Techniques for evaluating performance of analytical instruments

Abstract

Techniques and apparatuses for evaluating analytical device performance and data quality are described. In one implementation, for example, an apparatus can include at least one memory and logic coupled to the at least one memory. The logic can be configured to generate an analytical method to be performed by an analytical device, the analytical method including a plurality of method segments, the plurality of method segments including at least one performance evaluation procedure and at least one sample analysis procedure, and associate the at least one performance evaluation procedure with the at least one sample analysis procedure. Other implementations are described.

Description

[0001] Cross-references to related applications This application is a divisional application of application number 201980079981.4, entitled "Technique for Evaluating the Performance of Analytical Instruments". This application claims the benefit and priority of U.S. Provisional Patent Application No. 62 / 770,426, filed November 21, 2018, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The implementation scheme described in this paper relates to the management of analytical instruments as a whole, and more specifically to methods for evaluating the quality of data generated by analytical instruments. Background Technology

[0003] Analytical instrument performance is continuously monitored to ensure data quality. For example, operators may perform various maintenance procedures, system calibrations, and / or quality control checks to attempt to achieve proper system operation. Mass spectrometry (MS) and / or liquid chromatography-mass spectrometry (LC-MS) analytical systems can provide detailed characterization of complex sample sets, including biological matrices, food and environmental (F&E) materials, drug compounds, metabolic pathway analysis, and more. However, the ability to perform analyses to obtain accurate and detailed analytical data (including at low concentrations) makes MS and LC-MS systems susceptible to operational instability and data quality issues, especially during long-duration analytical runs.

[0004] In conventional MS and LC-MS systems, quality control measures, such as system suitability testing, are typically performed before initiating the sample analysis process to ensure proper operation of the analytical apparatus. Therefore, such measures may fail to detect problems that occur during subsequent executions of the sample analysis method. During sample analysis, additional quality control measures can be used to calibrate and / or measure the analytical apparatus response for known compounds. Often, the entire sample run is completed before the operator recognizes that the quality control results and the integrity of the data are questionable for failed quality control tests. Therefore, validation of the analytical apparatus's data quality can benefit from a dynamic evaluation process capable of providing meaningful data quality metrics throughout multiple configurable phases of the sample analysis method. Summary of the Invention

[0005] According to various aspects of the embodiments described, there is an apparatus that may include at least one memory and logic coupled to the at least one memory. The logic may be configured to generate an analysis method to be executed by an analysis device, the analysis method including multiple method segments, the multiple method segments including at least one performance evaluation process and at least one sample analysis process, and associating the at least one performance evaluation process with the at least one sample analysis process.

[0006] In some embodiments of the device, at least one analytical instrument may include at least one of a liquid chromatography (LC) system, a gas chromatography (GC) system, a mass analyzer system, a mass spectrometer (MS) system, an ion mobility spectrometer (IMS) system, a high-performance liquid chromatography (HPLC) system, an ultra-high-performance liquid chromatography (UPLC) system, an ultra-high-performance liquid chromatography (UHPLC) system, or any combination thereof. In exemplary embodiments of the device, the analytical equipment may include one of an MS system or an LC-MS system. In various embodiments of the device, at least one sample analysis procedure may include sample injection. In some embodiments of the device, at least one performance evaluation procedure may include system suitability testing.

[0007] In various embodiments of the device, the analysis method may include multiple paths. In an exemplary embodiment of the device, logic may determine one of the multiple paths for the analysis device to execute based on the results of at least one performance evaluation process.

[0008] In exemplary embodiments of the apparatus, logic may cause an anomalous event in response to at least one performance evaluation process exceeding a threshold. In various embodiments of the apparatus, logic may prevent the generation or access to data associated with the anomalous event in at least one sample analysis process. In exemplary embodiments of the apparatus, logic may cause the analysis device to enter a failure state in response to an anomalous event being a critical-level anomalous event. In various embodiments of the apparatus, logic may continue execution of the method and prevent the generation or access to data associated with the anomalous event in at least one sample analysis process in response to an anomalous event being a non-critical-level anomalous event. In some embodiments of the apparatus, logic may rerun at least one performance evaluation process associated with the anomalous event in response to an anomalous event being a non-critical-level anomalous event.

[0009] According to various aspects of the embodiments described, there is a method that may include generating an analysis method to be performed by an analysis device, the analysis method comprising a plurality of method segments, the plurality of method segments including at least one performance evaluation process and at least one sample analysis process, and associating the at least one performance evaluation process with the at least one sample analysis process.

[0010] In some embodiments of the method, at least one analytical instrument may include at least one of an LC system, GC system, mass analyzer system, MS system, IMS system, HPLC system, UPLC system, UHPLC system, or any combination thereof. In exemplary embodiments of the method, the analytical device may include one of an MS system or an LC-MS system. In various embodiments of the method, at least one sample analysis procedure may include sample injection. In some embodiments of the method, at least one performance evaluation procedure may include system suitability testing.

[0011] In some embodiments of the method, the analysis method may include multiple paths. In some embodiments, the method may include determining one of multiple paths for the analysis device to execute based on the results of at least one performance evaluation process.

[0012] In various embodiments, the method may include causing an anomalous event in response to at least one performance evaluation process exceeding a threshold. In some embodiments, the method may include preventing the generation or access to data associated with the anomalous event in at least one sample analysis process. In various embodiments, the method may include causing the analysis device to enter a failure state in response to the anomalous event being a critical-level anomalous event. In an exemplary embodiment, the method may include continuing to execute the method and preventing the generation or access to data associated with the anomalous event in at least one sample analysis process in response to the anomalous event being a non-critical-level anomalous event. In various embodiments, the method may include rerunning at least one performance evaluation process associated with the anomalous event in response to the anomalous event being a non-critical-level anomalous event. Attached Figure Description

[0013] Figure 1 An implementation scheme for the first operating environment is shown.

[0014] Figure 2 An implementation scheme for the second operating environment is shown.

[0015] Figure 3 An implementation scheme for the first logical flow is shown.

[0016] Figure 4 An implementation scheme for the second logical flow is shown.

[0017] Figure 5 An implementation scheme for the third logical flow is shown.

[0018] Figures 6A to 6C An exemplary screen image from an analytics service application, according to some implementation schemes, is depicted.

[0019] Figure 7 An implementation scheme for the computing architecture is shown. Detailed Implementation

[0020] Various implementations may collectively involve systems, methods, and / or apparatus for determining the data quality of an analytical instrument. In some implementations, a dynamic data quality assessment process is operable to process each sample (e.g., an analytical sample or a quality control sample) in real-time or substantially real-time and determine whether the sample is within expected limits. In various implementations, if a sample is not within expected limits, an anomalous event may be triggered. In exemplary implementations, the analytical method may be paused, canceled, aborted, stopped, or otherwise modified in response to an anomalous event. For example, an anomalous event may cause the analytical device to enter a failure state and suspend the analytical method performed via the analytical instrument. The analytical device (e.g., via a controller, control logic, software, etc.) and / or the operator may assess the anomalous event and determine the cause of the action, such as continuing the analytical method, rerunning all or part of the analytical method (e.g., a failed quality control (QC) sample), modifying the analytical method (e.g., continuing at a different concentration range, continuing down a different method path), etc. In some implementations, anomalous events can be classified as "critical-level anomalies" (e.g., system-level failures indicating that the analytical instrument is not working correctly or is otherwise unsuitable for performing the method) or "non-critical-level anomalies" (e.g., failures being processed or other functions not indicating poor quality data).

[0021] In various implementations, the data quality assessment process may be or may include one or more performance assessment processes, including but not limited to QC checks, calibration, analytical equipment validation, analytical equipment qualification, method validation, method qualification, system suitability testing, and / or combinations thereof. In some implementations, one or more performance assessment processes may be included within one or more segments of an analytical method. For example, in various implementations, an operator may select an analytical method and / or create an analytical method using a method editor. During one or more method segments, an analytical method may be created or modified to include various sample analysis processes, performance assessment processes, and / or portions thereof. For example, in some implementations, the analytical equipment may be or may include a mass spectrometer (MS). An analytical method according to some implementations, having sample analysis processes (e.g., sample injection) and performance assessment processes, may be performed using an MS, such that each injection is performed immediately after acquisition. In various implementations, if an injection exceeds specifications, operation may be paused, and the operator and / or analytical equipment may make decisions to continue, rerun the injection, modify the operation, etc. Implementations are not limited to this context.

[0022] In various implementations, the performance evaluation process may be or may include system suitability testing, such as for analytical devices or systems. Non-limiting examples of analytical devices or systems may include liquid chromatography (LC) systems, gas chromatography (GC) systems, mass analyzer systems, mass detector systems, mass spectrometry (MS) systems, ion mobility spectrometry (IMS) systems, high-performance liquid chromatography (HPLC) systems, ultra-high-performance liquid chromatography (UPLC) systems, ultra-high-performance liquid chromatography (UHPLC) systems, ultraviolet (UV) detectors, visible light detectors, solid-phase extraction systems, sample preparation systems, capillary electrophoresis instruments, combinations thereof, components thereof, variants thereof, etc. Although LC, MS, and LC-MS are used in the examples described herein, implementations are not limited thereto, as other analytical instruments capable of operating according to some implementations are contemplated herein.

[0023] Generally, system suitability testing aims to verify the correct functionality of analytical equipment in generating analytical measurement results. For example, system suitability testing of an LC-MS system can be operated to ensure that functional aspects of the LC-MS system (such as instrument components, chemical processes, software, etc.) function correctly to ensure accurate results. MS and / or LC-MS system suitability testing may include a variety of individual tests and / or parameters, including but not limited to peak characteristics, peak shape quantification, column retention, inter-peak resolution, calculations between injections to verify accuracy, peak area statistics over multiple injections, intensity, sensitivity, signal stability, residue, combinations thereof, and their variants.

[0024] Some implementations may provide testing of the analytical device at the method level. For example, in MS and / or LC-MS systems, implementations may define which injections are aligned with which tests. In various implementations, performance evaluation processes (e.g., system suitability testing) may be defined at the method level to provide pass / fail assessments. In various implementations, if a performance evaluation process fails and the analytical device enters a failure state, the analytical device (e.g., the software operating the analytical device) may be prevented from generating and / or providing data associated with sample analysis. Thus, sample data associated with the failed performance evaluation process (“failure-state sample data”) may not be generated and / or become inaccessible. In various implementations, failure-state sample data may remain in a “raw” or unprocessed state that may not be easily accessible to the operator (e.g., not converted into an operator-readable state, such as a chromatogram or spectrum). In other implementations, failure-state sample data may be “locked” or otherwise made inaccessible (e.g., within a secure data storage location, requiring a password or other authorization to access). In exemplary implementations, failure-state sample data may be generated and / or made accessible in response to certain events (“unlock events”), such as subsequent success of the performance evaluation process, approval by an authorized user, digital signatures, etc.

[0025] In some implementations, a sample analysis method can be generated using a performance evaluation process defined at the method level to provide different paths or branches based on, for example, the results of the performance evaluation process. For example, in various implementations, a sample analysis method can be defined as a first path (if the performance evaluation process succeeds), a second path (if the first performance process fails), a third path (if the second performance process fails within a first threshold), and a fourth path (if the second performance process fails within a second threshold). Implementations are not limited to this context. For example, the performance evaluation process can be monitored in real-time or substantially in real-time, and a failure, for example, of a system suitability parameter can prevent the operator or analysis equipment (e.g., via control software) from running the sample (e.g., a "hard failure") and / or allow the run to complete, but prevent the generation and / or access to the processed data.

[0026] The apparatus and methods according to some implementation schemes offer technical advantages over conventional systems. In conventional systems, sample data are generated and, for example, archived regardless of whether performance tests such as quality control checks or system suitability tests fail. Such data in conventional systems remains accessible in the event of quality assurance failure, and is therefore easily manipulated or otherwise misused. Furthermore, conventional analytical systems do not provide efficient and / or effective processes for defining method-level performance evaluation tests. For example, conventional analytical systems may allow some level of labeling (e.g., labeling of QC or calibration samples). However, such labeling only provides basic quality checks and does not allow for quality checks at the method level that allows analytical systems to understand the tests they are performing and to provide pass / fail validity. Moreover, in conventional systems, quality checks are often an all-or-nothing process in which an entire batch may be invalidated if a quality check fails.

[0027] Therefore, the embodiments provide improvements to the operation of analytical systems and / or computational techniques configured to operate analytical devices and / or process analytical data. In one non-limiting example of the improvement, some embodiments provide dynamic performance evaluation of analytical systems, analytical methods, sample analysis, etc., at the method level. In one non-limiting example of the improvement, some embodiments provide customizable processes that offer options or otherwise guide the user and / or analytical device (e.g., via control software) to correct errors that occur during analysis execution. In another non-limiting example of the improvement, exemplary embodiments may prevent the generation and / or access to sample data associated with a failed quality assessment process. In another non-limiting example of the improvement, some embodiments allow the user and / or analytical device to identify and correct errors (e.g., due to a performance assessment process failure) during the execution of an analytical process, potentially preserving sample data that might be invalid in a conventional system. In another non-limiting example of the improvement, embodiments may provide the generation of methods in which a particular sample analysis process can be directly associated with certain performance assessment processes. In yet another non-limiting example of the technological improvement, some embodiments may provide the generation of methods with multiple analysis paths, which can be executed based on, for example, the results of a performance evaluation process and / or a sample analysis process. These and other technical advantages are provided by the apparatus and methods according to some embodiments.

[0028] This description may include many specific details, such as component and system configurations, to provide a more thorough understanding of the described embodiments. However, those skilled in the art will understand that the described embodiments can be practiced without such specific details. Furthermore, some well-known structures, components, and other features have not been shown in detail to avoid unnecessarily obscuring the described embodiments.

[0029] In the following description, references to “an embodiment,” “an embodiment,” “an exemplary embodiment,” “various embodiments,” etc., indicate that an embodiment of the described technology may include a particular feature, structure, or characteristic. However, more than one embodiment may include that particular feature, structure, or characteristic, and not every embodiment must include that particular feature, structure, or characteristic. Furthermore, some embodiments may have some, all, or none of the features described for other embodiments.

[0030] As used in this specification and claims, unless otherwise stated, the use of ordinal adjectives such as “first,” “second,” “third,” etc., to describe an element indicates only a specific instance of the referenced element or a different instance of a similar element, and does not imply that the element described so is in a particular order in time, space, sequence, or any other manner.

[0031] Figure 1 An example of an operating environment 100 that can represent some implementation schemes is shown. For example... Figure 1 As shown, the operating environment 100 may include an analytical system 105 for managing analytical information associated with analytical devices 115a to 115n. In some embodiments, analytical devices 115a to 115n may be or may include chromatographic systems, liquid chromatography (LC) systems, gas chromatography (GC) systems, mass analyzer systems, mass detector systems, mass spectrometer (MS) systems, ion mobility spectrometer (IMS) systems, high performance liquid chromatography (HPLC) systems, ultra-high performance liquid chromatography (UPLC) systems, ultra-high performance liquid chromatography (UHPLC) systems, ultraviolet (UV) detectors, visible light detectors, solid phase extraction systems, sample preparation systems, capillary electrophoresis instruments, combinations thereof, components thereof, variants thereof, etc. Although LC, MS, and LC-MS are used in the examples described herein, embodiments are not limited thereto, as other analytical instruments capable of operating according to some embodiments are contemplated herein.

[0032] In some embodiments, analytical devices 115a to 115n are operable to perform analysis and generate analytical information 136. In various embodiments, analytical information 136 may include information, data, documents, charts, graphs, images, etc., generated by the analytical instrument as a result of performing the analytical method. For example, for an LC-MS system, analytical devices 115a to 115n may separate samples according to a specified method and perform quality analysis on the separated samples to generate analytical information 136, which may include raw or unprocessed data, chromatograms, spectra, peak lists, mass values, retention time values, concentration values, compound identification information, etc. In various embodiments, analytical information 136 may include information obtained from performance evaluation processes such as system suitability testing.

[0033] In various embodiments, the analysis system 105 may include a computing device 110 communicatively coupled to or otherwise configured to receive and store analysis information 136 associated with the analysis devices 115. For example, the analysis devices 115a to 115n may be operable to directly provide the analysis information 136 to the computing device 110 and / or to a location on a network 150 accessible to the computing device 110 (e.g., a cloud computing environment). In some embodiments, the computing device 110 may be operable to control, monitor, manage, or otherwise process various operational functions of the analysis devices 115a to 115n. In some embodiments, the computing device 110 may be operable to provide the analysis information 136 to a location on the network 150 via a secure or authenticated connection. In some embodiments, the computing device 110 may be or may include a standalone computing device, such as a personal computer (PC), server, tablet computer, cloud computing device, etc. In various embodiments, computing device 110 may be or may include a controller or control system integrated into analysis devices 115a to 115n to control aspects of their operation.

[0034] like Figure 1 As shown, computing device 110 may include processing circuitry 120, memory unit 130, and transceiver 160. Processing circuitry 120 may be communicatively coupled to memory unit 130 and / or transceiver 160.

[0035] Processing circuitry 120 may include and / or access various logics for performing processing according to some embodiments. For example, processing circuitry 120 may include and / or access analysis service logic 122, method generation logic 124, and / or performance evaluation logic 126. Processing circuitry and / or analysis service logic 122, method generation logic 124, and / or performance evaluation logic 126, or portions thereof, may be implemented in hardware, software, or a combination thereof. As used in this application, the terms “logic,” “component,” “layer,” “system,” “circuit,” “decoder,” “encoder,” and / or “module” are intended to refer to computer-related entities, which may be hardware, a combination of hardware and software, software, or software in execution, examples of which are provided by exemplary computing architecture 700. For example, logic, circuitry, or layer may be and / or include, but is not limited to, processes running on a processor, processors, hard disk drives, multiple storage drives (optical and / or magnetic storage media), objects, executable programs, execution threads, programs, computers, hardware circuits, integrated circuits, application-specific integrated circuits (ASICs), programmable logic devices (PLDs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs), systems-on-a-chip (SoCs), memory cells, logic gates, registers, semiconductor devices, chips, microchips, chipsets, software components, programs, application programs, firmware, software modules, computer code, and any combination of the foregoing.

[0036] although Figure 1 The analysis service logic 122 is depicted as being within the processing circuitry 120, but the implementation is not limited thereto. Furthermore, although the method generation logic 124 and performance evaluation logic 126 are depicted as part of the analysis service logic 122, the implementation is not limited thereto, as the method generation logic 124 and performance evaluation logic 126 may be separate logic and / or may not be separate logic, but rather part of the analysis service logic 122. For example, the analysis service logic 122 and / or any components thereof may reside within an accelerator, processor core, interface, single processor die, or be fully implemented as a software application (e.g., analysis service application 140), etc.

[0037] Memory cell 130 may include various types of computer-readable storage media and / or systems in the form of one or more higher-speed memory cells, such as read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), dual data rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory (such as ferroelectric polymer memory, bidirectional memory, phase-change or ferroelectric memory), silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic cards or optical cards, device arrays (such as redundant array of independent disks (RAID) drives), solid-state storage devices (such as USB storage devices, solid-state drives (SSDs), and any other type of storage media suitable for storing information. Additionally, memory cell 130 may include various types of computer-readable storage media in the form of one or more lower-speed memory cells, including internal (or external) hard disk drives (HDDs), floppy disk drives (FDDs), and optical disc drives (such as CD-ROMs or DVDs) for reading or writing removable optical discs, solid-state drives (SSDs), etc.

[0038] Memory unit 130 may store analysis service application 140, which may operate independently or in combination with analysis service logic 122 to perform various analysis functions according to some implementation schemes. In various implementation schemes, analysis service application 140 may interact with analysis devices 115a to 115n and / or their components through various drivers (drivers may include application programming interfaces (APIs), software and / or hardware interfaces, etc.).

[0039] In various embodiments, method generation logic 124 is operable to generate analytical methods that can be executed via analytical devices 115a to 115n. In exemplary embodiments, analytical methods may be stored as method information 132. In some embodiments, method generation logic 124 may be or may include a method editor application for allowing user and / or analytical service application 140 to generate analytical methods. For example, method generation logic 124 may be operable to add / remove / modify method steps, method step details, performance evaluation processes, performance evaluation process parameters, performance evaluation process thresholds or acceptance criteria, performance evaluation process anomalies or failure events, associate sample analysis processes with performance evaluation processes, etc. In various embodiments, method information 132 may include, for example, existing methods and / or portions thereof that have been validated, deemed qualified, and / or otherwise accepted for use with analytical devices. In some embodiments, existing methods may include performance evaluation processes and / or sample analysis processes for a particular method.

[0040] Method generation logic 124 allows users to access and modify existing methods to generate new methods. In various implementations, method generation logic 124 can recommend and / or generate methods based on analytical information such as the type of analytical equipment, equipment settings, and analysis type. For example, for MS or LC-MS analysis, method generation logic 124 can recommend and / or generate a first analytical method with a first set of performance evaluation procedures and / or sample analysis procedures for proteomics analysis and a second analytical method with a second set of performance procedures and / or sample analysis procedures for toxicology analysis. As another example, for MS or LC-MS analysis, method generation logic 124 can allow users to generate methods including an injection list and a system suitability list, which provides a system suitability workflow for the method. Implementations are not limited to this context.

[0041] In some MS or LC-MS implementations, the user operating the analytical device 115a can provide information about the analysis to the method generation logic 124, such as the type of compound of interest (e.g., protein, drug, etc.), whether the compound is known or unknown, analytical parameters and / or variables, etc. The method generation logic 124 can generate an analytical method that may include sample set candidates and performance evaluation processes, such as quality control checks, system suitability testing, etc. The proposed sample set for the analytical method can be submitted as a single batch for collection. In some implementations, the results of the proposed sample set can be evaluated by the user and / or the analytical device (e.g., via control software) to determine the optimal method for a particular sample of interest.

[0042] In various embodiments, performance evaluation logic 126 is operable to evaluate, assess, check, verify, identify, or otherwise determine the performance of analytical devices 115a to 115n before, during, and / or after the execution of an analytical method. In some embodiments, performance evaluation logic 126 may manage aspects of the performance evaluation of the analytical methods executed on analytical devices 115a to 115n. For example, performance evaluation logic 126 may receive performance information 134 in the form of the results of a performance evaluation process and determine whether an anomaly has occurred (e.g., whether the performance evaluation process exceeded expected thresholds). In various embodiments, performance information 134 may be accessed from method information 132 (e.g., system suitability test results from analytical data of the analytical method). In some embodiments, performance evaluation logic 126 may trigger a failure state in response to an anomaly, employ a specific path within the analytical method, elicit user input, prevent the generation and / or access to analytical information 136, or cause the user and / or analytical device (e.g., via control software) to rerun the performance evaluation process or other method segments, etc. Embodiments are not limited to this context.

[0043] In some implementations, for MS and / or LC-MS systems, performance evaluation logic 126 may allow the analyst to verify the pass of system suitability parameters, enabling the analyst to proceed with analysis information 136 to generate accurate results. In various implementations, performance evaluation procedures (e.g., system suitability procedures) can be added to the method via a method editor (e.g., implemented by method generation logic 124). Table 1 below depicts exemplary system suitability details of methods according to some implementations: parameter function Fields Components Acceptance Standards A %RSD Peak area Component 1 ≤1.00 B %RSD Retention time Component 1 ≤1.00 C Peak area Component 2 ≥1000 D USP trail Component 1 ≤2.0 Table 1.

[0044] In Table 1, the parameters may be labels used to identify which injections should be included; the function may be a summary calculation to be performed (if left blank, the summary calculation may not be performed and the identified fields may be used as is), and in some implementations, the function required for the increment may include relative standard deviation % (RSD) and average; the field may be a specific result field used for the summary calculation or placed as is in the summary table, and in some implementations, the field used for the increment may include peak area, peak height, retention time, tailing (e.g., United States Pharmacopeia (USP) tailing), plate count (e.g., USP plate count), and / or resolution; and the acceptance criteria may be a standard by which the analyst can compare the results presented in the method workflow.

[0045] In some implementations, a column can be added to the injection table of the MS or LC-MS method, where the analyst can indicate which injection will be used to evaluate each system suitability parameter. This column can accept labels associated with multiple parameters (e.g., A, B, D in Table 1). In some implementations, a user interface (UI) object can be used to define the injection, and this information can be imported into the sample set from the appropriate fields in the analysis information 136.

[0046] In various implementations, the performance evaluation process (e.g., system suitability workflow) may include the summary information depicted in Table 2 below regarding system suitability parameters, acceptance criteria, and observations: parameter Acceptance Standards Observed values A %RSD, peak area, component 1 ≤1.00 0.18 B %RSD, retention time, component 1 ≤1.00 0.15 C Peak area, component 2 ≥1000 1598 D USP trailing, component 1 ≤2.0 1.5 Table 2.

[0047] In Table 2, parameters may be a summary of function, field, and / or component selections; acceptance criteria may be the display of information entered in the method editor; and observations may include calculated values ​​from the selected parameters. In various implementations, performance evaluation logic 126 may compare observations with acceptance criteria and trigger exception events, display warnings, highlight failures, indicate pass or accept, etc.

[0048] In various implementations, non-system suitability fields may be applied to the defined injections and may be summarized, such as in the summary in Table 2. In various implementations, the operator may define certain "standard" fields (e.g., peak area, peak height, retention time, etc.) and components in the method. In an exemplary implementation, the operator may define specific injections in the injection list and review the defined fields for appropriate injections / components for system suitability, allowing the operator and / or analytical devices 115a to 115n (e.g., via control software) to verify the value against system suitability criteria.

[0049] In various implementations, system suitability calculations can be added, for example, as an option for field selection. For instance, an operator can define a "system suitability" field in the method (e.g., USP tailing, USP plate count, resolution, etc.) and specific injections in the component, injection list, etc. In an exemplary implementation, the operator can review the defined fields for appropriate injections / components in system suitability to verify the value against system suitability criteria, etc.

[0050] In exemplary embodiments, acceptance criteria can be added to and defined within the method and displayed in the summary. For example, an operator can add acceptance criteria to the system suitability criteria within the method, making them visible in the system suitability summary to effectively compare observations against predefined criteria in a visual manner. In some embodiments, summary calculations can be provided; for example, an operator can define summary calculations (%RDS and averages) to selected fields and components, and further define multiple injections used to complete the calculations. In this way, summary calculations can be included in the assessment of system suitability.

[0051] In various implementations, performance information 134 may include information related to user performance information or statistics. For example, analytics service application 140 may include a group of registered users. The execution of a method and / or parts thereof may be associated with one or more specific users. Method information 132, performance information 134, and / or analytics information 136 may be used to generate user statistics for registered users. For example, in some implementations, analytics service application 140 may include a user performance application that allows users to view results achieved by a specific user, performance evaluation processes associated with a specific user, and anomalous events associated with a specific user. For example, an administrator may access user statistics for a first user via the user statistics interface of analytics service application 140. The administrator can determine, for example, the pass rate of system suitability tests associated with the first user, whether the first user has passed data associated with certain system suitability results (e.g., failed or low-confidence system suitability results), which method path the user has chosen to respond to anomaly requests, the number of anomalous requests associated with the user, and so on. Implementations are not limited to this context.

[0052] Figure 2 An example of an operating environment 200 that can represent some implementation schemes is shown. For example... Figure 2 As shown, the operating environment 200 may include an analysis exchange platform (or analysis instrument platform) 205. In some embodiments, the analysis exchange platform 205 is operable to provide an exchange of analytical information between entities of interest. In various embodiments, the analysis exchange platform 205... In exemplary embodiments, the analysis exchange platform 205 may be or may include a software platform, suite, protocol suite, etc., provided to a customer by a manufacturer and / or developer associated with the analytical instrument. A non-limiting example of a developer may be Waters Corporation, Milford, Massachusetts, United States of America. For example, the developer may provide the analysis exchange platform 205 as a data exchange interface for analytical instruments such as LC, MS, LC-MS, etc., provided by the developer to the entities.

[0053] In an exemplary embodiment, the operating environment 200 may include a computing device 210 for displaying (e.g., via analytics service application 140) a user interface 220. In some embodiments, the user interface 220 may include a browser application, a graphical user interface (GUI), a web interface, a mobile application (“mobile app”, “mobile app”, or “app”), etc. The embodiments are not limited to this context. In various embodiments, a user may interact with the analytics exchange platform 205 and / or its components via the user interface 220.

[0054] Authentication 270 of the analytics exchange platform 205 may be performed via authentication device 230. In some embodiments, authentication device 230 may be or may include an identity provider in the form of a third-party entity or computing device that performs the authentication service. User interface service 272 may be provided via user interface web server 240. For example, some or all of the information, objects, etc., presented via user interface 220 may be provided via user interface web server 240. In various embodiments, user interface web server 240 may serve as the entry point and interface for users to access analytics exchange platform 205.

[0055] In various implementations, business logic service 274 may be provided to computing device 210 via application server 250. Generally, business logic service 274 may include database access and services, workflow services, etc. In various implementations, analytics service application 140 may be executed by application server 250. For example, a server version of analytics service application 140 may be executed by application server 250, and a corresponding client-side analytics service application 140 may be executed on computing device 210. In some implementations, the client application may be or may include a web application (“webapp” or “app”), a remote web client, a thin client, etc.

[0056] In some implementations, the application server 250ng is operatively coupled to the acquisition controller 260 to access data generated by the analytics device 215. In various implementations, the acquisition controller 260 is operable to (e.g., via the application server 250) send information, events, etc., to the user interface 220 for real-time monitoring and status updates. In various implementations, the acquisition controller 260 is operable to manage the acquisition of data by the analytics device 215 (e.g., via an analytics service application). Implementations are not limited to this context.

[0057] In various implementations, user interface 220 may provide certain functionalities to implement the methods of analytics service application 140. For example, when data is invalid, the user interface 220 may notify the user. In various implementations, the user interface may prevent the saving of invalid data. In exemplary implementations, user interface 220 may allow the saving of invalid data, provided that the invalid data is specified or otherwise marked as invalid. In various implementations, processes may be provided to verify invalid data, such as stopping by an authorized user, associating invalid data with a rerun of a method segment and / or performance evaluation process, etc. In some implementations, for example, if the invalid data is due to some type of error (such as a processing error or other non-system failure error), the invalid data may be able to be corrected. In various implementations, data, methods, reports, or other objects viewed via user interface 220 may be automatically saved. For example, if a user is viewing data on a first screen displaying data and navigates to a second screen, the data on the first screen will be automatically saved.

[0058] This document includes one or more logical flows representing exemplary methods for performing novel aspects of the disclosed embodiments. While for illustrative purposes, one or more methods shown herein are illustrated and described as a series of actions, those skilled in the art will understand and appreciate that these methods are not limited by the order of actions. Therefore, some actions, steps, etc., may occur in a different order and / or concurrently with other actions shown and described herein. Furthermore, certain actions, steps, etc., may be excluded. For example, those skilled in the art will understand and appreciate that methods may alternatively be represented as a series of related states or events, such as in a state diagram. Moreover, not all behaviors shown in the methods may be necessary for the novel implementation.

[0059] The logical flow can be implemented using software, firmware, hardware, or any combination thereof. In software and firmware implementations, the logical flow can be implemented by computer-executable instructions stored on a non-transitory computer-readable medium or a machine-readable medium, such as an optical, magnetic, or semiconductor storage device. Implementations are not limited to this context.

[0060] Figure 3 An embodiment of logic flow 300 is illustrated. Logic flow 300 may represent some or all of the operations performed by components of one or more embodiments described herein, such as computing device 110 and / or analysis exchange platform 205. In some embodiments, logic flow 300 may represent some or all of the operations of a method generation process.

[0061] At box 302, the logic flow 300 has access to a method editor. In some implementations, the method editor may include manual and / or automatic input of method steps, parameters, system evaluation procedures, etc. In various implementations, the user may input the type of analysis (e.g., toxicology analysis on an MS system), and the method editor may load method templates, previously used methods, suggested methods, etc. In some implementations, the user may modify the loaded method. Implementations are not limited to this context.

[0062] At box 304, logic flow 300 may provide a system performance evaluation process. For example, a performance evaluation process for assessing the overall performance of an analytical apparatus may be provided to be included in the method. Generally, the system performance evaluation process is operable to determine whether the analytical apparatus is suitable for performing the analytical method and whether it is functioning correctly. In an MS or LC-MS system, the system performance evaluation process may include system suitability tests to determine, for example, whether the MS or LC-MS system is suitable for performing the analytical method. Non-limiting examples of system suitability tests may include tailing, retention time, plate count, resolution, etc. In some embodiments, the performance evaluation process may be injection-specific. For example, labels or other indicators may be used to specify and visualize the relationship between an injection and a specific test, such as associating an injection with a specific test.

[0063] At box 306, logic flow 300 can create a method segment. Generally, a method segment can include discrete parts of a method, including steps, tests, analyses, paths, branches, user-defined segments, etc. In various embodiments, a method segment can include a sample analysis process (or sample event) associated with the analysis of a sample (e.g., sample injection in an MS or LC-MS system). In an exemplary embodiment, a method segment can include test events associated with a performance evaluation process. In various embodiments, methods can be generated to associate sample events with test events. For example, a first test event (e.g., a set of system suitability tests) can be associated with a first set of sample events (e.g., a set of sample injections), and a second test event can be associated with a second set of sample events. The failure of the first test event (e.g., system suitability testing out of scope) can affect the first set of sample events (e.g., may skip the method segment and / or may not generate data and / or make the data unavailable for the associated method segment), but does not affect the second set of sample events.

[0064] In some implementations, a method segment may include other segments. For example, a method segment may be defined as a path or branch that may include multiple step segments. In implementations using an MS or LC-MS system, a segment may include an injection and / or a set or series of injections.

[0065] In various implementations, a segment may include conditions for executing the segment. For example, a first segment may have a condition that a system performance evaluation process has passed. Another example is a second segment with a condition that a specific performance evaluation process has passed, while a third segment may have a condition that a specific performance evaluation process has failed (e.g., a segment for handling anomalies). Yet another example is a fourth segment with a condition that the sample is within a specific threshold (e.g., to ensure that the analytical instrument is within a range for accurately detecting or otherwise processing sample concentrations). In various implementations, a method segment may include steps, paths, branches, etc., for handling anomalies (e.g., a failed performance evaluation process). In an exemplary implementation, a method segment may include data generation, access, and / or processing segments. This allows the operator to manage data generation and / or access at the method level.

[0066] In various implementations, the method editor may automatically include default method segments. For example, certain method segments may be required depending on certain protocols, such as a quality control check method segment for analysis of a specified number of samples. In exemplary implementations, a method may include hidden and / or non-editable method segments. For example, a data generation and / or access method segment may be hidden and / or non-editable. In various implementations, the sample analysis method segment may be separate from the data generation and / or access method segment. For example, a first method segment in an MS analysis method may include multiple injections. By default, the method editor may include a second method segment in the form of a hidden or non-editable data generation method segment after the first method segment. Thus, data generated by analyzing injections may not be available until after the execution of the second method segment. In some implementations, a third method segment may be included between the first and second method segments for performing a performance evaluation process, and the second method segment may have the condition that the third method segment passes the performance evaluation process. Thus, generating and / or accessing data associated with the analysis of the injections in the first method segment depends on the passing of the method-level performance evaluation process. Implementations are not limited to this context.

[0067] At box 308, logic flow 300 can provide a method segment performance evaluation process. For example, a performance evaluation process can be assigned to a method segment to provide performance evaluation at the method level. Thus, logic flow 300 can implement dynamic performance evaluation, where each analytical step (or method segment) can be processed immediately or substantially immediately, and if the analytical step exceeds a threshold, the method can continue downwards along the appropriate branch (e.g., pause the run, abort the run, provide the operator with a manual option to continue, rerun the analytical step, etc.). For example, in an MS or LC-MS system, logic flow can facilitate dynamic system suitability, where each injection can be processed immediately after acquisition, and if the injection is non-compliant, the run is paused, and the operator can make a manual decision to continue, rerun the injection, or otherwise modify the run.

[0068] At box 310, logic flow 300 can determine whether the method has completed. If the method requires and / or expects more method segments, the logic flow can return to box 306 to create the method segments. If the method has completed, logic flow 310 can generate, for example, a method file 312 that can be executed via an analysis device.

[0069] Figure 4 An embodiment of logic flow 400 is illustrated. Logic flow 400 may represent some or all of the operations performed by components of one or more embodiments described herein, such as computing device 110 and / or analysis exchange platform 205. In some embodiments, logic flow 400 may represent some or all of the operations performed according to an execution method of some embodiments.

[0070] At box 402, logic flow 400 can execute the method by determining system performance evaluation result information. For example, a system performance evaluation process for the method can be executed, and performance information (e.g., performance information 134) can be determined. For example, for an MS or LC-MS system, system suitability testing can be performed and the results determined. At box 404, logic flow 400 can determine whether the system performance evaluation process for the method has passed, for example, by comparing the analyzed value with a threshold. If the system performance evaluation fails, a "hard failure" can be triggered, and logic flow 400 can enter a failure state at box 406 (see Exemplary exception event logic flow according to some implementations). Figure 5 In various implementations, a failure of system performance evaluation may indicate that the analysis device is not operating correctly in executing the method. In some implementations, a failure state may exit the method workflow, and the method run may be designated as a failure run. In some implementations, if a method segment associated with the system performance process indicates a system suitability test failure, the method may continue down a path that terminates in a failure state without performing sample analysis.

[0071] If logic flow 400 determines at block 404 that the system performance evaluation has passed, then the logic flow may continue execution of method segment N at block 408. Logic flow 400 may determine the performance information of method segment N at block 410. For example, if a performance evaluation process has been defined for method segment N, these processes may be executed and the associated performance information determined. At block 410, logic flow 400 may determine whether the performance evaluation process associated with method segment N (in some embodiments, it may be in a different method segment associated with method segment N via conditions, etc.) has passed. If the performance evaluation process has failed, logic flow 400 may trigger an exception event at block 420.

[0072] If the performance evaluation process fails, the exception may cause the method to continue down one or more different paths defined in the method (e.g., to handle the failed performance evaluation process). For example, in the first path, the performance evaluation process may have failed due to an operational error of the analysis device, and the logic flow 400 may enter failure state 406. Alternatively, in the second path, the failure may be due to processing or other reasons that allow the operator and / or analysis device (e.g., automatically via control software) to attempt to rerun and / or fix the problem, and the logic flow 400 may re-enter the method workflow (e.g., in the failed performance evaluation process segment to confirm its success).

[0073] If logic flow 400 determines at block 412 that the performance evaluation of method segment N has passed, then logic flow 400 can determine at block 414 whether the method has completed. If the method has not completed, the method steps can be incremented at block 418, and the next method segment can be executed at block 408. If the method has completed, logic flow 400 can provide method information for analysis at block 416.

[0074] Figure 5 An embodiment of logic flow 500 is illustrated. Logic flow 500 may represent some or all of the operations performed by components of one or more embodiments described herein, such as computing device 110 and / or analysis exchange platform 205. In some embodiments, logic flow 500 may represent some or all of the operations for handling exception requests according to some embodiments.

[0075] Logic flow 500 may prevent the generation and / or access to method data at block 502 in response to an anomalous event. For example, in some embodiments, data processing tasks may be segmented, partitioned, or otherwise separated. For example, each method segment and / or portion thereof may be associated with a data processing task to, for example, generate data associated with any analysis associated with the method segment and / or make that data accessible. In MS or LC-MS system embodiments, a first method segment associated with a first sample injection may include a call to a processing task to generate or make accessible method information resulting from the sample injection analysis. The call to the processing task may depend on the absence of an anomalous request (e.g., "If there is no anomalous request, call the 'Process Data' routine"). In various embodiments, the method is operable to provide only the processing necessary to perform the task and / or to provide information (e.g., associated with a sample injection or method segment) on a specific user interface page. Thus, the user may not be able to access the data unless appropriate data quality assurance (e.g., a performance evaluation process) associated with the data is passed.

[0076] Therefore, sample data associated with a failed performance evaluation process (e.g., “failure state sample data”) may not be generated and / or become inaccessible. In various implementations, failure state sample data may remain in a “raw” or unprocessed state that may not be easily accessible to the operator (e.g., not converted into an operator-readable state, such as a chromatogram or spectrum). Therefore, in some implementations, users may be proactively prohibited from adjusting or manipulating the data to prevent the misuse of suspicious data through system suitability or otherwise.

[0077] At box 504, logic flow 500 may determine whether an anomalous event is associated with a system failure (e.g., a critical-level anomalous event). For example, a system failure may include the failure of a performance evaluation process (e.g., system suitability) that indicates the analysis equipment is not operating correctly. If a system failure is detected, logic flow 500 may exit the analysis workflow at box 506, enter a failure state at box 508, and / or designate the method run as a failure at box 510.

[0078] If logic flow 500 determines at block 504 that the exceptional event is not a system failure (e.g., a non-critical level exception), then logic flow 500 may wait at block 512 for instructions to continue the process. For example, an operator may provide input indicating that the process should continue, for example, by rerunning the failed method segment, performing a maintenance method segment, etc. In some implementations, if logic flow 500 does not receive instructions to continue at block 512, then logic flow 500 may continue down the same or a similar path to system failure 504.

[0079] At box 514, in response to receiving an instruction to continue the method at box 512, logic flow 500 may determine performance information, for example, through rerunning a failed performance evaluation process, execution of subsequent method segments, or execution of a path of a method segment triggered due to failure. Logic flow 500 may determine at box 516 whether the performance evaluation passed, for example, in connection with rerunning a failed performance evaluation process, execution of subsequent method segments, or execution of a path of a method segment triggered due to failure. If logic flow 500 determines at box 516 that the performance evaluation passed, then logic flow 500 may continue the method at box 518 and generate the resulting method data and / or provide access to it at box 520. In some embodiments, logic flow may continue the method at box 518, but may not generate the resulting method data and / or provide access to it at box 520. For example, in various embodiments, the method may continue at box 518, but may not generate the resulting data and / or may not authorize access to the accessed data. In exemplary embodiments, a data unlock event may be required to access non-generated and / or inaccessible data. Data unlocking events may include authorization from administrators or other authorized users, designation or tagging of data associated with a failed performance evaluation process, etc.

[0080] If logic flow 500 determines at block 516 that the performance evaluation has failed, logic flow 500 may return to block 502 to re-execute the exception event procedure. In some implementations, the failure threshold number of the performance evaluation procedure can be specified as a system failure.

[0081] Figures 6A to 6C Exemplary screen images from an analytics service application, according to some implementation schemes, are depicted. In various implementations, the analytics service application may be applicable to an LC-MS system. Figure 6A A screen image 605 depicts a sample window 620, a component window 630, and a chromatogram window 640. The sample window 620 may present, for example, an injection associated with an analytical method. The component window 630 is operable to display identified components in the selected injection. The chromatogram window 640 may display the trace of the selected injection. In some embodiments, when a user selects an injection, the component window 630 may load the components in that injection and automatically select the first row or previously selected components. In various embodiments, the chromatogram window 640 is operable to acquire and render the trace of the component identifier (ID) associated with the selected component.

[0082] Figure 6B An inspection capture screen image 650 is depicted according to some implementation schemes. For example... Figure 6B As shown, sample injection may include system suitability injection, standard injection, and / or sample injection. Implementation methods are not limited to this context. Figure 6CScreen image 660 depicts system applicability according to some implementation schemes. For example... Figure 6C As shown, failure parameters of system suitability testing or injection can be visually indicated to the user.

[0083] Figure 7 An embodiment of an exemplary computing architecture 700 suitable for implementing the various embodiments described above is shown. In various embodiments, the computing architecture 700 may include or be implemented as part of an electronic device. In some embodiments, the computing architecture 700 may represent, for example, devices 205, 305, and / or 405. The embodiments are not limited to this context.

[0084] As used in this application, the terms "system," "component," and "module" are intended to refer to computer-related entities, which may be hardware, a combination of hardware and software, software, or software in execution, examples of which are provided by the exemplary computing architecture 700. For example, a component can be, but is not limited to, a process running on a processor, a processor, a hard disk drive, multiple storage drives (optical and / or magnetic storage media), an object, an executable file, an execution thread, a program, and / or a computer. For example, both an application running on a server and the server itself can be components. One or more components may reside within a process and / or an execution thread, and components may be located on a single computer and / or distributed across two or more computers. Furthermore, components may be communicatively coupled to each other to coordinate operation via various types of communication media. Coordination may involve one-way or two-way information exchange. For example, a component may convey information in the form of signals communicated through a communication medium. This information may be implemented as signals assigned to various signal lines. In such assignments, each message is a signal. However, alternative embodiments may use data messages. Such data messages can be sent via various connections. Exemplary connections include parallel interfaces, serial interfaces, and bus interfaces.

[0085] The computing architecture 700 includes various general-purpose computing elements, such as one or more processors, multi-core processors, coprocessors, memory units, chipsets, controllers, peripherals, interfaces, oscillators, timing devices, video cards, audio cards, multimedia input / output (I / O) components, power supplies, etc. However, implementations are not limited to the implementation of the computing architecture 700.

[0086] like Figure 7 As shown, the computing architecture 700 includes a processing unit 704, a system memory 706, and a system bus 707. The processing unit 704 can be any of a variety of commercially available processors, including but not limited to: AMD... ® Athlon ® Duron ® And Opteron ®Processor; ARM ® Application, embedded, and security processors; IBM ® and Motorola ® DragonBall ® and PowerPC ® Processors; IBM and Sony ® Cell processor; Intel ® Celeron ® Core(2) Duo ® Itanium ® Pentium ® Xeon ® and XScale ® Processors; and similar processors. Dual microprocessors, multi-core processors, and other multiprocessor architectures can also be used as processing units 704.

[0087] System bus 707 provides interfaces for system components, including but not limited to interfaces for connecting system memory 706 to processing unit 704. System bus 707 can be any of several types of bus architectures, which can be further interconnected to memory bus (with or without memory controller), peripheral bus, and local bus using any of a variety of commercially available bus architectures. Interface adapters can be connected to system bus 707 via slot architectures. Exemplary slot architectures can include, but are not limited to, Accelerated Graphics Port (AGP), Card Bus, (Extended) Industry Standard Architecture ((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral Component Interconnect (Extended) (PCI(X)), PCI Express, PCMCIA, etc.

[0088] System memory 706 may include various types of computer-readable storage media in the form of one or more high-speed memory cells, such as read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), dual data rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory (such as ferroelectric polymer memory, bidirectional memory, phase-change or ferroelectric memory), silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic cards or optical cards, device arrays (such as redundant array of independent disks (RAID) drives), solid-state storage devices (such as USB storage devices, solid-state drives (SSDs), and any other type of storage media suitable for storing information. Figure 7In the illustrated embodiment, system memory 706 may include non-volatile memory 710 and / or volatile memory 712. The basic input / output system (BIOS) may be stored in non-volatile memory 710.

[0089] Computer 702 may include various types of computer-readable storage media in the form of one or more low-speed memory cells, including internal (or external) hard disk drive (HDD) 714, magnetic floppy disk drive (FDD) 716 for reading or writing to removable disk 717, and optical disc drive 720 (e.g., CD-ROM or DVD) for reading or writing to removable optical disc 722. HDD 714, FDD 716, and optical disc drive 720 may be connected to system bus 707 via HDD interface 724, FDD interface 726, and optical disc drive interface 727, respectively. HDD interface 724 for external drive implementations may include at least one or both of Universal Serial Bus (USB) and IEEE 1374 interface technologies.

[0090] Drives and associated computer-readable media provide volatile and / or non-volatile storage of data, data structures, computer-executable instructions, etc. For example, multiple program modules may be stored in drive and memory units 710, 712, including an operating system 730, one or more application programs 732, other program modules 734, and program data 736. In one embodiment, one or more application programs 732, other program modules 734, and program data 736 may include various application programs and / or components, such as those in devices 105, 205, 305, and / or 405.

[0091] Users can input commands and information into computer 702 through one or more wired / wireless input devices (e.g., keyboard 737 and clicking devices such as mouse 740). Other input devices may include microphones, infrared (IR) remote controls, radio frequency (RF) remote controls, game controllers, styluses, card readers, dongles, fingerprint card readers, gloves, graphics tablets, joysticks, keyboards, retina readers, touchscreens (e.g., capacitive, resistive, etc.), trackballs, touchpads, sensors, styluses, etc. These and other input devices are typically coupled to processing unit 704 via input device interface 742, which is coupled to system bus 707, but can be connected via other interfaces such as parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, etc.

[0092] A monitor 744 or other type of display device is also connected to the system bus 707 via an interface such as a video adapter 746. The monitor 744 can be internal or external to the computer 802. In addition to the monitor 744, the computer typically includes other peripheral output devices such as speakers, printers, etc.

[0093] Computer 702 can operate in a networked environment via logical connections to one or more remote computers, such as remote computer 747, using wired and / or wireless communications. Remote computer 747 can be a workstation, server computer, router, personal computer, portable computer, microprocessor-based entertainment device, peer-to-peer device, or other public network node, and typically includes many or all of the elements described relative to computer 702; however, for simplicity, only memory / storage device 750 is shown. The depicted logical connections include wired / wireless connections to a local area network (LAN) 752 and / or a larger network such as a wide area network (WAN) 754. Such LAN and WAN network environments are common in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which can connect to global communication networks, such as the Internet.

[0094] When used in a LAN network environment, computer 702 is connected to LAN 752 via a wired and / or wireless communication network interface or adapter 756. Adapter 756 facilitates wired and / or wireless communication to LAN 752, which may also include a wireless access point configured thereon for wireless functional communication with adapter 756.

[0095] When used in a WAN networking environment, computer 702 may include modem 757, or a communication server connected to WAN 754, or other means for establishing communication via WAN 754, such as via the Internet. Modem 757 may be internal or external, and wired and / or wireless, connected to system bus 707 via input device interface 742. In a networking environment, program modules or portions thereof described relative to computer 702 may be stored in remote memory / storage device 750. It should be understood that the network connections shown are exemplary, and other means of establishing communication links between computers may be used.

[0096] Computer 702 is operable to communicate with wired and wireless devices or entities, such as wireless devices operably configured in wireless communication (e.g., IEEE 802.16 air modulation technology), using IEEE 802 series standards. This includes at least Wi-Fi (or Wireless Fidelity), WiMax, and Bluetooth. ™Wireless technologies, etc. Therefore, communication can be a predefined structure like a regular network, or simply self-organized communication between at least two devices. Wi-Fi networks use radio technology known as IEEE 802.11x (a, b, g, n, etc.) to provide secure, reliable, and fast wireless connectivity. Wi-Fi networks can be used to connect computers to each other, connect to the Internet, and connect to wired networks (using IEEE 802.3 related media and functions).

[0097] Many specific details have been set forth herein to provide a thorough understanding of the implementation scheme. However, those skilled in the art will understand that the implementation scheme can be practiced without these specific details. In other instances, well-known operations, components, and circuits have not been described in detail to avoid obscuring the implementation scheme. It is understood that the specific structural and functional details disclosed herein are representative and do not necessarily limit the scope of the implementation scheme.

[0098] The terms “coupled” and “connected”, as well as their derivatives, may be used to describe some implementations. These terms are not intended to be synonymous with each other. For example, the terms “connected” and / or “coupled” may be used to describe some implementations to indicate that two or more elements are in direct physical or electrical contact with each other. However, the term “coupled” may also mean that two or more elements are not in direct contact with each other, but still cooperate or interact with each other.

[0099] Unless otherwise expressly stated, terms such as “processing,” “computing,” “operation,” and “determining” refer to the operation and / or process of a computer or computing system or similar electronic computing device that processes and / or converts data represented as physical quantities (e.g., electrons) within the registers and / or memory of the computing system into physical quantities similarly represented within the memory, registers, or other such information storage, transmission, or display devices of the computing system. Implementations are not limited to this context.

[0100] It should be noted that the methods described herein need not be performed in the order described or in any particular order. Furthermore, the various activities described with respect to the methods identified herein can be performed in a series or in parallel.

[0101] While specific embodiments have been illustrated and described herein, it should be understood that any arrangement intended to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of the various embodiments. It should be understood that the above description is illustrative and not restrictive. After reading the above description, combinations of the above embodiments and other embodiments not specifically described herein will be apparent to those skilled in the art. Therefore, the scope of the various embodiments includes any other application in which the above compositions, structures, and methods are used.

[0102] Although the subject matter has been described in language specific to structural features and / or methodological actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, specific features and actions are disclosed as exemplary forms for implementing the claims.

Claims

1. An apparatus comprising: At least one memory; and Logic, the logic being coupled to the at least one memory, the logic being used for: An analysis method is generated to be executed by an analysis device. This analysis method includes multiple method segments, each including at least one performance evaluation process and at least one sample analysis process. The at least one performance evaluation process includes system suitability testing. The at least one performance evaluation process is associated with the at least one sample analysis process, wherein the at least one performance evaluation process is executed dynamically during the execution of the at least one sample analysis process. In response to an abnormal event caused by at least one performance evaluation process exceeding a threshold, Prevent the generation or access to data associated with the anomalous event in at least one sample analysis process. The analysis device enters a failure state in response to the abnormal event being a critical-level abnormality. In response to the anomaly being a non-critical level anomaly, the method continues but prevents the generation or access to data associated with the anomaly in the at least one sample analysis process. The analysis method includes multiple paths, and the logic is used to determine one of the multiple paths for the analysis device to execute based on the results of the at least one performance evaluation process.

2. The apparatus of claim 1, wherein at least one analytical instrument comprises at least one of a liquid chromatography (LC) system, a gas chromatography (GC) system, a mass analyzer system, a mass spectrometer (MS) system, an ion mobility spectrometer (IMS) system, a high performance liquid chromatography (HPLC) system, an ultra-high performance liquid chromatography (UPLC) system, an ultra-high performance liquid chromatography (UHPLC) system, and any combination thereof.

3. The apparatus according to claim 2, wherein the at least one sample analysis process includes sample injection.

4. The apparatus of claim 1, wherein the logic responds to the exception event being a non-critical exception by re-running the at least one performance evaluation process associated with the exception event.

5. A method comprising: Generate an analysis method to be executed by an analysis device, the analysis method comprising multiple method segments, the multiple method segments including at least one performance evaluation process and at least one sample analysis process; The at least one performance evaluation process is associated with the at least one sample analysis process, wherein the at least one performance evaluation process is executed dynamically during the execution of the at least one sample analysis process. In response to an abnormal event caused by at least one performance evaluation process exceeding a threshold, Prevent the generation or access to data associated with the anomalous event in at least one sample analysis process. The analysis device enters a failure state in response to the abnormal event being a critical-level abnormality. In response to the anomaly being a non-critical level anomaly, the method continues but prevents the generation or access to data associated with the anomaly in the at least one sample analysis process. The analysis method includes multiple paths, and the analysis method further includes determining one of the multiple paths for the analysis device to execute based on the results of the at least one performance evaluation process.

6. The method according to claim 5, wherein the analytical device comprises either a mass spectrometry (MS) system or a liquid chromatography-mass spectrometry (LC-MS) system.

7. The method according to claim 6, wherein the at least one sample analysis process includes sample injection.

8. The method of claim 6, wherein the at least one performance evaluation process includes system suitability testing.

9. The method of claim 5, wherein the method includes rerunning the at least one performance evaluation process associated with the anomalous event in response to the anomalous event being a non-critical level anomalous event.

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