DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
In light of the amendments, the previous 35 U.S.C. 112(a) rejections are withdrawn.
In light of the amendments, the previous 35 U.S.C. 112(b) rejections are withdrawn.
In light of the amendments, the claims are rejected under 35 U.S.C. 101.
Notice to Applicant
In the amendment dated 05/28/2026, the following has occurred: claims 1, 8, and 15 have been amended; claims 4, 11, and 18 are canceled; claims 2-3, 5-7, 9-10, 12-14, 16-17, and 19 remain unchanged; and claims 21-23 have been added.
Claims 1-3, 5-10, 12-17, and 19-23 are pending.
Effective Filing Date: 11/07/2023
Response to Arguments
35 U.S.C. 112(a) and 112(b) Rejections:
Applicant amended the claims to overcome the previous 112(a) and 112(b) claims. Examiner withdraws the previous 112 rejections.
35 U.S.C. 101 Rejections:
Applicant argues that the claims are not merely directed to determining the appropriate steps to treat a patient undergoing radiation therapy treatment, but rather to a real-time, transcript-trained validation system that intercepts treatment planning errors before plan generation. Applicant points to the specification and states that the present invention overcomes technical difficulties in conventional approaches to validating radiotherapy by using a large language model. The mere application/execution of an LLM to provide a technical improvement is an additional element which is applied to the abstract idea.
Applicant then argues that a server is performing validity checks to intercept erroneous treatment planning decisions before they reach a treatment plan optimizer, catching process-level errors that conventional numerical validation methods are technically incapable of detecting. This however is not a statement reflected in the specification. Furthermore, detecting errors is not a process that is inherently inhuman.
Applicant also argues that there is identification of errors during a process as opposed to an end on one, and this is a technical improvement. It may be an improvement, but that improvement can be deemed as an improvement to an abstract idea. If the detection is already occurring how is it a technical improvement to change when the improvement is occurring?
Applicant further argues that there is an improvement in the newly recited claims. The input is being refined into a summary and then provided to a model which has a maximum length that limits the size of the input. The model itself is not being improved in a technical manner, rather it is being used within its own confines. The data provided to it is being improved so that the model can be used. An improvement to the data itself is not necessarily a technical improvement.
Additionally, Applicant argues that the training step is not math. This argument is deemed moot in view of the updated 101 rejection section in view of the amendments to the claims now directing the training step to an additional element under “apply it”.
Furthermore, Applicant argues in view of Recentive and states that the claims are not directed to making machine learning better, but rather improvements to systems and methods for radiation therapy treatment planning. Examiner agrees that the present claims are not directed improving machine learning. Applicant further states however that it is the specific training and specific data which is being provided to the machine learning model which enables for this improvement to occur. Examiner however respectfully disagrees as the specific improvements appear to be non-technical in nature and that of a biproduct of applying an LLM to this process.
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 1-3, 5-10, 12-17, and 19-23 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 1-3, 5-7, and 21 are drawn to a method and claims 8-10, 12-17, 19-20, and 22-23 are drawn to systems, each of which is within the four statutory categories. Claims 1-3, 5-10, 12-17, and 19-23 are further directed to an abstract idea on the grounds set out in detail below. As discussed below, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea (Step 1: YES).
Step 2A:
Prong One:
Claim 1 recites a method of validating radiotherapy treatment planning decisions proposed during tumor board meetings, the method comprising:
1) presenting, by a1) a processor, b) a user interface providing an interaction interface between a plurality of medical professionals communicating regarding a radiation therapy treatment of a patient during a tumor board meeting or a radiotherapy treatment planning process;
2) receiving, by a1) the processor through the interaction interface, a first input comprising a first patient attribute of the patient and a second input corresponding to the radiation therapy treatment of the patient;
3) generating, by a1) the processor, a prompt containing the first patient attribute of the patient and the radiation therapy treatment of the patient in a text format according to a prompt template stored c) in memory identifying locations corresponding to data types within the prompt, a first data type of the fist input, and a second data type of the second input;
4) executing, by a1) the processor, d) a large language model using the generated prompt to generate a text string of characters identifying a predicted task to be completed prior to generating a treatment plan for the patient generated using e) a treatment plan optimizer computer model,
wherein d) the large language model is trained using text of a set of transcriptions of a set of tumor board meetings or radiotherapy treatment planning processes for a set of previously implemented radiation therapy treatments and a hierarchy of tasks associated with generating treatment plans;
5) presenting, by a1) the processor, the text string of characters identifying the predicted task for the treatment plan on the interaction interface;
6) receiving, by a1) the processor from the interaction interface, a third input containing text identifying an input task, and
7) when the text of the third input does not match the text of the predicted task:
7a) presenting, by a1) the processor on the interaction interface, an indication of the predicted task and an indication of a difference between the input task and the predicted task;
7b) responsive to receiving, from the interaction interface, an indication accepting the predicted task, transmitting, by a1) the processor, the first input, the second input, and the predicted task to e) the treatment plan optimizer computer model; and
7c) instructing, by a1) the processor, e) the treatment plan optimizer computer model to generate the treatment plan for the patient using the first input, the second input, and the predicted task.
Claim 1 recites, in part, performing the steps of 1) presenting a user interface providing an interaction interface (when a piece of paper) between a plurality of medical professionals communicating regarding a radiation therapy treatment of a patient during a tumor board meeting or a radiotherapy treatment planning process, 2) receiving, through the interaction interface, a first input comprising a first patient attribute of the patient and a second input corresponding to the radiation therapy treatment of the patient, 3) generating a prompt containing the first patient attribute of the patient and the radiation therapy treatment of the patient in a text format according to a prompt template stored in memory (mental storage of information on a piece of paper) identifying locations corresponding to data types within the prompt, a first data type of the first input, and a second data type of the second input, 5) presenting the text string of characters identifying the predicted task for the treatment plan on the interaction interface, 6) receiving, from the interaction interface, a third input containing text identifying an input task, and 7) when the text of the third input does not match the text of the predicted task: 7a) presenting, on the interaction interface, an indication of the predicted task and an indication of a difference between the input task and the predicted task, 7b) responsive to receiving, from the interaction interface, an indication accepting the predicted task, transmitting the first input, the second input and the predicted task to the treatment plan optimizer model, and 7c) instructing the treatment plan optimizer model to generate the treatment plan for the patient using the first input, the second input, and the predicted task. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claims describe a process of determining the appropriate steps to treat a patient undergoing radiation therapy treatment, where an incorrect step is addressed.
The above limitations will be considered as a single abstract idea going forward. Independent claims 8 and 15 recite similar limitations and are also directed to an abstract idea under the same analysis.
Depending claims 2-3, 5-7, 9-10, 12-14, 16-17, and 19-23 include all of the limitations of claims 1, 8, and 15, and therefore likewise incorporate the above described abstract idea. Depending claims 6, 13, and 20 add steps involving retraining an LLM which is an extension of the LLM which is an extension of the d) large language model. Depending claims 2, 5, 7, 9, 12, 14, 16, 19, 21-23 add additional, functional steps to the claims. Additionally, the limitations of depending claims 3, 10, and 17 further specify elements from the claims from which they depend on without adding any additional steps. These additional limitations only further serve to limit the abstract idea. Thus, depending claims 2-3, 5-7, 9-10, 12-14, 16-17, and 19-23 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 8, and 15 (Step 2A (Prong One): YES).
Prong Two:
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of – using a) a server (from claims 8 and 15) comprising a1) a processor (from claims 1, 8, and 15) and a2) a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform functions (from claim 15), b) a user interface providing an interaction interface (when a computer display), c) memory, d) a large language model, e) a treatment plan optimizer computer model, and f) a computer configured to display a user interface (from claim 15) to perform the claimed steps.
The claims also include the additional element step of 4) “executing a large language model using the generated prompt to generate a text string of characters identifying a predicted task to be completed prior to generating a treatment plan for the patient generated using a treatment plan optimizer model, wherein the large language model is trained using text of a set of transcriptions of a set of tumor board meetings or radiotherapy treatment planning processes for a set of previously implemented radiation therapy treatments and a hierarchy of tasks associated with generating treatment plans”.
The a) server comprising a1) a processor and a2) a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform functions, b) user interface providing an interaction interface, c) memory, e) treatment plan optimizer computer model, and f) computer configured to display a user interface in these steps are recited at a high-level of generality (i.e., as generic components performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using generic computer components, see MPEP 2106.05(f).
The d) large language model processing model and the additional element step of 4) “executing a large language model using the generated prompt to generate a text string of characters identifying a predicted task to be completed prior to generating a treatment plan for the patient generated using a treatment plan optimizer model, wherein the large language model is trained using text of a set of transcriptions of a set of tumor board meetings or radiotherapy treatment planning processes for a set of previously implemented radiation therapy treatments and a hierarchy of tasks associated with generating treatment plans” in these steps are recited at a high-level of generality (i.e., as generic components performing generic computer functions) such that it amount to no more than mere instructions to apply the exception using generic computer components (see: Applicant’s specification, paragraph [0006] where there is a generic processing model, see MPEP 2106.05(f)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. 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 and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea (Step 2A (Prong Two): NO).
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a) a server comprising a1) a processor and a2) a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform functions, b) a user interface providing an interaction interface, c) memory, d) a large language model, e) a treatment plan optimizer computer model, and f) a computer configured to display a user interface to perform the claimed steps and the additional element step of 4) “executing a model using the generated prompt to generate a text string of characters identifying a predicted task to be completed prior to generating a treatment plan for the patient generated using a treatment plan optimizer model, wherein the model is trained using text of a set of transcriptions of a set of tumor board meetings or radiotherapy treatment planning processes for a set of previously implemented radiation therapy treatments and a hierarchy of tasks associated with generating treatment plans” amounts to no more than insignificant extra-solution activity in the form of WURC activity (well-understood, routine, and conventional activity), a general linking to a particular technological field, or mere instructions to apply the exception using a generic computer component that does not offer “significantly more” than the abstract idea itself because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of any computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. It should be noted that the claims do not include additional elements that amount to significantly more than the judicial exception because the Specification recites mere generic computer components, as discussed above that are being used to apply certain mental steps, certain method steps of organizing human activity, or certain mathematical steps. Specifically, MPEP 2106.05(f) recites that the following limitations are not significantly more:
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)).
The current invention generates a predicted task using a) a server comprising a1) a processor and a2) a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform functions, b) a user interface providing an interaction interface, c) memory, d) a large language model, e) a treatment plan optimizer computer model, f) a computer configured to display a user interface, and step of 4) “executing a model using the generated prompt to generate a text string of characters identifying a predicted task to be completed prior to generating a treatment plan for the patient generated using a treatment plan optimizer model, wherein the model is trained using text of a set of transcriptions of a set of tumor board meetings or radiotherapy treatment planning processes for a set of previously implemented radiation therapy treatments and a hierarchy of tasks associated with generating treatment plans”, thus these components are adding the words “apply it” with mere instructions to implement the abstract idea on a computer.
Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible (Step 2B: NO).
Claims 1-3, 5-10, 12-17, and 19-23 are therefore rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Steven G.S. Sanghera whose telephone number is (571)272-6873. The examiner can normally be reached M-F 7:30-5:00 (alternating Fri).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shahid Merchant can be reached on 571-270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684
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