimen contains, and assigning the risk factor score representative of the number of active ingredients in the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. Nonetheless, e.g., see [0010], [0096], [0103] wherein the aggregated risk factor score comprises importing data of patient-specific drug regimens, identifying any level of composition of the regimen, including individual ingredients, and assigning a risk score).
As to claim 6, the rejection of claim 1 is incorporated. Von Schweber-Hoffman further teaches wherein calculating the aggregated risk factor score representative of the anticholinergic burden of the active ingredients in the drug regimen comprises importing a data set comprising indices of anticholinergic burden, associating the respective active ingredients with their clinically determined anticholinergic value, quantifying the value for the entire respective regimen, and assigning the aggregated risk factor score representative of the anticholinergic burden of the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber and Hoffman, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. e.g., see [0010], [0096] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event. See also [0062], [0074], Table 1, Table 2 teaching a plurality of risk scores that can be calculated, including those impacting the nervous system).
As to claim 7, the rejection of claim 1 is incorporated. Von Schweber-Hoffman further teaches wherein calculating the aggregated risk factor score representative of the sedative burden of the active ingredients in the drug regimen comprises importing a data set comprising indices of sedation effects, associating the respective active ingredients with their clinically determined sedation value, quantifying the value for the entire respective regimen, and assigning the aggregated risk factor score representative of the sedative burden of the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber and Hoffman, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. e.g., see [0010], [0037], [0096], [0102] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event, including drowsiness. See also [0062], [0074], Table 1, Table 2 teaching a plurality of risk scores that can be calculated, including barbiturates (i.e., sedatives)).
As to claim 8, the rejection of claim 1 is incorporated. Von Schweber-Hoffman further teaches wherein calculating the aggregated risk factor score representative of the QT-interval prolongation risk of the active ingredients in the drug regimen comprises importing a data set comprising indices of QT-interval prolongation risk, associating the respective active ingredients with their clinically determined QT-risk value, quantifying the value for the entire respective regimen, and assigning the aggregated risk factor score representative of the QT-interval prolongation risk of the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber and Hoffman, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. e.g., see [0010], [0096], [0100] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event, including heart palpitations. See also [0062], [0074], Table 1, Table 2 teaching a plurality of risk scores that can be calculated).
As to claim 9, the rejection of claim 1 is incorporated. Von-Schweber-Hoffman further teaches wherein calculating the aggregated risk factor score representative of the competitive inhibition of the active ingredients in the drug regimen comprises importing a data set comprising metabolic pathways and extent of metabolism for each active ingredient, associating the respective active ingredients with competitive inhibition values based on shared pathways, quantifying the competitive inhibition value for the entire respective regimen, and assigning the aggregated risk factor score representative of the competitive inhibition of the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber and Hoffman, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. e.g., see [0010], [0037], [0096] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event, including drowsiness. See also [0062], [0074], Table 1, Table 2 teaching a plurality of risk scores that can be calculated, including inhibitors).
As to claim 10, the rejection of claim 1 is incorporated. Von-Schweber-Hoffman further teaches wherein calculating each of the aggregated risk factor scores comprises: importing a first data set comprising patient-specific drug regimens, converting said data set into respective active ingredients, quantifying the number of active ingredients each patient-specific regimen contains, and assigning the aggregated risk factor score representative of the number of active ingredients in the drug regimen; importing a second data set comprising indices of anticholinergic burden, associating the respective active ingredients with their clinically determined anticholinergic value, quantifying the value for the entire respective regimen, and assigning the aggregated risk factor score representative of the anticholinergic burden of the drug regimen; importing a third data set comprising indices of sedation effects, associating the respective active ingredients with their clinically determined sedation value, quantifying the value for the entire respective regimen, and assigning the aggregated risk factor score representative of the sedative burden of the drug regimen; importing a fourth data set comprising indices of QT-prolongation risk, associating the respective active ingredients with their clinically determined QT-risk value, quantifying the value for the entire respective regimen, and assigning the aggregated risk factor score representative of the QT-interval prolongation risk of the drug regimen; and importing a fifth data set comprising metabolic pathways and extent of metabolism for each active ingredient, associating the respective ingredients with competitive inhibition values based on shared pathways, quantifying the competitive inhibition value for the entire respective regimen, and assigning the aggregated risk factor score representative of the competitive inhibition of the drug regimen; and importing a sixth data set comprising information regarding the patient's genetic variations affecting drug metabolism for each active ingredient, associating the respective ingredient with their clinically determined pharmacogenomic risk value, quantifying the pharmacogenomic risk value for the entire respective regimen, and assigning the aggregated risk factor score representative of the pharmacogenomic risk of the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber and Hoffman, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. e.g., see [0010], [0037], [0096], [0102] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event, including drowsiness, heart palpitations, etc. See also [0062], [0074], Table 1, Table 2 teaching a plurality of risk scores that can be calculated, including those impacting the nervous system, inhibitors, sedatives, etc.).
As to claim 11, the claim is directed to a processor (e.g., see Fig. 8 of Von Schweber) implementing the instructions of non-transitory medium of claim 1, and is similarly rejected.
As to claim 12, the claim is directed to client device (e.g., see Fig. 8 of Von Schweber) comprising the processor of claim 11, and further recites a communication infrastructure, a memory, a user interface and a communication interface (e.g., see Fig. 8), and is similarly rejected.
As to claim 13, the claim is directed to a system comprising one or more computing devices (e.g., see Fig. 8 of Von Schweber) comprising the processor of claim 11, and is similarly rejected.
As to claim 14, Von Schweber teaches A computer implemented system for determining a patient’s risk of an adverse drug event based on the patient’s drug regimen (e.g., see Abstract, Fig. 8, [0128] teaching a method/apparatus/machine-readable medium), comprising:
a database containing two or more of the following data sets related to the patient’s risk factors: number of active ingredients in the drug regimen, 2) anticholinergic burden of the active ingredients in the drug regimen, 3) sedative burden of the active ingredients in the drug regimen, 4) QT-interval prolongation risk of the active ingredients in the drug regimen, 5) competitive inhibition of the active ingredients in the drug regimen, wherein competitive inhibition includes any pharmacokinetic interaction including: interactions between active ingredient inhibitors and active ingredient substrates, interactions between active ingredient inducers and active ingredient substrates, and interactions between active ingredient substrates of the same isoenzyme with different affinities, and 6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient’s genetic variations (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber, having taught a plurality of different risk factor scores that can be calculated using data from a database, then it meets the claimed limitation. e.g., see Fig. 1, [0010], [0096], [0124], [0125] teaching a plurality of databases for relational drug data, wherein any level of composition of the regimen can be applied, including drowsiness, heart palpitations, plurality of ingredients, etc.); and
While Von Schweber teaches a calculating module, which applies algorithms and calculates a quantitative personalized medication risk score that is representative of the patient’s risk for an adverse drug event (e.g., see Fig. 1, [0097]-[0099]) and further teaches calculating multiple aggregated risk factor scores, Von Schweber fails to explicitly teach the algorithm to said two or more data sets.
However, in the same field of endeavor of assessing patient risks associated with medical products, Hoffman teaches two or more data sets (e.g., see [0089] teaching calculating an overall risk score of a patient of all medications the patient is using).
Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman).
As to claim 15, the rejection of claim 14 is incorporated. Hoffman further teaches wherein the calculating module calculates the quantitative personalized medication risk score based on aggregated risk factor scores representative of each of the two or more data sets (e.g., see [0089] teaching calculating an overall risk score of a patient of all medications the patient is using).
Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman).
As to claim 16, Von Schweber teaches A method of reducing a risk of an adverse drug event in a patient, wherein the patient has been prescribed a drug regimen that includes at least a first drug and a second drug (e.g.,see Abstract, Figs. 1, 3), the method comprising:
calculating a quantitative personalized medication risk score that is representative of the patient's risk for an adverse drug event by combining aggregated risk factor scores associated with the patient's drug regimen (e.g., see Fig. 1, [0035], [0096], [0102] teaching calculating aggregated risk factor of multiple risk factors associated with a patient’s drug regimen),
wherein the two or more risk factors are selected from the group consisting of: 1) number of active ingredients in the drug regimen, 2) anticholinergic burden of the drug regimen, 3) sedative burden of the drug regimen, 4) QT-interval prolongation risk of the drug regimen, and 5) competitive inhibition of the drug regimen; and 6) pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient's genetic variations (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber, having taught a plurality of different risk factor scores that can be calculated using data from a database, then it meets the claimed limitation. e.g., see [0010], [0037], [0096], [0102] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event at any level of composition of the regimen, including drowsiness, heart palpitations, plurality of ingredients, etc.); and
adjusting the patient's drug regimen by performing one or more steps of: (a) removing the first drug and/or the second drug from the patient's drug regimen; (b) reordering which of the first drug and the second drug is taken first by the patient; (c) changing the timing of when the first drug and/or the second drug are taken by the patient; (d) changing time of day when the first drug and/or the second drug are taken by the patient; (e) replacing the first drug and/or the second drug of the patient's drug regimen with one or more alternate drugs of the same class and/or category as the first drug and/or the second drug; (f) reducing the dosage of the first drug and/or the second drug from an initial dosage to a reduced dosage; (g) increasing the dosage of the first drug and/or the second drug from an initial dosage to an increased dosage; (h) performing a surgical procedure; and (i) adding at least a third drug to the patient's drug regimen (e.g., see Fig. 3, [0011], [0103] wherein in response to the identified risk, modifications to the patient’s regimen can be implemented including modification of the medication and/or dose/duration/frequency, etc.).
While Von Schweber teaches combining risk factors to provide a quantitative personalized medication risk score that is representative of the patient’s risk for an adverse drug event (e.g., see Fig. 1) and further teaches calculating multiple aggregated risk factor scores, Von Schweber fails to explicitly teach combining the aggregated risk factor scores calculated for each of said two or more risk factors.
However, in the same field of endeavor of assessing patient risks associated with medical products, Hoffman teaches combining the aggregated risk factor scores calculated for each of said two or more risk factors to provide a quantitative personalized medication risk score that is representative of the patient’s risk for an adverse drug event (e.g., see [0089] teaching calculating an overall risk score of a patient of all medications the patient is using).
Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman).
As to claim 17, the claim is directed to the non- transitory computer-readable medium (e.g., see Fig. 8) implementing the method of claim 16 and is similarly rejected.
As to claim 18, the claim is directed to a computing device (e.g., see Fig. 8) implementing the instructions of the computer-readable medium of claim 17 and is similarly rejected.
As to claim 19, the rejection of claim 16 is incorporated. Hoffman further teaches comparing the patient's quantitative personalized medication risk score for the drug regimen to quantitative personalized medication risk scores of a patient population for said drug regimen (e.g., see [0016], [0041], [0077] wherein a risk score can be calculated for a patient, patient group, or patient population and the factoring risks are compared to weightings assigned to similar data points).
As to claim 20, the rejection of claim 16 is incorporated. Von Schweber further wherein adjusting the patient's drug regimen causes the quantitative personalized medication risk score to decrease (e.g., see [0103] wherein the modification can reduce the combined risk).
As to claim 22, the rejection of claim 10 is incorporated. Von Schweber teaches wherein the step of importing the first data set comprises associating each of the respective active ingredients with its respective risk of one or more side effects by utilizing data from the FDA Adverse Event Reporting System, quantifying the associated respective risk of one or more side effects of each respective active ingredient in each patient-specific regimen, and assigning an aggregated risk score based on a combined associated respective risk of one or more side effects of each respective active ingredient (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber, having taught a plurality of different risk factor scores that can be calculated using data from a database, then it meets the claimed limitation. e.g., see [0010], [0037], [0096], [0102] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event at any level of composition of the regimen).
Nonetheless, for the purposes of compact prosecution and in the same filed of endeavor of assessing patient risk score associated with medical products, Hoffman explicitly teaches the database being from an FDA Adverse Event Reporting system (e.g., see [0010], [0011], [0031], [0062], [0075]-[0077] wherein the system uses available information for predicting risks associated with use of a drug/medication from numerous sources including the FDA Adverse Event Reporting System). Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman).
Claim(s) 2 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Von Schweber and Hoffman, as applied above, and in further view of Knowlton (USPPN: 2015/0178465; hereinafter Knowlton).
As to claim 2, the rejection of claim 1 is incorporated. Von Schweber-Hoffman further teach wherein the method comprises calculating the risk factor score representative of [six] or more risk factors associated with the patient’s drug regiment within a patient population, wherein the risk factors comprise:
number of active ingredients in the drug regimen, 3) sedative burden of the active ingredients in the drug regimen, 4) QT-interval prolongation risk of the active ingredients in the drug regimen, 6) competitive inhibition of the active ingredients in the drug regimen (e.g., see [0035], [0037], [0096], [0100], [0107]-[0110] of Von Schweber teaching calculating risk scores for a plurality of different risk factors for a regimen at any level of composition, including the risk of drowsiness (i.e., sedation), heart palpitations (i.e, QT-interval prolongation), and the active ingredients.
While Von Schweber teaches calculating a risk score for a plurality of different risk factors, Von Schweber fails to explicitly teach wherein the risk factor comprises: anticholinergic burden of the active ingredients in the drug regimen, and inhibition of the active ingredients in the drug regimen (e.g., see [0089], Table 1 of Hoffman wherein an aggregate risk score is calculated from a plurality of individual risks, including inhibitors and anticholingertic. Accordingly, it would have been obvious to modify Von Schweber in view of Hoffman before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0018], [0019] of Hoffman)).
While Von Schweber-Hoffman teach calculating a risk factor score representative of a plurality of risk factors, Von Schweber-Hoffman fail to teach the risk factor comprising pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient’s genetic variations.
However, in the same field of endeavor of medication risk mitigation, Knowlton teaches the risk factor comprising pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient’s genetic variations (e.g., see [0017]-[0033], [0051] teaching a plurality of components for determining a medication risk, including pharmacogenomic data, sedative burdens, anticholinergic burden, drug-drug interactions, etc.). Accordingly, it would have been obvious to modify Von Schweber-Hoffman in view of Knowlton before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0011], [0035] of Knowlton)).
As to claim 21, the rejection of claim 1 is incorporated. Von Schweber-Hoffman teach wherein calculating the aggregated risk factor score representative of the pharmacogenomic interactions of the active ingredients in the drug regimen based on the patient's genetic variations comprises importing a sixth data set comprising information regarding the patient's genetic variations affecting drug metabolism for each active ingredient, associating the respective ingredient with their clinically determined pharmacogenomic risk value, quantifying the pharmacogenomic risk value for the entire respective regimen, and assigning the aggregated risk factor score representative of the pharmacogenomic risk of the drug regimen (Notably, the particular type of risk factor is interpreted as non-functional descriptive language as they are not functionally required in the claimed method. See MPEP 2111.05. The function described in the claimed method would be performed regardless of the particular type of risk factor score calculated. Therefore, Von Schweber and Hoffman, having taught a plurality of different risk factor scores that can be calculated, then it meets the claimed limitation. e.g., see [0010], [0037], [0096], [0102] wherein aggregated risk factor score comprising importing data from various databases to associated a probable risk of an adverse event, including drowsiness, heart palpitations, etc. See also [0062], [0074], Table 1, Table 2 teaching a plurality of risk scores that can be calculated, including those impacting the nervous system, inhibitors, sedatives, etc.).
Nonetheless, for the purposes of compact prosecution and in the same field of endeavor of medication risk mitigation, Knowlton teaches pharmacogenomic risk (e.g, see [0021], [0035] wherein a pharmacogenomic risk of a drug regimen is assessed).
Accordingly, it would have been obvious to modify Von Schweber-Hoffman in view of Knowlton before the effective date of the present invention with a reasonable expectation of success. One would have been motivated to make the modification in order to produce a probability safety risk score comprising the plurality of potential risks to a patient (e.g., see [0011], [0035] of Knowlton)).
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). Further, a reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill the art, including nonpreferred embodiments. Merck & Co. v. Biocraft Laboratories, 874 F.2d 804, 10 USPQ2d 1843 (Fed. Cir.), cert. denied, 493 U.S. 975 (1989). See also Upsher-Smith Labs. v. Pamlab, LLC, 412 F.3d 1319, 1323, 75 USPQ2d 1213, 1215 (Fed. Cir. 2005); Celeritas Technologies Ltd. v. Rockwell International Corp., 150 F.3d 1354, 1361, 47 USPQ2d 1516, 1522-23 (Fed. Cir. 1998).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/STELLA HIGGS/Primary Examiner, Art Unit 3681
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