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 .
DETAILED ACTION
Priority
Acknowledgment is made of applicant's claim for foreign priority based on a European application 22162137.8 filed on March 15, 2022.
DETAILED ACTION
Claims 1 - 15 are pending in the application.
The claims were subject to an Election/Restriction requirement filed on
09/05/2025 and claims 1 – 11 and 14 were elected on 09/22/2025.
Claims 12, 13 and 15 were non-elected claims and withdrawn by applicant.
Claim 1 is independent.
This action is Final based on the same 35 U.S.C. §103 prior art references that
were not necessitated by the applicant’s amendment; see MPEP §706.07(a).
Given the amended claims 7 and 11, the 35 U.S.C. §112(b) rejections are
rescinded.
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.
Claims 1 – 4, 6, 9, 10, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over European Patent document Furrer et al. (EP 3817003 A1), herein “Furrer,” in view of Denton (US PG Pub. No. 20080312893), herein “Denton.”
Regarding claim 1,
Furrer teaches a computer-implemented method of forecasting future laboratory performance of a laboratory system comprising a plurality of laboratory instruments configured to perform tests on laboratory test samples, a laboratory middleware programmed to operate the plurality of laboratory instruments, a control unit, a dashboard display, and a communication network communicatively connecting the plurality of laboratory instruments, the laboratory middleware, the control unit, and the dashboard display, the method comprising: (Par. 0013: “Embodiments herein disclosed address the need for an analytical laboratory respectively a method of operating an analytical laboratory which prevents overloading/underutilization of laboratory instruments by determining an effective flow rate of the laboratory instruments and dynamically reacting to the deviations of the effective flow rate by controlling the load limit of each instrument. Par. 0038 – “logic controller.” Par. 0008. Examiner’s Note – See Paxson that also teaches a display and acquisition hardware that allows control of an experiment in the laboratory; (Par. 0084).)
providing laboratory operator preferences and laboratory constraints obtained from a laboratory operator to an optimization module of the control unit; (Par. 0051: “As shown on figure 2, in a first preparatory step 100, a load limit is set for each laboratory instrument 10. The load limit is initially set at a value equal to a maximum instrument capacity of the respective laboratory instrument 10. According to embodiments disclosed herein, the maximum instrument capacity is set by a vendor; manufacturer; and/or operator, optionally considering a safety margin. The maximum instrument capacity as well as the load limit may be expressed as a number of biological samples a laboratory instrument 10 can process in a given time frame, such as samples per hour/day, etc. Achieving an effective processing rate of the laboratory instruments 10 as close as possible to the maximum instrument capacity is the goal of the optimization by the laboratory middleware 20.” See also Par. 0019 and 0073 that teaches performing load balancing between laboratory instruments.)
providing laboratory input data and laboratory test order data to the optimization module (middleware or analyzer) of the control unit; (The maximum instrument capacity as well as the load limit may be expressed as a number of biological samples a laboratory instrument 10 can process in a given time frame, such as samples per hour/day, etc. Achieving an effective processing rate of the laboratory instruments 1 0 as close as possible to the maximum instrument capacity is the goal of the optimization by the laboratory middleware 20.” Par. 0038: “The laboratory middleware may, for instance, be embodied as a programmable logic controller running a computer-readable program provided with instructions to perform operations.” Par. 0038: “The term 'laboratory middleware' as used herein encompasses any physical or virtual processing device configurable to control a laboratory instrument / or system comprising one or more laboratory instruments in a way that workflow(s) and workflow step(s) are conducted by the laboratory instrument / system. The laboratory middleware may, for example, instruct the laboratory instrument/system to conduct pre-analytical, post analytical and analytical workflow(s)/ workflow step(s).”)
optimizing laboratory configuration based on the laboratory operator preferences, laboratory constraints, laboratory inputs, and laboratory test order data at the optimization module of the control unit; (Par. 0051: “The maximum instrument capacity as well as the load limit may be expressed as a number of biological samples a laboratory instrument 10 can process in a given time frame, such as samples per hour/day, etc. Achieving an effective processing rate of the laboratory instruments 10 as close as possible to the maximum instrument capacity is the goal of the optimization by the laboratory middleware 20.” Par. 0073 and 0074 – Optimizing and load balancing of the laboratory and/or its instruments.)
Furrer does not teach simulating the different laboratory reactions or simulating the hardware or design. However, Denton does teach simulating future laboratory performance of the laboratory system by a simulation module of the control unit based on the optimized laboratory configuration provided by the optimization module and real-time laboratory inputs and laboratory test order data; (Par. 0014: “A portable simulation method and system is disclosed for evaluating laboratory testing and diagnostic systems, such as clinical diagnostic analyzers. The disclosed evaluation methods and devices are efficient and cost effective because their evaluation reflects actual expected usage and provides metrics tailored to aid in addressing cost or management issues.” See also Par. 0031 and 0047.)
monitoring actual laboratory performance; (Par. 0012: “Applicants recognized the need for evaluation of clinical diagnostic analyzers performance based on local needs. FIG. 6 and the illustrative graphs for two different sites shown in FIGS. 4A-B demonstrate the influence of multiple factors on the performance of a clinical analyzer in a particular place as well the considerable difference in the demands made on the instrument in different contexts.” Par. 0046: “…providing a measure of the performance of the clinical diagnostic analyzer (step 140 of FIG. 1B) in a report including, for pseudo-samples marked Routine or STAT, at least one member of the group consisting of a Maximum Turn Around Time, an Average Turn Around Time, a 95% Turn Around Time, a Maximum Throughput, Consumable Usage, a Walk-Away Time, and a Downtime. Advantageously, the method includes a report on the performance metrics including in the form of an Arrival and Exit Rate Graph. A graph of Cumulative and % Turn Around Times may also be provided.” Par. 0005.)
and displaying the simulated future laboratory performance and the monitored actual laboratory performance on the dashboard display to the laboratory operator. (Par. 0052: “Preferably, the simulation apparatus includes a users' interface to provide an output. The output, preferably, includes one or more of the Maximum Turn Around Time, the Average Turn Around Time, the 95% Turn Around Time, the Maximum Throughput, Consumable Usage, the Walk-Away Time, and the Downtime. Further, the output may further include an Arrival and Exit Rate Graph, illustrative example of which are presented in FIGS. 4A-B.” Par. 0010.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the computer implemented system and method that optimizes and/or load balances the laboratory middleware or instruments as in Furrer with simulation of laboratory or biological or chemical system and outputting the simulation results on a user interface as in Denton in order to provide realistic projections of expected use of laboratory testing and diagnostic system and deliver predictable financials by eliminating hidden costs, maintenance and productivity issues associated with alternative implementations. (Par. 0025)
Regarding claim 2,
The previously cited references teach the limitations of claim 1 which claim 2 depends. Furrer also teaches that the laboratory input data and order data is continuously provided by the laboratory middleware in real-time, wherein the real-time laboratory data comprises timing for masking of analyzers, reagent pack assignments and placements, sample loading scheduling, and/or combinations thereof. (Par. 0038: “The term 'laboratory middleware' as used herein encompasses any physical or virtual processing device configurable to control a laboratory instrument / or system comprising one or more laboratory instruments in a way that workflow(s) and workflow step(s) are conducted by the laboratory instrument / system. The laboratory middleware may, for example, instruct the laboratory instrument / system to conduct pre-analytical, post analytical and analytical workflow(s)/ workflow step(s). The laboratory middleware may receive information from a data management unit regarding which steps need to be performed with a certain sample. In some embodiments, the laboratory middleware might be integral with a data management unit, may be comprised by a server computer and/or be part of one laboratory instrument or even distributed across multiple instruments of the analytical laboratory. The laboratory middleware may, for instance, be embodied as a programmable logic controller running a computer-readable program provided with instructions to perform operations.” Par. 0041: “An 'analytical laboratory' as used herein comprises a laboratory middleware operatively coupled to one or more analytical; pre- and post-analytical laboratory instruments wherein the laboratory middleware is operable to control the instruments. In addition, the laboratory middleware may be operable to evaluate and/or process gathered analysis data, to control the loading, storing and/or unloading of samples to and/or from any one of the analyzers, to initialize an analysis or hardware or software operations of the analysis system used for preparing the samples, sample tubes or reagents for said analysis and the like. In particular, the instruments of an analytical laboratory and the laboratory middleware are interconnected by a communication network.”)
Regarding claim 3,
The previously cited references teach the limitations of claim 1 which claim 3 depends. Denton also teaches that the simulated future laboratory performance comprises predicting arrival of test results from the plurality of laboratory instruments. (Par. 0003: “…such components can be combined to provide customization and, naturally, this adds to the complexity in carrying out a simulation. Further, highly predictable performance of these systems is required because accuracy and time taken to provide test results may be critical.” See also Furrer Par. 0010.)
Regarding claim 4,
The previously cited references teach the limitations of claim 1 which claim 4 depends. Furrer also teaches simulated throughputs, turnaround times (TATs) of samples, times to results, buffer levels, sample traffic intensities, instrument loads and workload of laboratory operators, idle times, number of samples, reagents, or tests exceeding a performance acceptance criteria, point-to-point travel times, buffer wait times, walk-away times, number of laboratory operator interactions per time, number of laboratory operators needed, power consumption, water consumption, operational costs, or combinations thereof. (Furrer teaches turn-around time TAT of the respective biological samples in paragraph 0074, and this is one combination of the elements as described above for claim 4.)
Regarding claim 6,
The previously cited references teach the limitations of claim 1 which claim 6 depends. Denton also teaches that changing laboratory configuration of current laboratory via input from the laboratory operator based on the simulated future laboratory performance. (Par. 0016: “The results of the simulation include a Maximum Turn Around Time, an Average Turn Around Time, a 95% Turn Around Time, a Maximum Throughput, Consumable Usage, a Walk-Away Time, and a Downtime. These results allow customers to improve their estimates of resource and capital needs, modify the laboratory setup, adjust delivery schedules, or adding equipment to better meet their needs based on predictable financials while eliminating many of the hidden costs, maintenance and productivity issues. Some preferred embodiments are described below with the aid of illustrative figures, which are briefly described next.” Par. 0031: “The simulation is preferably based on data provided by the customer for a representative simulation. Such a simulation-based tool allows improved turn-around times, delivery schedules and rapid identification of desirable modifications to the laboratory setup.”)
Regarding claim 9,
The previously cited references teach the limitations of claim 1 which claim 9 depends. Furrer also teaches calculating sample loading effects on the simulated future laboratory performance, and reporting the calculated sample loading effects and/or optimizing laboratory configuration based the calculated sample loading effects. (Par. 0074: “The calculation/ estimation of the transportation time is based on data indicative of a layout of the sample transportation system 10TRS and/or data indicative of an effective transportation capacity/ availability of the sample transportation system 10TRS or a specific transportation route of the sample transportation system 10TRS from the first to the second laboratory instrument. Overall, in optimizing the processing of biological sample(s), the laboratory middleware 20 monitors and controls the load of the sample transportation system 10TRS similarly to other laboratory instruments 10, namely monitoring its effective flow rate and adjusting its load limit (in this case transportation capacity) to avoid overloading and/or underutilization of the sample transportation system 10TRS. In such a way, the overall turn-around-time TAT of the respective biological sample(s) can be significantly improved by ensuring the biological sample(s) are transported to the laboratory instruments 10 as efficiently as possible.” See also Abstract and full paragraph 0014.)
Regarding claim 10,
The previously cited references teach the limitations of claim 1 which claim 10 depends. Denton also teaches scheduling manual interactions with the laboratory system based on the optimized laboratory configuration. (Par. 0063: “Means for accessing a clinical diagnostic analyzer definition provide access to either a default clinical diagnostic analyzer definition or to a particular clinical diagnostic analyzer definition. In most instances, it is expected that such a definition includes timing details underlying Scheduler operations. Such means may be in the form of an electronic memory or be implemented as part of a user interface designed to accept a clinical diagnostic analyzer definition, including by specifying a memory location or data structure with the required information.”)
Regarding claim 14,
The previously cited references teach the limitations of claim 1 which claim 14 depends. Denton also teaches optimizing future laboratory performances of the different configurations based on laboratory operator preferences, laboratory constraints, real-time laboratory inputs, and order data at an optimization module. (Par. 0016: “These results allow customers to improve their estimates of resource and capital needs, modify the laboratory setup, adjust delivery schedules, or adding equipment to better meet their needs based on predictable financials while eliminating many of the hidden costs, maintenance and productivity issues. Some preferred embodiments are described below with the aid of illustrative figures, which are briefly described next.” Abstract and Par. 0014 and 0031.)
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over European Patent document Furrer in view of Denton in further view of Howell et al. (US PG Pub. No. 20160188769), herein “Howell.”
Regarding claim 5,
The previously cited references teach the limitations of claim 1 which claim 5 depends. They do not teach comparing simulated with actual lab information. However, that the displayed simulated future performance comprises indicators of benefits of simulated laboratory configuration compared to a current laboratory configuration. (Par. 0063: “For efficiency and avoidance of redundancy the operation to be performed may be saving a simulation result, and the condition may comprise a comparison between a current process variable simulation result and a previous process variable simulation result.” Par. 0291: “The user opens the tab in the simulator workflow manager that displays the workflow execution.” See also Par. 0213 and 0414 and claim 54.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the computer implemented system and method that optimizes and/or load balances the laboratory middleware or instruments as in Furrer with simulation of laboratory or biological or chemical system and outputting the simulation results on a user interface as in Denton with a system and method of comparing a simulated laboratory information with current results in the laboratory as in Howell in order to find efficiency and reliability of the processes of chemical and hydrocarbon refining. (Par. 0002)
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over European Patent document Furrer in view of Denton in further view of Bhattacharya et al. (US PG Pub. No. 20210241863), herein “Bhattacharya.”
Regarding claim 7,
The previously cited references teach the limitations of claim 1 which claim 7 depends. They do not teach an alert when an abnormality is detected. However, Bhattacharya does teach an alert when the simulated future laboratory performance and the monitored actual laboratory performance deviate from an acceptable level and/or simulated test samples arrivals and actual test samples arrivals deviate from an acceptable level and/or an abnormality is detected; and indicating on the dashboard display a potential source of the deviation or abnormality. (Par. 0209: “The simulation facility 110 of the platform 104 may, based on the space definitions from the configuration facility 106, evaluate the trial designs. The simulation facility 110 may include models 126. As used herein, a model includes the combination of parameters and the values that describe a design and the scenario under which the design is evaluated. Models 126 may include hundreds or even thousands of models. Models 126 may include deviation specifications for one or more of the parameters of the models. Deviation specification may define a range of values, a distribution of values, and/or a function of values for one or more parameters of a model. The deviation specifications may be based on expected or previously measured distributions or variations in design parameters.” Par. 0376: “In embodiments, interactive interfaces may include reporting and alert features.” Par. 0714: “In embodiments, the system and methods described herein may include alerts. The platform or components thereof may include components for generation and transmission of data messages to an end user (human or machine). Alerts may be generated for notifying an end user of analysis results, status of processes (such as simulation, analysis, configuration, and the like), errors (delays in processing, unavailability of platform or external resources, unauthorized access, and the like), time of completions of simulations and/or analysis, and the like. Alerts may be logged for system audit and used for predictions. Alerts may be pushed or pulled to user devices, such as mobile devices and may wake a device from a sleep or low power mode. Alerts may be provided to other platform elements which may be used as a trigger to initiate and/or abort other processes of the platform. For example, simulated annealing analysis may provide alerts when improved designs are observed. The alerts may be provided to a user and used to trigger an update of interfaces that display analyzed designs.” See also Par. 0533, 0557, 0558, 0639, and et al.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the computer implemented system and method that optimizes and/or load balances the laboratory middleware or instruments as in Furrer with simulation of laboratory or biological or chemical system and outputting the simulation results on a user interface as in Denton with simulating clinical trials and alerting a user when a simulation deviates from what actually occurs as in Bhattacharya in order to notify of analysis and process of the simulation which then can be used to trigger or abort other processes on the platform. (Par. 0714)
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over European Patent document Furrer in view of Denton in further view of Lancaster (US Patent No. 10,311,442), herein “Lancaster.”
Regarding claim 11,
The previously cited references teach the limitations of claim 1 which claim 11 depends. They do not teach estimating maintenance. However, Lancaster does teach displaying predicted upcoming events with an indication when these predicted upcoming events are expected to occur, wherein the predicted upcoming events are estimations of when refills are needed and/or estimations of the start time of maintenance events and/or estimations of the duration of maintenance events and/or predicting future laboratory maintenance events. (Abstract: “Systems and methods that provide for automation-assisted research into the workings of one or more studied systems include software modules that communicate with domain knowledge bases, research professionals, automated laboratories, research service objects,…” Col. 9, lines 42 – 49: “In order to remain competitive, many research tool manufacturers seek to continuously improve overall equipment and research effectiveness. To facilitate these improvements, the invention provides implementing computer-based applications to employ such techniques as research-robot equipment monitoring, fault detection and classification, run-to-run control, predictive and preventative maintenance, collection and analysis of data from research equipment…” See also Col. 1, lines 38 – 45.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined the computer implemented system and method that optimizes and/or load balances the laboratory middleware or instruments as in Furrer with simulation of laboratory or biological or chemical system and outputting the simulation results on a user interface as in Denton with simulating automated laboratories and to employ a technique to predict preventative maintenance as in Lancaster in order to provide improved research methodologies in the biotechnology and/or biomedical industry, and particularly to provide improved software and hardware systems for managing automated laboratories and automated research methodologies.” (Col. 6, lines 55 – 59)
Allowable Subject Matter
Claim 8 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Reasons for allowance will be held in abeyance pending final recitation of the claims. The prior art does not disclose the elements of claim 1 and the elements of: calculating estimated future orders based on laboratory test order data, simulated future laboratory performance, and/or monitored actual laboratory performance, and reporting the calculated estimated future orders and/or optimizing laboratory configuration based on the calculated future orders.
Response to Arguments
The examiner respectfully traverses applicant’s arguments. In the remarks, applicant argues that the prior art reference of Furrer do not describe or suggest any predictive aspects. Examiner respectfully disagrees with this argument. Furrer discloses only one element of predict[ion] in paragraph 0069 where a “derivative action predicts system behavior and thus improves settling time and stability of the system.” This paragraph teaches at least in part that some of the system is to predict behavior and improve performance of the laboratory and laboratory instruments. The substantive aspect of the Furrer is that the reference teaches preventative measures for the laboratory and the laboratory instruments. Preventative measures are deeply intertwined with predictive elements. Preventative actions as taught in Furrer are designed and prioritized based on predictive insights (the overloading and/or underutilization of labs and the laboratory instruments). These preventative and predictive insights are used to optimize the instruments of the laboratory using test data or middleware and/or an analyzer, on point with the instant application.
Applicant argues that “Furrer explicitly relies on a purely reactive approach, specifically completely devoid of any assumptions, predictive performance simulations, etc.” In support of this argument Applicant cites Furrer paragraph 0017 that states: “Furthermore, determining the effective flow rate by the laboratory middleware based on
the test order queries received from the laboratory instruments is advantageous as it is
devoid of any assumptions of performance and can be implemented even without any
change to the existing laboratory instruments.” Examiner is not is not persuaded by this argument. Paragraph 0038 states that the laboratory middleware encompasses any physical or virtual processing device… and receives “information from a data management unit regarding which steps need to be performed with a certain sample. Given this paragraph and others that teach preventative measures, Furrer clearly teaches a predictive and preventative element using middleware that controls the laboratory and the instruments. Furrer teaches a computer program that performs steps to prevent negative attributes of instruments (meaning the overloading and/or underutilization is being predicted as a problem to life-critical decisions.
Even if Furrer does not teach a simulating the laboratory, cited prior art of Denton does teach prediction by way of simulation as rejected above and paragraph 0022 specifically states: “…prediction of the configuration and type of clinical diagnostic analyzer by a preferred simulation.” Furrer teaches overloading and/or underutilization of laboratory instruments, and applicant argues that Denton teaches a completely different technical problem of “investment decisions", and estimating "predictable financials" and "cost of ownership". However, paragraph 0016 clearly teaches “modifying the laboratory setup” and several paragraphs of Denton teach evaluating laboratory testing and diagnostic systems. Supporting paragraph 0014 of Denton teaches” “A portable simulation method and system is disclosed for evaluating laboratory testing and diagnostic systems, such as clinical diagnostic analyzers. The disclosed evaluation methods and devices are efficient and cost effective because their evaluation reflects actual expected usage and provides metrics tailored to aid in addressing cost or management issues. The disclosed method and system rely on a simulation, which allows estimation of the performance of a clinical diagnostic analyzer or automation system at each specific customer site before actual deployment.” Clearly the simulation is being used for evaluating devices for the expected usage as stated in paragraph 0014. The paragraph does teach addressing costs, but as the final phrase relates to buying and installing equipment for the laboratory. Paragraph 0016 also supports utilization, laboratory setup, and equipment choices. This is directly related to the problem of the instant application and is combinable with Furrer for an obviousness type rejection. Thus the rejection is maintained and this is a final action. Examiner Note – See also Paxson et al. paragraphs 0009, 0010, 0028, and 0067 as cited below.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Paxson et al. (US PG Pub. No. 20070005317) may also teach the element of simulation of future laboratory performance. Paxson teaches at least a portion of simulating future laboratory performance of the laboratory system by a simulation module of the control unit based on the optimized laboratory configuration provided by the optimization module and real-time laboratory inputs and laboratory test order data; (Par. 0028: “Because the execution of one reaction can change the factors that influence the reaction time of other reactions, the simulator then recalculates and resorts the reaction time for reactions that change due to the execution of the most recently executed reaction. The simulator then executes the next reaction in the list, moving the simulation time forward to the reaction time of that reaction. This process is repeated many times as the system is simulated forward in time until a specified end time for the simulation is reached.” Par. 0030: “The simulation engine 120 receives models of chemical reactions or biological processes generated using the modeling environment 110. The simulation engine 120 communicates refinements to models created in the modeling environment 110. The analysis environment 130 is in communication with both the modeling environment 110 and the simulation engine 120. The analysis environment 130 may be used to perform various types of analysis directly on models created in the modeling environment 110. Also, the analysis environment 130 may receive and process results from the simulation engine 120 representing the execution by the simulation engine 120 of a model produced in the modeling environment. In other words, the simulation engine 120 generates the dynamic behavior of the model and communicates at least some of this dynamic behavior to the analysis environment. The analysis environment 130 may provide refinements to a model in the modeling environment 110 and may provide parameters for use by the simulation engine 120 when executing a model. The interaction between the modeling environment 110, the simulation engine 120, and the analysis environment 130 will be discussed in more detail below.” Par. 0009, 0010, and 0067 (simulation of hardware, software and design.)
monitoring actual laboratory performance; (Par. 0042: “…the particular probability distribution associated with a particular reaction may be derived from experimental data. For example a program may collect data from experiments and calculate a probability distribution, which is fed back to the model environment and associated with a model of that reaction.” Par. 0084: “…the data acquisition hardware allows the analysis tool to control an experiment that is in progress based on the results generated by the simulation engine 120.” See also Par. 0010 and 0083.)
and displaying the simulated future laboratory performance and the monitored actual laboratory performance on the dashboard display to the laboratory operator. (Par. 0083: “The analysis environment 130 may further process the results generated by the simulation engine 120 or it may display the results visually or auditorially. For example, the analysis environment 120 may use graph visualization techniques to identify to a user similar pathways. In some embodiments the analysis environment 130 interfaces with data acquisition hardware (not shown in FIG. 1) which allows the analysis environment 130 to compare the generated results with experimental data. In these embodiments, data gathered from an ongoing experiment is used to correct or generate a model of the reaction that is occurring in situ. In some embodiments the experiment is conducted on a microarray or a gene chip. For example, if the existence of a given protein is predicted by a model but data acquired from the experiment indicates that the protein does not exist, the analysis tool 130 may signal a user, either auditorially or visually, that the in situ experiment and the predicted response differ. For embodiments in which the experiment is conducted on a microarray, the gathered data may differ between microwells. In these embodiments, the analysis tool may average the value of the gathered data. In others of these embodiments, the analysis environment 130 may signal a difference if the data from a single microwell differs from the model's predicted response. In some embodiments, the amount of tolerable difference between the in situ experiment and the predicted result is user-configurable. In other embodiments, the analysis tool transmits the gathered data to the modeling environment 110 so that the model may be modified to account for the difference. In still other embodiments, the analysis environment 130 graphically displays the expected result of the experiment and data gathered from the experiment.” See also Abstract, Par. 0027, and 0053.)
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHAD G ERDMAN whose telephone number is (571)270-0177. The examiner can normally be reached Mon - Fri 7am - 3pm or 4pm EST..
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth Lo can be reached at (571) 272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHAD G ERDMAN/Primary Examiner, Art Unit 2116
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