DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This action is in response to application filed on 5/30/2024, in which claims 1 – 20 was presented for examination.
3. Claims 1 – 20 are pending in the application.
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 10/6/2025 has been reviewed and entered into the record. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
5. Claims 1 - 20 are directed are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As per claim 1,
Step 1: Claim 1 recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The claim recites the limitation of
obtaining mechanism of action (MOA) data that is indicative of a hierarchical tree structure of relationships between the MOA data (Mental Process performed in human mind using a pen and paper (i.e. observation)).
generating linear representations of branches of the hierarchical tree structure (Mental Process performed in human mind using a pen and paper (i.e. organization)).
determining association rules for the MOA data by applying one or more frequent pattern mining algorithm to the linear representations (Mental Process performed in human mind using a pen and paper (i.e. evaluation)).
determining, as at least a portion of the generated machine learning training data, MOA clusters by applying a clustering model to the linear representations and the association rules (Mental Process performed in human mind using a pen and paper (i.e. evaluation)).
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the additional elements of
determining association rules for the MOA data by applying one or more frequent pattern mining algorithm to the linear representations (the step is directed to evaluating information, which is understood to be significant extra-solution activity and is well understood, routine, and conventional activity of preparing data for presentation (MPEP 2106.05(d)(II)(i))))).
determining, as at least a portion of the generated machine learning training data, MOA clusters by applying a clustering model to the linear representations and the association rules (the step is directed to evaluating information, which is understood to be significant extra-solution activity and is well understood, routine, and conventional activity of preparing data for presentation (MPEP 2106.05(d)(II)(i))))).
Although the additional element limits the identified judicial exceptions. The limitation merely confines the use of the abstract idea to a particular technological environment and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional element
determining association rules for the MOA data by applying one or more frequent pattern mining algorithm to the linear representations (the step is directed evaluating and presenting information, which is understood to be significant extra-solution activity, and is well understood, routine, and conventional activity of preparing data for presentation (MPEP 2106.05(d)(II)(i))))).
determining, as at least a portion of the generated machine learning training data, MOA clusters by applying a clustering model to the linear representations and the association rules (the step is directed evaluating and presenting information, which is understood to be significant extra-solution activity, and is well understood, routine, and conventional activity of preparing data for presentation (MPEP 2106.05(d)(II)(i))))).
As explained above, the additional element is recited at a high level of generality. These elements amount to receiving, generating, and organizing information are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. The recitation of a computer to perform these limitations amounts to no more than mere instructions to apply the exception using a generic computer. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
Thus, the claim is ineligible.
As per claim 2, the rejection of claim 1 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
determining the hierarchical tree structure by: extracting a plurality of nodes from the MOA data and generating the hierarchical tree structure based on the extracted nodes (Mental Process performed in human mind using a pen and a paper (i.e. organization)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
determining the hierarchical tree structure by: extracting a plurality of nodes from the MOA data and generating the hierarchical tree structure based on the extracted nodes (the step is directed to organizing information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 3, the rejection of claim 1 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein generating linear representations of branches of the hierarchical tree structure includes applying one or more techniques selected from the group consisting of: tokenization, vectorization, max and min n-gram limit determination, word clouds, median treatments, segmentation, text classification, and categorical transformation (Mental Process performed in human mind using a pen and a paper (i.e. organization)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein generating linear representations of branches of the hierarchical tree structure includes applying one or more techniques selected from the group consisting of: tokenization, vectorization, max and min n-gram limit determination, word clouds, median treatments, segmentation, text classification, and categorical transformation (the step is directed to organizing information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 4, the rejection of claim 1 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein determining association rules for the linear representations comprises applying a Frequent Pattern (FP) Growth algorithm (Mathematical Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein determining association rules for the linear representations comprises applying a Frequent Pattern (FP) Growth algorithm (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 5, the rejection of claim 1 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein determining MOA clusters comprises applying a clustering model selected from the group consisting of: a Gaussian Mixture Model (GMM), K-Means Clustering, and hierarchical clustering (Mathematical Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein determining MOA clusters comprises applying a clustering model selected from the group consisting of: a Gaussian Mixture Model (GMM), K-Means Clustering, and hierarchical clustering (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 6, the rejection of claim 1 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
transforming the MOA clusters into numerical representations for use as input into a machine learning model (Mathematical Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
transforming the MOA clusters into numerical representations for use as input into a machine learning model (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 7, the rejection of claim 1 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein the machine learning training data further includes a labeled dataset indicating whether a post-marketing requirement (PMR) was imposed on a previous clinical trial. (Mental Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein the machine learning training data further includes a labeled dataset indicating whether a post-marketing requirement (PMR) was imposed on a previous clinical trial. (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 8,
Step 1: Claim 8 recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The claim recites the limitation of
predicting whether a post-marketing requirement (PMR) will be imposed on a clinical trial (Mental Process performed in human mind using a pen and paper (i.e. evaluating)).
obtaining data associated with a clinical trial (Mental Process performed in human mind using a pen and paper (i.e. observation)).
obtaining mechanism of action (MOA) data associated with the clinical trial, the MOA data indicative of a hierarchical tree structure of relationships between the MOA data (Mental Process performed in human mind using a pen and paper (i.e. observation)).
generating a linear representation of one or more branches of the hierarchical tree structure (Mental Process performed in human mind using a pen and paper (i.e. organization)).
generating a prediction of whether a PMR will be imposed on the clinical trial by applying a trained machine learning model to the data associated with the clinical trial and the linear representation of the one or more branches (Mental Process performed in human mind using a pen and paper (i.e. evaluation)).
the trained machine learning model having been trained based on clusters of linear representations of historical MOA data (Mental Process performed in human mind using a pen and paper (i.e. organization)).
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the additional elements of
generating a prediction of whether a PMR will be imposed on the clinical trial by applying a trained machine learning model to the data associated with the clinical trial and the linear representation of the one or more branches (the step is directed to evaluating information, which is understood to be significant extra-solution activity and is well understood, routine, and conventional activity of preparing data for presentation (MPEP 2106.05(d)(II)(i))))).
Although the additional element limits the identified judicial exceptions. The limitation merely confines the use of the abstract idea to a particular technological environment and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional element
generating a prediction of whether a PMR will be imposed on the clinical trial by applying a trained machine learning model to the data associated with the clinical trial and the linear representation of the one or more branches (the step is directed evaluating and presenting information, which is understood to be significant extra-solution activity, and is well understood, routine, and conventional activity of preparing data for presentation (MPEP 2106.05(d)(II)(i))))).
As explained above, the additional element is recited at a high level of generality. These elements amount to receiving, generating, and organizing information are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. The recitation of a computer to perform these limitations amounts to no more than mere instructions to apply the exception using a generic computer. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
Thus, the claim is ineligible.
As per claim 9, the rejection of claim 8 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein the data associated with the clinical trial includes one or more of: global approval status, key regulatory events, therapeutic class, license country, originator country, and target (Mental Process performed in human mind using a pen and a paper (i.e. observation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein the data associated with the clinical trial includes one or more of: global approval status, key regulatory events, therapeutic class, license country, originator country, and target (the step is directed to observation of information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 10, the rejection of claim 8 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
the trained machine learning model was further trained using regulatory data from one or more of the Food and Drug Administration (FDA) or the European Medicines Agency (EMA) (Mental Process performed in human mind using a pen and a paper (i.e. observation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
the trained machine learning model was further trained using regulatory data from one or more of the Food and Drug Administration (FDA) or the European Medicines Agency (EMA) (the step is directed to observation of information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible
As per claim 11, the rejection of claim 8 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
causing a user interface of a user device to display the prediction (Mental Process performed in human mind using a pen and a paper (i.e. organization)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
causing a user interface of a user device to display the prediction (the step is directed to organizing information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 11, the rejection of claim 8 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein the trained machine learning model includes a gradient-boosting decision tree model. (Mental Process performed in human mind using a pen and a paper (i.e. organization)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein the trained machine learning model includes a gradient-boosting decision tree model. (the step is directed to organizing information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 13, the rejection of claim 8 is incorporated.
Step 1: The claim recites a method, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein the prediction further includes an indication of a specific type of PMR likely to be imposed (Mental Process performed in human mind using a pen and a paper (i.e. organization)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein the prediction further includes an indication of a specific type of PMR likely to be imposed (the step is directed to organizing information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claims 14 - 16
Step 1: The claim recites a system, which is one of the four statutory categories of eligible matter.
Claims 14 – 16 are system claim corresponding to method claims 8 – 10 respectively and rejected under the same reason set forth in connection to the rejection of claims 8 – 10 respectively above.
As per claim 17, the rejection of claim 14 is incorporated.
Step 1: The claim recites a system, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein the one or more processors are configured to periodically retrain the trained machine learning model with updated data, wherein the updated data includes one or more of: MOA data, linear representations of MOA data, clusters of linear representations of MOA, data associated with a clinical trial, and regulatory data. (Mental Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein the one or more processors are configured to periodically retrain the trained machine learning model with updated data, wherein the updated data includes one or more of: MOA data, linear representations of MOA data, clusters of linear representations of MOA, data associated with a clinical trial, and regulatory data (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 18, the rejection of claim 14 is incorporated.
Step 1: The claim recites a system, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
an interactive user interface configured to receive a drug query from a user and to display a prediction of whether a PMR will be imposed on a clinical trial associated with the drug query (Mental Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
an interactive user interface configured to receive a drug query from a user and to display a prediction of whether a PMR will be imposed on a clinical trial associated with the drug query (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
The claim is not patent eligible.
As per claim 19, the rejection of claim 18 is incorporated.
Step 1: The claim recites a system, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
wherein the interactive user interface is further configured to display an indication of a specific type of PMR likely to be imposed. (Mental Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
wherein the interactive user interface is further configured to display an indication of a specific type of PMR likely to be imposed (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
As per claim 20, the rejection of claim 19 is incorporated.
Step 1: The claim recites a system, which is one of the four statutory categories of eligible matter.
Step 2A Prong 1: The judicial exceptions of claim 1 are incorporated, the limitation of
herein the interactive user interface is further configured to display details of historical post-marketing studies and types of studies mandated for drugs associated with the drug query (Mental Process performed in human mind using a pen and a paper (i.e. evaluation)).
Step 2A Prong 2: the judicial exceptions are not integrated into a practical application. The claim recites additional elements of
herein the interactive user interface is further configured to display details of historical post-marketing studies and types of studies mandated for drugs associated with the drug query (the step is directed to evaluating information, which is understood to be significant extra-solution activity, see MPEP 2106.05(g)).
The limitation recited at high level of generality and thus are insignificant extra-solution activity. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions. Mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
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.
6. Claims 1 – 5 and 7 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Piffo et al (WO 2023/245301 A1), in view of Shyu et al (US 11,055,351 B1).
As per claim 1, Piffo et al (WO 2023/245301 A1) discloses,
A computer-implemented method for generating machine learning training data (para.[0075]; “a machine learning engine comprising a model trained with the data processed by the data processing engine”).
Piffo does not specifically disclose obtaining mechanism of action (MOA) data that is indicative of a hierarchical tree structure of relationships between the MOA data, generating linear representations of branches of the hierarchical tree structure, determining association rules for the MOA data by applying one or more frequent pattern mining algorithm to the linear representations, and determining, as at least a portion of the generated machine learning training data, MOA clusters by applying a clustering model to the linear representations and the association rules.
However, Shyu et al (US 11,055,351 B1) in an analogous art discloses,
the method comprising: obtaining mechanism of action (MOA) data that is indicative of a hierarchical tree structure of relationships between the MOA data (col.2 lines 29 – 30; “construct a graph structure, and frequent patterns”, col.10 3 – 4; “create the trees of the persistent data structure”, and col.26 lines 42 - 44; “persistent data structure, FHPTree and FHPGrowth, which can be constructed as a tree”).
generating linear representations of branches of the hierarchical tree structure (col.2 lines 49 – 50; “nodes in the tree structure is linearly dependent on the number of unique items”).
determining association rules for the MOA data by applying one or more frequent pattern mining algorithm to the linear representations (col.2 lines 51 – 53; “discover frequent patterns in a top-down fashion, locating maximal item sets before any of their subsets”).
and determining, as at least a portion of the generated machine learning training data, MOA clusters by applying a clustering model to the linear representations and the association rules (col.10 lines 56 – 57; “agglomerative clustering and is a way to define the structure of the persistent data structure”, col.11 lines 7 – 9; “nodes in an FHPTree, or the tree construction 400, increases linearly relative to the number of unique items”, and col.26 lines 56 – 58; “FHPTree is a hierarchical cluster tree of items, and FHPGrowth is a top-down mining scheme for extracting frequent patterns”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate frequent pattern mining process of the system of Shyu into drug development risk prediction of the system of Piffo to identify interesting pattern that exist in the clinical data, thereby providing relevant information for understating the clinical trial.
As per claim 2, the rejection of claim 1 is incorporated and further Shyu et al (US 11,055,351 B1) discloses,
further comprising: determining the hierarchical tree structure by: extracting a plurality of nodes from the MOA data and generating the hierarchical tree structure based on the extracted nodes (col.9 lines 65 - 67 and col.10 line 1; “persistent data structure 200 represents a tree construction 400. Within the tree construction 400, nodes are created as parent nodes 405 and child nodes 410 in a tree like branching structure”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate frequent pattern mining process of the system of Shyu into drug development risk prediction of the system of Piffo to obtain relevant data for generating the hierarchical data structure that accurately represent the data.
As per claim 3, the rejection of claim 1 is incorporated and further Shyu et al (US 11,055,351 B1) discloses,
wherein generating linear representations of branches of the hierarchical tree structure includes applying one or more techniques selected from the group consisting of: tokenization, vectorization, max and min n-gram limit determination, word clouds, median treatments, segmentation, text classification, and categorical transformation (col.20 lines 11 – 16; “extracting maximal frequent patterns from the chess dataset. FIG. 23 characterizes the runtime relative to the min_support threshold. At high support values, FPMax is fastest by a narrow margin, but as the 15 min_support threshold becomes small, the number of maximal frequent patterns increases”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate frequent pattern mining process of the system of Shyu into drug development risk prediction of the system of Piffo to obtain relevant data for generating the hierarchical data structure that accurately represent the data.
As per claim 4, the rejection of claim 1 is incorporated and further Shyu et al (US 11,055,351 B1) discloses,
wherein determining association rules for the linear representations comprises applying a Frequent Pattern (FP) Growth algorithm (col.6 lines 36 – 37; “execute the persistent data structure 200 or FHPTree and FHPGrowth”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate frequent pattern mining process of the system of Shyu into drug development risk prediction of the system of Piffo to obtain relevant data for generating the hierarchical data structure that accurately represent the data
As per claim 5, the rejection of claim 1 is incorporated and further Shyu et al (US 11,055,351 B1) discloses,
wherein determining MOA clusters comprises applying a clustering model selected from the group consisting of: a Gaussian Mixture Model (GMM), K-Means Clustering, and hierarchical clustering (col.12 lines 62 – 63; “persistent data structure 200 utilizes an agglomerative or hierarchical clustering”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate frequent pattern mining process of the system of Shyu into drug development risk prediction of the system of Piffo to obtain relevant data for generating the hierarchical data structure that accurately represent the data
As per claim 7, the rejection of claim 1 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the machine learning training data further includes a labeled dataset indicating whether a post-marketing requirement (PMR) was imposed on a previous clinical trial (pg.25 lines 27 – 29; “manual labeling processing by domain experts, the methods and systems will provide predictive and prescriptive insights from drug clinical development including clinical study startup to market access”).
As per claim 8, Piffo et al (WO 2023/245301 A1) discloses,
A computer-implemented method for predicting whether a post-marketing requirement (PMR) will be imposed on a clinical trial (para.[00141]; “prediction of clinical phase transitions (Phase l, Phase 11, Phase Ill and regulatory approval/pharmaco-economic approval), estimation of commercial success …. better control of risk factors/events in the conduct of clinical trials”, where pharmaco-economic approval is interpreted as “post-marketing requirement (PMR)” as claimed).
the method comprising: obtaining data associated with a clinical trial (para.[0147]; “access to a set of diverse trained models for different phases of clinical trials”).
obtaining mechanism of action (MOA) data associated with the clinical trial (para.[0004]; “obtaining regulatory approval for marketing authorization from regulatory agencies”).
and generating a prediction of whether a PMR will be imposed on the clinical trial by applying a trained machine learning model to the data associated with the clinical trial and the linear representation of the one or more branches (para.[0075]; “a model trained with the data processed by the data processing engine, the trained machine learning engine being configured to execute an algorithm to analyse the data of the data source relating to the clinical trial and to calculate a prediction of success of the clinical trial based on the said analyzed data”).
the trained machine learning model having been trained based on clusters of linear representations of historical MOA data (para.[0075]; “a model trained with the data processed by the data processing engine, the trained machine learning engine being configured to execute an algorithm to analyse the data of the data source
relating to the clinical trial”).
Piffo does not specifically disclose the MOA data indicative of a hierarchical tree structure of relationships between the MOA data, generating a linear representation of one or more branches of the hierarchical tree structure.
However, Shyu et al (US 11,055,351 B1) in an analogous art discloses,
the MOA data indicative of a hierarchical tree structure of relationships between the MOA data (col.2 lines 29 – 30; “construct a graph structure, and frequent patterns”, col.10 3 – 4; “create the trees of the persistent data structure”, and col.26 lines 42 - 44; “persistent data structure, FHPTree and FHPGrowth, which can be constructed as a tree”).
generating a linear representation of one or more branches of the hierarchical tree structure (col.2 lines 49 – 50; “nodes in the tree structure is linearly dependent on the number of unique items”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate frequent pattern mining process of the system of Shyu into drug development risk prediction of the system of Piffo to identify interesting pattern that exist in clinical data, thereby providing relevant information for understanding the clinical trial.
As per claim 9, the rejection of claim 8 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the data associated with the clinical trial includes one or more of: global approval status, key regulatory events, therapeutic class, license country, originator country, and target (para.[0075]; “data source comprising data relating to the clinical trial …. external data sources comprising data relating to clinical trials, regulatory approvals, economic and reimbursement information, pharmacological information, and commercial and corporate information” and para.[0148]; “information on clinical trials, regulatory approval decisions, economic and reimbursement data, pharmacological data”).
As per claim 10, the rejection of claim 8 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the trained machine learning model was further trained using regulatory data from one or more of the Food and Drug Administration (FDA) or the European Medicines Agency (EMA) (para.[0100]; “clinical phase data, such as approvals by Health Canada (Canada), Food and Drug Administration FDA (USA)”).
As per claim 11, the rejection of claim 8 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
further comprising: causing a user interface of a user device to display the prediction (para.[0147]; “report component 82 30 configured to display on a user interface a summary of the predictions”).
As per claim 12, the rejection of claim 8 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the trained machine learning model includes a gradient-boosting decision tree model (para.[00151]; “multi-tier model 207 to calculate predictions about the clinical trial” and para.[00152]; “machine learning model (tier 1) for predicting the 30 success based on the specific business needs”).
As per claim 13, the rejection of claim 8 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the prediction further includes an indication of a specific type of PMR likely to be imposed (para.[0151]; “calculating prediction of the protocol deviation 211 and calculating prediction of other factors”).
Claims 14 – 16 are system claim corresponding to method claims 8 – 10 respectively and rejected under the same reason set forth in connection to the rejection of claims 8 – 10 respectively above.
As per claim 17, the rejection of claim 14 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the one or more processors are configured to periodically retrain the trained machine learning model with updated data, wherein the updated data includes one or more of: MOA data, linear representations of MOA data, clusters of linear representations of MOA, data associated with a clinical trial, and regulatory data (para.[0084]; “developing a plurality of machine learning model for 30 the clinical trial, training the developed models with acquired data and selecting one or more of the developed models based on performance metrics”).
As per claim 18, the rejection of claim 14 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
further comprising: an interactive user interface configured to receive a drug query from a user and to display a prediction of whether a PMR will be imposed on a clinical trial associated with the drug query (para.[0147]; “report component 82 configured to display on a user interface a summary of the predictions”).
As per claim 19, the rejection of claim 18 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
19. The system of claim 18, wherein the interactive user interface is further configured to display an indication of a specific type of PMR likely to be imposed (para.[0147]; “configured to display on a user interface a summary of the predictions”).
As per claim 20, the rejection of claim 19 is incorporated and further Piffo et al (WO 2023/245301 A1) discloses,
wherein the interactive user interface is further configured to display details of historical post-marketing studies and types of studies mandated for drugs associated with the drug query (para.[00147]; “a report component 82 configured to display on a user interface a summary of the predictions, the predictive factors, the models and the counterfactual recommendations and explanations”).
7. Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Piffo et al (WO 2023/245301 A1), in view of Shyu et al (US 11,055,351 B1), and further in view of Wang et al (US 2023/0342348 A1).
As per claim 6, the rejection of claim 1 is incorporated, Piffo and Shyu does not specifically disclose transforming the MOA clusters into numerical representations for use as input into a machine learning model.
However, Wang et al (US 2023/0342348 A1) in an analogous art discloses,
further comprising transforming the MOA clusters into numerical representations for use as input into a machine learning model (para.[0046]; “the tree structure is converted into a numerical representation, such as a vector or matrix, that can be used as input to a machine learning model”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate numerical representation of data of the system of Wang into frequent pattern mining process of the system of Shyu to provide a model that can accurately process different types of data.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
TITLE: Collaborative data mining for clinical trial analytics, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), authors: Gholap et al.
TITLE: Clinical trial treatment effect evaluation method, device, equipment and storage medium, CN 117312881 A authors: Yan et al. (see Abstract, pg.4 and pg.5).
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/AUGUSTINE K. OBISESAN/
Primary Examiner
Art Unit 2156
8/2/2026
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