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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
1. Claims 1-2 and 9 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “produces a verification result”, “outputs feedback information” and “outputs preparation process information”; However, it is not clear which “module” is responsible for these tasks. Examiner notes that all limitations are separated by a semicolon and does not rely on any commas.
Claim 2 recites “performs the image recognition based on” - the preparation action image
the drug image … the syringe marking image … the mixed-drug image. Where the first recitation of “performs the” introduces performing and the rest of the recitations should instead read “performs image recognition based on”
Claim 9 recites “wherein the step of detecting”, which is provided in the singular form “step”, and “; or outputting”, which is in the disjunctive “or” where only one of the previous features in the list of features needs to be present for the feature to be satisfied.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
2. Claims 1, 4, and 6-7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by “DrugCam -An intelligent video camera system to make safe cytotoxic drug preparations” by Frederic Benizri et al., (herein after “Benizri”).
Regarding claim 1, as best understood, A system for verifying chemotherapy medication preparation (Benizri, §Abstract: “DrugCam1 is a new approach to control the chemotherapy preparations with an intelligent video system that enables automatic verification during the critical stages of preparations combined with an a posteriori control with partial or total visualization of the video recording of preparations.”), comprising: an image sensing module for capturing image information of a chemotherapy medication preparation process (Benizri, Fig. 4, where the DrugCam system contains multiple parts and subparts connected and in communication with one another, where the image sensing module is the camera used to capture the images and video.);
an image recognition module in signal connection with the image sensing module, wherein the image recognition module performs image recognition based on the image information and produces a corresponding identification result (Benizri, Fig. 4, “Barcode reading of preparation label” discloses an image recognition model that recognizes barcodes, see captured barcodes in Fig. 3., which are identified and validated against the “Validation of Fabrication sheet” shown in Fig. 4.); and
a computation and processing module in signal connection with the image recognition module, wherein the computation and processing module performs computation and comparison based on the identification result (Benizri, Fig. 4, “DrugCam control Modul” discloses a computation and processing module connected with the image recognition model, where within the validation, comparison is performed based on the identification result from the barcode reading.);
produces a verification result (Benizri, Fig. 4, “Validation of preparation’s conformity”);
outputs feedback information when the verification result indicates a mismatch, in order for the image information to be recaptured and re-subjected to the image recognition until the verification result indicates a match (Benizri, Fig. 4, “Partial or total vizualisation of preparation (steps identified by Assist Alert or not)”); and
outputs preparation process information when the verification result indicates a match (Benizri, Fig. 4, “Validation of preparation’s conformity” is output for “Pharmaceutical release”).
Regarding claim 4, further comprising a database in signal connection with the computation and processing module, wherein the database stores the preparation process information, where the database must store preparation process information for validation to occur, as shown by Benizri in Fig. 4, “DrugCam Control Modul” in signal connection with “CPOE system of chemotherapy process”.
Regarding claim 6, wherein the image sensing module (camera provided by Benizri) captures barcode information of a prescription sheet (Benizri, Fig. 4, “Prescription”, and Fig. 3 shows the associated barcode.), the image recognition module performs the image recognition based on the barcode information and thereby obtains corresponding prescription information (Benizri, Fig. 4, “DrugCam Assist Modul”), and the computation and processing module performs evaluation based on the prescription information and produces an evaluation result, wherein when the evaluation result indicates a match (Benizri, Fig. 4, “DrugCam Control Modul”), the image sensing module starts to capture the image information of the chemotherapy medication preparation process, and when the evaluation result indicates a mismatch, remark information is output, and the chemotherapy medication preparation process is stopped (Benizri, §2.1, P[01]: “Critical steps of preparations are checked in real time allowing a digitalized visual double control. The system is composed of cameras positioned outside the work area (Fig. 1) allowing for two complementary actions: recognition of the objects used during preparation (labels, vials and syringes), and the complete video recording of the process. The device uses two IT modules: - The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn)”).
Regarding claim 7, further comprising an alert module in signal connection with the computation and processing module (Benizri, Fig. 4, “Partial or total vizualisation of preparation (steps identified by Assist Alert or not)”), wherein the alert module outputs and displays alert information when the verification result or the evaluation result indicates a mismatch (Benizri, §2.1, P[01]: “Critical steps of preparations are checked in real time allowing a digitalized visual double control. The system is composed of cameras positioned outside the work area (Fig. 1) allowing for two complementary actions: recognition of the objects used during preparation (labels, vials and syringes), and the complete video recording of the process. The device uses two IT modules: - The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn)”).
Claim Rejections - 35 USC § 103
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.
3. Claims 2-3 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Benizri in view of “Comparison of BD Pyxis IV Prep and Epic Dispense Prep with Gravimetric Checking for Production of Hazardous Compounded Sterile Preparations at a Cancer Care Center” by Danielle Alvarez, (herein after “Alvarez”).
Regarding claim 8, A method for verifying chemotherapy medication preparation (Benizri, §Abstract: “DrugCam1 is a new approach to control the chemotherapy preparations with an intelligent video system that enables automatic verification during the critical stages of preparations combined with an a posteriori control with partial or total visualization of the video recording of preparations.”), comprising the steps of:
detecting a preparation action (where the action is reading the barcode, Benizri, §Abstract: “In addition to the vial detection model, barcodes can also read when they are present on vials.”, and is shown to be detected in Fig. 2 which shows the barcode, and verification is completed for all critical stages of preparations, which includes having the appropriate bar code.;
capturing and identifying a preparation action image corresponding to the preparation action, and producing a preparation action identification result (Benizri, Fig. 2, shows the barcodes as the preparation action images.);
comparing the preparation action identification result against predetermined preparation action information, and producing a preparation action comparison result (Benizri, Fig. 2, shows the barcodes as the preparation action images, which are analyzed and compared to predetermined information, which for example is the operator re-reading the label to affirm its correctness, or comparing the imaged label information to the “Validation of Fabrication sheet”, as shown in Fig. 4.);
outputting first feedback information when the preparation action comparison result indicates a mismatch, in order to recapture and re-identify the preparation action image until the preparation action comparison result indicates a match (Benizri, §2.1, P[01]: “Critical steps of preparations are checked in real time allowing a digitalized visual double control. The system is composed of cameras positioned outside the work area (Fig. 1) allowing for two complementary actions: recognition of the objects used during preparation (labels, vials and syringes), and the complete video recording of the process. The device uses two IT modules: - The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn) (Figs. 2 and 3). - The “Control” module, accessible via a web platform, allows the conformity of the pharmacist’s preparation to be validated remotely a posteriori. This module enables the video of the preparation to be totally or partially visualized via key moments recognized by the “Assist” module.”), and detecting a drug grabbing action when the preparation action comparison result indicates a match, where the drug grabbing action occurs directly after the barcode is verified and Benizri discloses detecting grabbing of the vials in §2.1, P[01]: “The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn)”.;
capturing and identifying a drug image corresponding to the drug grabbing action, and producing a drug identification result (Benizri, §2.1, P[01]: “The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn)”);
comparing the drug identification result against predetermined drug information, and producing a drug comparison result (Benizri, §2.1, P[01]: “The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn)”, where for an alert to be triggered for an error occurring concerning a particular vial, for example, grabbing the incorrect drug, the information in association with the vial must be compared to predetermined information for the error, and therefore the alert to occur.);
outputting second feedback information when the drug comparison result indicates a mismatch, in order to recapture and re-identify the drug image until the drug comparison result indicates a match (Benizri, §2.1, P[01]: “Critical steps of preparations are checked in real time allowing a digitalized visual double control. The system is composed of cameras positioned outside the work area (Fig. 1) allowing for two complementary actions: recognition of the objects used during preparation (labels, vials and syringes), and the complete video recording of the process. The device uses two IT modules: - The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn) (Figs. 2 and 3). - The “Control” module, accessible via a web platform, allows the conformity of the pharmacist’s preparation to be validated remotely a posteriori. This module enables the video of the preparation to be totally or partially visualized via key moments recognized by the “Assist” module.”), and detecting a syringe-based drawing action when the drug comparison result indicates a match, where after the drug vial is verified to be the correct vial via the imaging system, the operator/robot draws the drug from the vial with a syringe, (Benizri, §2.1, P[01]: “The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn)”;
capturing and identifying a syringe marking image corresponding to the syringe-based drawing action, and producing a dose identification result (Benizri, Fig. 3);
comparing the dose identification result against predetermined dose information, and producing a dose comparison result (Benizri, Fig. 3);
outputting third feedback information when the dose comparison result indicates a mismatch, in order to recapture and re-identify the syringe marking image until the dose comparison result indicates a match (Benizri, §2.1, P[01]: “Critical steps of preparations are checked in real time allowing a digitalized visual double control. The system is composed of cameras positioned outside the work area (Fig. 1) allowing for two complementary actions: recognition of the objects used during preparation (labels, vials and syringes), and the complete video recording of the process. The device uses two IT modules: - The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn) (Figs. 2 and 3). - The “Control” module, accessible via a web platform, allows the conformity of the pharmacist’s preparation to be validated remotely a posteriori. This module enables the video of the preparation to be totally or partially visualized via key moments recognized by the “Assist” module.”), and detecting an action of (dose provided by information in Fig. 3);
Benizri provides disclosure for the process of taking video and images of a station for drug preparation where all critical aspects and actions of the process are monitored and verified against known values, where the video segments/images pertaining to the critical aspects of the drug preparation processing show actions that are detection for the verification process; However, Benizri does not disclose this processing for specifically “of mixing drugs”. That is, Benizri does not explicitly disclose and detecting an action of mixing drugs used to form a pharmaceutical preparation, when the dose comparison result indicates a match;
However, Alvarez discloses utilizing BD PyXis IV Prep and Epic Dispense Prep which include the observation of mixing chemotherapy medication as shown in Table 3, and further in Appendix A, that is, the combination of Benizri and Alvarez disclose detecting an action of mixing drugs used to form a pharmaceutical preparation, when the dose comparison result indicates a match.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Benizri to include monitoring all actions taken while processing chemotherapy medication, as taught by Alvarez, to arrive at the claimed invention discussed above. Such a modification is the result of combining prior art elements according to known methods to yield predictable results. It is predictable that the proposed modification would have provided the benefit of reducing errors in final mixtures of chemotherapy medication.
capturing and identifying a mixed-drug image corresponding to the action of mixing drugs, and producing a mixed-drug identification result, where Benizri provides capturing and processing images and video of the critical aspects of the drug preparation process which includes mixing (Benizri, §Abstract: “DrugCam1 is a new approach to control the chemotherapy preparations with an intelligent video system that enables automatic verification during the critical stages of preparations combined with an a posteriori control with partial or total visualization of the video recording of preparations.”), and the identification through a verification process capable providing alerts, where mixing is provided by Alvarez in Table 3 and Appendix A.;
comparing the mixed-drug identification result against predetermined mixed-drug information, and producing a mixed-drug comparison result, where Benizri provides the verification processing through comparison of known values and Alvarez provides mixed drug information.; and
outputting fourth feedback information when the mixed-drug comparison result indicates a mismatch, in order to recapture and re-identify the mixed-drug image until the mixed-drug comparison result indicates a match (Benizri, §2.1, P[01]: “Critical steps of preparations are checked in real time allowing a digitalized visual double control. The system is composed of cameras positioned outside the work area (Fig. 1) allowing for two complementary actions: recognition of the objects used during preparation (labels, vials and syringes), and the complete video recording of the process. The device uses two IT modules: - The “Assist” module, visible by the operator via a close-up screen. This allows the operator to be monitored in real time and alerted in the event of an error occurring (vial and/or volume drawn) (Figs. 2 and 3). - The “Control” module, accessible via a web platform, allows the conformity of the pharmacist’s preparation to be validated remotely a posteriori. This module enables the video of the preparation to be totally or partially visualized via key moments recognized by the “Assist” module.”), and outputting preparation process information when the mixed-drug (where the mixed drug is provided by Alvarez) comparison result indicates a match (Benizri, Fig. 4, output for “Validation of preparion’s conformity”.).
Regarding claim 9, as best understood, wherein the step of detecting a preparation action comprises: capturing barcode information of a prescription sheet to obtain corresponding prescription information (where the action is reading the barcode, Benizri, §Abstract: “In addition to the vial detection model, barcodes can also read when they are present on vials.”, and is shown to be detected in Fig. 2) ; comparing the prescription information against predetermined medication information; producing an evaluation result as to whether or not the prescription information matches the predetermined medication information; and detecting a preparation action when the evaluation result indicates a match; or outputting remark information and suspending a subsequent process of the chemotherapy medication preparation, when the evaluation result indicates a mismatch.
Regarding claim 10, wherein after the preparation process information is output in response to the mixed-drug comparison result indicating a match, the preparation process information is transmitted to and stored in a database (Benizri, Fig. 4, the CPOE system stores the “Validation of preparation’s conformity” sent from “DrugCam” for pharmaceutical release), and notification information is output to prompt a user to pick up the mixed drug prepared (Benizri, Fig. 4, “Distribution”).
Regarding claim 2, as best understood, wherein the image information comprises a preparation action image (Benizri, Fig.3-4, images of barcodes from scanning action), a drug image (Benizri, Fig.3), a syringe marking image (Benizri, Fig.4), and a mixed-drug image (where Benizri provides the monitoring environment for taking videos and images of the production process for purposes of validation that provides hard-stops in case of error, and Alvarez provides the monitoring of the mixing of chemotherapy medication utilizing BD PyXis IV Prep and Epic Dispense Prep, which in combination provides an image of the mixed drug), and the image recognition module (Benizri, Fig. 4, DrugCam Assist Modul) performs the image recognition based on the preparation action image and produces a preparation action identification result (Benizri, Fig. 2, the barcode imaged provides information for the drug.), performs the image recognition based on the drug image and produces a drug identification result (Benizri, Fig. 2, shows the image of the drug and identification result), performs the image recognition based on the syringe marking image and produces a dose identification result (Benizri, Fig. 2, shows the image of the syringe and dosage.), and performs the image recognition (where the image recognition is provided by the DrugCam Assist Modul disclosed by Benizri in Fig. 4, where all critical aspects of the procedure are monitored, including the mixing provided by Alvarez in Table 3.) based on the mixed-drug image and produces a mixed-drug identification result (where Benizri provides the imaging and analysis of the mixed drug for identification in the same way as shown in Fig. 2-3, and the preparation processing for producing a mixed drug for chemotherapy is provided by Alvarez in Table 3.).
Regarding claim 3, wherein the computation and processing module compares the preparation action identification result against predetermined preparation action information and produces a preparation action comparison result, compares the drug identification result against predetermined drug information and produces a drug comparison result, compares the dose identification result against predetermined dose information and produces a dose comparison result, and compares the mixed-drug identification result against predetermined mixed-drug information and produces a mixed-drug comparison result where the “DrugCam Assist Modul” provided by Benziri in Fig. 4 is responsible for monitoring and validating all critical aspects included in processing the mixed drug as disclosed in the §Abstract: “DrugCam is a new approach to control the chemotherapy preparations with an intelligent video system that enables automatic verification during the critical stages of preparations combined with an a posteriori control with partial or total visualization of the video recording of preparations.”, where validation requires the comparison of a measured value to a known value, and where the process of observing the mixing of the drugs is provided by Alvarez in Table 3.
4. Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Benizri and Alvarez in view of “Introducing Augmented Reality Technique to Enhance the Preparation Circuit of Injectable Chemotherapy Drugs” by Sarah Othman et al., (herein after “Othman”).
Regarding claim 5, further comprising a display unit in signal connection with the computation and processing module, wherein the display unit displays the image information, the identification result, the verification result, and the feedback information (Benizri, Fig. 2-3 discloses the display unit for displaying image information for identification and verification along with feedback in case of error.), and the display unit is selected (selected by the user in Benizri of Fig. 2-3) from The combination of Benizri and Alvarez does not explicitly disclose utilizing smart glasses. However, Othman discloses the utilization of smart glasses for aiding in the preparation of chemotherapy drugs in Fig. 1: “Smart Prep Architecture”.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Benizri and Alvarez to incorporate smart glasses for chemotherapy drug preparation, as taught by Othman, to arrive at the claimed invention discussed above. Such a modification is the result of combining prior art elements according to known methods to yield predictable results. It is predictable that the proposed modification would have provided the benefit of improving traceability of the preparation steps.
Conclusion
5. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TY M BEATTY whose telephone number is (703)756-5370. The examiner can normally be reached Mon-Fri: 8AM-4PM EST..
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/TY MITCHELL BEATTY/Examiner, Art Unit 2663
/GREGORY A MORSE/Supervisory Patent Examiner, Art Unit 2698
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