Systems and methods for configuring mass spectrometers for multi-component assays

Abstract

Disclosed are methods, systems, apparatus, devices, and other implementations, that includes a method of operating a mass spectrometry (MS) system to analyze a sample, including that includes obtaining compound analysis data for multiple compounds of interest, obtaining compound detectability data for each of the multiple compounds of interest over a plurality of sets of operating parameters of the MS system, determining, based on the detectability data and evaluation conditions, at least one set of optimal operating parameter values for one or more operating parameters of the MS system to analyze the multiple compounds of interest, and storing the optimal operating parameter values corresponding to the sample. In some embodiments, the method can further include retrieving the stored optimal operating parameter values, controllably adjusting the one or more operating parameters of the MS system according to the optimal operating parameter values, and analyzing the sample using the determined optimal operating parameters.

Description

SYSTEMS AND METHODS FOR CONFIGURING MASS SPECTROMETERSFOR MULTI-COMPONENT ASSAYSRelated Applications

[0001] This application claims priority to U.S. Provisional Application No. 63 / 559,647 filed on February 29, 2024, the contents of which are incorporated herein by reference in their entirety.Technical Field

[0002] The present disclosure relates generally to systems and methods for performing mass spectrometry, and more particularly for configuring a mass spectrometer for optimal detection of compounds of interest in multi-component (multi-compound) assays.Background

[0003] The present disclosure relates generally to methods and systems for determining optimal operating parameters for a mass spectrometer (of various types) to allow detection of a maximum number of compounds that might be present in a sample and that are to be analyzed through mass spectrometry. Mass spectrometry analysis can then be done under optimal (or near-optimal) conditions to facilitate acquisitions of good analysis results. Setting of optimal operating parameters for the mass spectrometry can thus facilitate analysis of multiple compounds (e.g., in the hundreds) within a sample to ascertain that certain compounds of interest are present, and to determine quantitative properties of different compounds such as their absolute abundance / concentration and / or relative abundance and concentration relative to other compounds that are present.

[0004] Mass spectrometry (MS) is an analytical technique for determining the structures and characteristics of test chemical substances with both qualitative and quantitative applications. MS can be useful for identifying unknown compounds, determining the composition of atomic elements in a molecule, determining the structure of a compound by observing its fragmentation, and quantifying the amount of a particular chemical compound in a mixed sample. Mass spectrometers detect chemical entities as ions such that a conversion of the analytes to charged ions must occur.

[0005] When an assay with a small number of compounds is prepared for analysis, the mass spectrometer can be configured (e.g., have its operating parameters controlling the behavior of certain components or features of the mass spectrometer) in such a way that likelihood of detectability and the quality of the quantitative analysis for the compounds increases. However, when creating an assay with a large number (e.g., hundreds) of compounds in it, a typical step that is undertaken is to determine the sensitivity or limit of quantitation (LOQ) for each compound and then start working on any compound that does not achieve the desired LOQ. The development of these large panel assays is difficult as some compounds are fragile and require lower source temperature. It might be developed once, and then used for a long time, even if some of the parameter values (for various respective operating parameters of MS system) are sub-optimal.

[0006] Thus, there is a need for a new approach to more efficiently determine operating parameters for large assays that would make it easier to create such large panel assays.Summary

[0007] In one aspect, a method of operating a mass spectrometry (MS) system to analyze a sample is disclosed that includes obtaining compound analysis data for multiple compounds of interest to be analyzed, obtaining compound detectability data for each of the multiple compounds of interest over a plurality of sets of operating parameters of the MS system, determining, based on at least the detectability data and one or more evaluation conditions, at least one set of optimal operating parameter values for one or more operating parameters of the MS system to analyze the multiple compounds of interest in the sample, and storing the optimal operating parameter values corresponding to the sample.

[0008] In various embodiments, the method can further include retrieving the stored optimal operating parameter values determined for the multiple compounds of interest, controllably adjusting the one or more operating parameters of the MS system according to the optimal operating parameter values, and analyzing the sample using the determined optimal operating parameter values for the one or more operating parameters of the MS system.

[0009] In various embodiments, the compound detectability data for each of the multiple compounds of interest can represent detectability characteristics for that compound with respect to a set of operating parameters of the MS system.

[0010] In various embodiments, obtaining the compound detectability data can include excluding one of the plurality of sets of operating parameter values as a possible candidate for the optimal operating parameter values in response to a determination that for at least one of the multiple compounds of interest, a respective detectability value for a particular detectability parameter for the at least one of the multiple compounds of interest is below a target threshold associated with the particular detectability parameter.

[0011] In various embodiments, obtaining the compound detectability data can include accessing a data repository in communication with the MS system, the data repository storing detectability data for a plurality of compounds over the plurality of sets of operating parameters of the MS system, and retrieving detectability data records from the data repository for the multiple compounds of interest, the detectability data records containing the detectability data for the multiple compounds of interest over the plurality of sets of operating parameters.

[0012] In various embodiments, determining the optimal operating parameter values for the one or more operating parameters can include performing one or more mitigation operations in response to a determination that at least one of the multiple compounds of interest has a detectability value, for a respective detectability parameter, that is below a detectability threshold using any combination of detectability data values for the multiple compounds of interest and the one or more evaluation conditions. In such embodiments, the one or more mitigation operations can include one or more of, for example, a) triggering a system exception condition, b) relaxing at least one of the one or more evaluation conditions, and re-executing the determining step, and / or c) presenting on a user- interface multiple sub-optimal proposals of operating parameter values for the one or more operating parameters of the MS system, presenting for each of the sub-optimal proposals a respective number of non-detectable compounds, and receiving user input representative of a selection of one of the multiple sub-optimal proposals.

[0013] In various embodiments, obtaining the compound detectability data can include obtaining a respective mass spectrometer (MS) compound data set for the each of the multiple compounds of interest, with the MS compound data set for a particular compound including oneor more detectability values associated with respective one or more detectability parameters, for different values for the one or more operating parameters of the MS system.

[0014] In various embodiments, the one or more detectability parameters can include one or more of, for example, intensity level, ionization efficiency level, limit of quantification (LoQ) level, and / or signal-to-noise ratio (S / N) level.

[0015] In various embodiments, each of the one or more detectability parameters can be associated with a set of operating parameters that includes one or more of, for example, temperature, gas flow rate, electrospray ionization (ESI) source voltage, atmospheric pressure chemical ionization (APCI) source voltage, source current, LC elution rate, column temperature, column type, solvent type, solvent gradient, and / or any other slow-changing MS system parameter that requires multiple reaction monitoring (MRM) cycles of the MS system.

[0016] In various embodiments, the method can further include setting desired compound characteristic parameters for at least one of the multiple compounds of interest, the compound characteristic parameters include one or more of, for example, a desired limit of quantitation (LOQ) analyte concentration for the at least one compound, signal response factors for the at least one compound, and / or multiple reaction monitoring (MRM) transition parameter for the at least one compound. In such embodiments, determining the optimal operating parameter values for the one or more operating parameters of the MS system can include determining the optimal setting values for the one or more operating parameters of the MS system based further on the desired compound characteristic parameters for the at least one of the multiple compounds.

[0017] In various embodiments the method can further include analyzing the sample using the determined optimal operating parameters of the MS system, and, prior to completion of the analysis adjusting at least one of the compound characteristic parameters, re-computing the optimal operating parameter values based, in part, on the adjusted at least one of the compound characteristic parameters, and completing the analysis of the sample using the re-computed optimal operating parameter values.

[0018] In various embodiments, determining the optimal operating parameter values for the one or more operating parameters of the MS system based on at least the detectability data and the one or more evaluation conditions can include determining the optimal operating parametervalues for the one or more operating parameters subject to one or more pre-defined constraints that can including, for example, a) excluding parameter values, for a first operating parameter from the one or more operating parameters, in a value range associated with a drop-off rate in signal intensity, for a first compound of the multiple compounds of interest, that exceeds a predetermined drop-off threshold, and / or b) excluding parameters values, for a second operating parameter from the one or more operating parameters, that result in signal intensity, for a second compound from the multiple compounds, being lower than a pre-determined signal intensity threshold.

[0019] In various embodiments, determining the optimal operating parameter values for the one or more operating parameters can include determining combinations of tested values for the one or more operating parameters of the MS system, including generating for each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters, for each of the multiple compounds of interest, that would result from setting the one or more operating parameters to the tested values of the each combination, and determining the optimal setting values based on the respective scores computed for the each combination of the tested values for the one or more operating parameters.

[0020] In various embodiments, generating for the each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters can include computing a product of expected detected signal intensity of the one or more compounds of interest that would result from setting the one or more operating parameters of the MS system to the tested values of the each combination.

[0021] In various embodiment, the method can further include presenting on a user- interface one or more of, for example, a) at least some of the determined combinations of the tested values for the one or more operating parameters of the MS system, and the respective computed scores for the at least some of the determined combinations, b) at least some of detectability data for one or more of the multiple compounds, and / or c) a graphic representation of pareto front curves comparing detectability data for two or more of the multiple compounds.

[0022] In another aspect, a mass spectrometry (MS) system is provided that includes a mass analyzer, an ion lens assembly to receive ions and direct the received ions along an ion path into the mass analyzer, and a controller to control operation of the MS system. The controller isconfigured to obtain compound analysis data for multiple compounds of interest to be analyzed, obtain compound detectability data for each of the multiple compounds over a plurality of sets of operating parameters of the MS system, determine, based on at least the detectability data and one or more evaluation conditions, optimal operating parameter values for one or more operating parameters to analyze the multiple compounds of interest, and store the optimal operating parameter values corresponding to the sample.

[0023] In various embodiments, the controller can be further configured to retrieve the stored optimal operating parameter values determined for the multiple compounds of interest, controllably adjust the one or more operating parameters of the MS system according to the optimal operating parameter values, and analyze the sample using the determined optimal operating parameter values for the one or more operating parameters of the MS system.

[0024] In various embodiments, the controller configured to obtain the compound detectability data can be configured to exclude one of the plurality of sets of operating parameter values as a possible candidate for the optimal operating parameter values in response to a determination that for at least one of the multiple compounds of interest, a respective detectability value for a particular detectability parameter for the at least one of the multiple compounds of interest is below a target threshold associated with the particular detectability parameter.

[0025] In various embodiments, the controller configured to obtain the compound detectability data can be configured to access a data repository in communication with the MS system, the data repository storing detectability data for a plurality of compounds over the plurality of sets of operating parameters of the MS system, and retrieve detectability data records from the data repository for the multiple compounds of interest, the detectability data records containing the detectability data for the multiple compounds of interest over the plurality of sets of operating parameters.

[0026] In various embodiments, the controller configured to determine the optimal operating parameter values for the one or more operating parameters can be configured to perform one or more mitigation operations in response to a determination that at least one of the multiple compounds of interest has a detectability value, for a respective detectability parameter, that is below a detectability threshold using any combination of detectability data values for themultiple compounds of interest and the one or more evaluation conditions. The one or more mitigation operations can include one or more of, for example, a) triggering a system exception condition, b) relaxing at least one of the one or more evaluation conditions, and re-executing the determining step, or c) presenting on a user-interface multiple sub-optimal proposals of operating parameter values for the one or more operating parameters of the MS system, presenting for each of the sub-optimal proposal a respective number of non-detectable compounds, and receiving user input representative of selection of one of the multiple sub-optimal proposals.

[0027] In various embodiments, the controller configured to determine the optimal operating parameter values for the one or more operating parameters of the MS system based on at least the detectability data and the one or more evaluation conditions can be configured to determine the optimal operating parameter values for the one or more operating parameters subject to one or more pre-defined constraints including to, for example, exclude parameter values, for a first operating parameter from the one or more operating parameters, in a value range associated with a drop-off rate in signal intensity, for a first compound of the multiple compounds of interest, that exceeds a pre-determined drop-off threshold, and / or exclude parameters values, for a second operating parameter from the one or more operating parameters, that result in signal intensity, for a second compound from the multiple compounds, being lower than a pre-determined signal intensity threshold.

[0028] In various embodiments, the controller configured to determine the optimal operating parameter values for the one or more operating parameters can be configured to determine combinations of tested values for the one or more operating parameters of the MS system, including to generate for each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters, for each of the multiple compounds of interest, that would result from setting the one or more operating parameters to the tested values of the each combination, and determine the optimal setting values based on the respective scores computed for the each combination of the tested values for the one or more operating parameters.

[0029] In various embodiments, the controller configured to generate for the each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters can be configured to compute a product of expecteddetected signal intensity of the one or more compounds of interest that would result from setting the one or more operating parameters of the MS system to the tested values of the each combination.

[0030] In various embodiments, the system can further include a user-interface to present one or more of, for example, at least some of the determined combinations of the tested values for the one or more operating parameters of the MS system, and the respective computed scores for the at least some of the determined combinations, at least some of detectability data for one or more of the multiple compounds, and / or a graphic representation of pareto front curves comparing detectability data for two or more of the multiple compounds.

[0031] In a further aspect, a method of operating a mass spectrometry (MS) system to analyze a sample is disclosed that includes receiving a sample containing a plurality of compounds, identifying one or more compounds of interest from the sample, obtaining previously computed optimal operating parameter values, associated with the one or more compounds of interest, for the one or more operating parameters of the MS system, controllably adjusting the one or more operating parameters of the MS system to the optimal operating parameter values, and analyzing the sample using the determined optimal operating parameters values for the one or more operating parameters of the MS system. The optimal operating parameter values, associated with the one or more compounds of interest, are determined based on at least compound detectability data for each of the one or more compounds of interest over a plurality of sets of operating parameters of the MS system and one or more evaluation conditions.

[0032] In various embodiments, obtaining previously computed optimal operating parameter values can include retrieving, from a storage device in communication with the MS system, stored optimal operating parameter values determined for the multiple compounds of interest.

[0033] In various embodiments, the method can further include presenting on a userinterface one or more of, for example, at least some of the optimal operating parameter values for the one or more operating parameters of the MS system, and / or sample analysis results including output data representative of detected compounds from the one or more compounds of interest and detectability levels associated with the detected compounds.

[0034] Further understanding of various aspects of the present teachings can be obtained by reference to the following detailed description in conjunction with the associated drawings, which are described briefly below.Brief Description of the Drawings

[0035] FIG. 1 is a parameter-space graph showing two compounds of interest whose intensity detectability parameter is plotted against temperature.

[0036] FIG. 2 shows the parameter-space graph of FIG. 1, alongside an objective-space graph converted from the parameter-space graph.

[0037] FIG. 3 includes graphs showing conversion of a pair of points from the parameterspace graph into a single point on the objective-space graph.

[0038] FIG. 4 includes graphs showing conversion of another pair of points from the parameter-space graph into another single point on the objective-space graph.

[0039] FIG. 5 is a graph that shows the intensity objective space, with regions of non-optimal objective space points.

[0040] FIG. 6 is a graph that includes the objective space plot of FIGS. 2-5, and illustrates a region of points representing efficient tradeoffs between the intensity levels of compounds A and B.

[0041] FIG. 7 is a graph illustrating selection of an optimal point for a mass spectrometry multi-objective situation.

[0042] FIG. 8 is a graph illustrating selection of another optimal point for a mass spectrometry multi-objective situation.

[0043] FIG. 9 is a schematic diagram of an example of a triple quadrupole mass spectrometer used in a framework implementation to determine operating parameters to allow detection of compounds of interest in a sample.

[0044] FIG. 10 is a flowchart of an example procedure for operating a mass spectrometry (MS) system.

[0045] FIG. 11 is a flowchart of another example procedure for operating an MS system.Detailed Description

[0046] It will be appreciated that for clarity, the following discussion will explicate various aspects of embodiments of the applicant’s teachings, while omitting certain specific details wherever convenient or appropriate to do so. For example, discussion of like or analogous features in alternative embodiments may be somewhat abbreviated. Well-known ideas or concepts may also, for brevity, not be discussed in any great detail. The skilled person will recognize that some embodiments of the applicant’s teachings may not require certain of the specifically described details in every implementation, which are set forth herein only to provide a thorough understanding of the embodiments. Similarly, it will be apparent that the described embodiments may be susceptible to alteration or variation according to common general knowledge without departing from the scope of the disclosure. The following detailed description of embodiments is not to be regarded as limiting the scope of the applicant’s teachings in any manner.

[0047] As used herein, the terms "about" and "substantially equal" refer to variations in a numerical quantity that can occur, for example, through measuring or handling procedures in the real world; through inadvertent error in these procedures; through differences in the manufacture, source, or purity of compositions or reagents; and the like. Typically, the terms "about" and "substantially" as used herein means 10% greater or less than the value or range of values stated or the complete condition or state. For instance, a concentration value of about 30% or substantially equal to 30% can mean a concentration between 27% and 33%. The terms also refer to variations that would be recognized by one skilled in the art as being equivalent so long as such variations do not encompass known values practiced by the prior art.

[0048] As used herein the term "and / or" includes any and all combinations of one or more of the associated listed items and may be abbreviated asAlthough some aspects have been described in the context of an apparatus, it is clear that these aspects also represent a description of the corresponding method, where a block or device corresponds to a method step or a feature of a method step. Analogously, aspects described in the context of a method step also representdescription of a corresponding block or item or feature of a corresponding apparatus. Some or all of the method steps may be executed by (or using) a hardware apparatus, like for example, a processor, a microprocessor, a programmable computer or an electronic circuit. In some embodiments, some one or more of the most important method steps may be executed by such an apparatus.

[0049] The term “component of a mass spectrometer” refers to a device, unit, section, and / or sub-assembly associated with the mass spectrometer. Some examples of a component of a mass spectrometer can include, without limitation, an ion guide, a mass filter, a mass analyzer, etc.

[0050] The present disclosure is generally related to methods and systems for quickly and efficiently developing multi-component (also referred to as “multi-compound”) assays that include compounds of interest that are to be analyzed by a mass spectrometer (e.g., to detect the compounds’ presence, and study their properties, such as their concentration, intensity, etc.) The proposed framework seeks to find an optimal, or near-optimal, set of operating parameters that would allow as many of the compounds in the assay to be detected and analyzed with acceptable sensitivity or LOQ. The proposed framework searches for an optimal combination of operating parameters using detectability data that is available for individual compounds. For example, mass spectrometer manufacturers and users publish detectability data that presents detectability parameters (e.g., detection intensity levels, ionization efficiency levels, limit of quantification levels, signal to noise ratios) for a particular compound, for different combinations of values of controllable operating parameters for a mass spectrometer. That is, operating parameters of an MS system (i.e., adjustable settings, such as gas flow rate, temperature within one or more components of the MS, etc.) that control the behavior of the MS system, affect the detectability parameters for particular compounds. The proposed framework identifies and determines values for MS operating parameters, based on the detectability data (which is provided in the form of heat maps, charts / tables of detectability parameters for different values of the MS operating parameters) that would allow as many of the compounds of interest to be detected by the MS system.

[0051] To illustrate, consider an example in which a mass spectrometer system’s operating parameters relating to gas flow and temperature are controlled. Temperature and gas flow are considered to be source operating parameters that cannot be changed quickly since it takes toolong for heaters and gas supplies to adjust. For large panel assays, the source parameters (heat and gas settings in this example) should therefore be chosen carefully so that all compounds (or, if that is not feasible, then the maximum possible number of compounds) in the assay can be detected. If compound A optimizes at 750° C but has reasonable signal at 350° C, and compound B optimizes at 350° C but has no signal at 750° C, then choosing 350° C or somewhere between 350° C and 750° C may be the best compromise. Determining the optimal compromise is a complex problem. It involves signal response factors, the desired LOQ of each compound, and optimization curves and heat maps for various source parameters for each compound. It is to be noted that in situations where it is not feasible to detect all the compounds of interest using a single assay, it may be necessary to create a second assay that would separately be used detect and analyze a subset of the compounds of interest (with the first assay formed to include a subset with the remainder of the compounds of interest). The formation of a further assay (or even two more assays) may be guided according to the principle that all the original compounds of interest from the original assay need to be detected, and further guided by one or more optimization criteria such as, for example, forming assays with respective compounds of interest that have the largest average detection value for the detection parameters selected (subject to all other evaluation conditions).

[0052] Implementation of the proposed framework and approach to determine the optimal parameter values for the MS system to analyze a sample of compounds begins with a determination of the compounds of interest in the sample that are to be analyzed by the MS system. Thus, multiple compounds of interest that are to be detected / analyzed are defined (e.g., according to any particular MS scan mode, including multiple reaction monitoring, or MRM, transitions, desired limit of quantitation (LOQ) from regulatory guidelines, etc.).

[0053] Having defined the compounds of interest that are to be analyzed, the source parameters, corresponding to adjustable operating parameters (e.g., temperature within various components of the MS system, gas flow rate within one or more of the MS system’s components, etc.) of the particular MS system on which the analysis is to be perform are selected. It is to be noted that the particular MS system may be controllable through a large number of adjustable parameters, but that for the purpose of analyzing a sample only a subset of those parameters may need to be controlled (i.e., determining optimal parameter values only for that subset ofparameters, with the remaining operating parameters being set, for example, to their default values). For the subset of operating parameters, the framework searches for values (deemed the optimal values) that would allow the compounds of interest (defined at the outset of the procedure) to be detected / analyzed. If there is no set of values that would allow all the compounds of interest to be detected, the system searches for sub-optimal solutions that would allow the greatest number of the compounds of interest to be detected. As a next step the parameters may also be adjusted to maximize signal for one or more compounds while maintaining the parameters within a region that allows the greatest number of compounds to be detected.

[0054] Automatic searching for the optimal values of one or more operating parameters of the MS system that are to be controlled is based on detectability data, provided in the form of heat maps, optimization curves (measured using flow injection analysis, in which source parameters for the MS system are adjusted on each injection), charts / tables, etc., that have been determined a priori. Determination of optimal parameter values for one or more source operating parameters for a particular sample / assay can be performed based on a multi- objective optimization methodology that includes one or more evaluation conditions (constraints or criteria). Such multi-objective methodologies can include combinations of:A) Using desired LOQ (relative) and signal response factors, to decide how much signal can be given up for some compounds.B) Avoiding large signal drop-offs (cliffs). That is, some compounds have no signal at some temperatures, and this drop-off may occur quickly. Accordingly, the methodology described herein may be configured to stay away from this drop-off point, even if some signal detectability needs to be sacrificed.C) Measuring the percent of maximum signal for each compounds optimization curves, and choosing a parameter value that maximizes this measurement. For example, a temperature that gives 80% of max signal for five (5) compounds is better than a temperature that gives 100% signal for one compound but only 10% signal for the other four (4).D) Using a tolerance to exclude parameter values that cause detection of a compound to fail. For example, the framework may be configured to avoid parameter values that result inany of the compounds of interest being detected at an intensity level that is less than 30% of the compound’s maximum signal intensity. Thus, when controlling, for example, heater values, only parameter values for the heater parameters that result in detection of all the compounds of interest with at least 30% or more of their maximum intensity should be considered.E) Generating a score / metric as a function of the detectability parameter values associated with one or more operating parameters. Such a score / metric can be used to eliminate certain parameter value combinations, or, alternatively, to rank some possible operating parameter values. An example of a score / metric that can be computed based on detectability parameters is a temperature product score that can be derived based on detectability values of the compounds of interest when considering the operating parameter of MS temperature. Consider a situation where, for a particular temperature operating parameter value, the signal intensity detectability values for all the compounds of interest are multiplied by each other. If the particular temperature value causes some of the compounds of interest to have zero signal, this will cause a score of zero for that temperature value. Consequently, operating parameter value combinations that include the particular temperature that caused the intensity score to drop to 0 can be eliminated from consideration.

[0055] Thus, the proposed framework facilitates the automatic determination of optimal (or near-optimal) source / operating parameters values controlling operation of the MS system to analyze multi-component assays. It is common for one set of operating parameters to represent the best operating values for one compound (i.e., to allow detectability of that compound), but is the worst value for another compound (i.e., the same MS operating parameters may not allow detectability of that other compound). If both compounds need to be detected in the same assay, then an operating parameter values compromise needs to be made. The proposed framework implements the methodology and approaches to determine such compromise operating parameter values for use with an assay with multiple (e.g., in the hundreds) compounds, yielding optimal values (i.e., optimal compromise values) that allow the greatest number (and in some cases all of) the compounds to be detected.

[0056] The proposed framework allows users to develop their own multi component assays, and also increases, for expert users, their confidence in building large multi-component assays. The proposed framework can also be used to troubleshoot instruments or assays. For example, when an assay prepared in one lab (with operating parameters for analyzing the assay in that lab), those same operating parameters for the assay will likely not work as well in a different lab (that uses different equipment). Consequently, the optimization framework described herein would need to be applied for the equipment in the new lab to determine new operating parameters for the equipment of the second lab so that the compounds in the original assay can be detected using the equipment of the second lab. The optimization framework can also be used to highlight differences between the first lab and the new lab (the different optimal parameter values would be indicative of the different apparatus / equipment being used). These differences could point to hardware issues or simply mechanical and / or electrical tolerance ranges across various instruments, or they may indicate that the optimization procedure needs to be run for the new hardware to determine new optimal parameter values for the new hardware.

[0057] Further details regarding the proposed framework for determining optimal operating parameter values for an MS system to analyze compounds in a particular assay will now be discussed with reference to the diagrams of FIGS. 1-11. Particularly, FIG. 1 is a graph 100 showing two compounds of interest (in this case compounds A and B) whose intensity detectability parameter is plotted against temperature (the temperature may represent the temperature in one of the sections or compartments of the MS system such as the ion source region). In this relatively simple example, the assay is first defined with the multiple compounds of interest that are to be analyzed (preferably in a single run). Determination of the compounds to be added to the assay and the compounds of interest to be analyzed may be based on such information as MRM transitions (e.g., to identify the precursor ions and the transitions they will undergo during the MS analysis), desired LOQ level from regulatory guidelines, etc. At this stage, a determination may be made (automatically, using a computing device), using such information as desired LOQ and signal response factors, to decide how much signal can be given up for some compounds. This determination may be based on known compound data (in the form of a heat maps, charts, calibration charts and tables) that detail detectability levels for various detectability parameters (intensity, S / N ratio) of a particular compound at various controllable operating parameters values (and possibly for different sections) of a particular MSsystem. The detectability data for a particular compound thus provides a comprehensive source of information on the expected behavior of various compounds in a mass spectrometer. Detectability data may be obtained from public sources and / or manufacturers that maintain repositories of detectability parameters for different compounds and for different mass spectrometers whose controlled adjustment of their operating parameters, in accordance with the detectability data, can result in a successful, selective detection of compounds of interest (and conversely, in preventing / eliminating certain compounds from being detected).

[0058] In FIG. 1, two plots 110 and 120 of the detected intensity level of two compounds A and B at different temperatures are shown. The plots can be generated based on detectability data for these two compounds, which typically would show detailed information about not only the intensity level, but other detectability parameters and their expected levels at different operating parameter values. As seen in FIG. 1, compound A is readily detectable at relatively low operating temperatures of 280-450°C, but its detectability degrades at higher temperatures. In contrast, compound B has degraded detectability at relatively low temperatures (e.g., 280- 400°C), but its detectability increases for higher temperatures.

[0059] The plots of FIG. 1 define a parameter space in which the temperature-dependent behavior of the intensity level detectability parameter for the two compounds is presented. The parameter space of FIG. 1 is a two-dimensional space. The parameters space may be a multidimensional space with a size that depends on the number of detectability parameters thar are to be presented and analyzed / processed in that space.

[0060] FIG. 2 includes another copy of the graph 100 from FIG. 1, alongside a graph 200 which shows a representation of the information presented in graph 100 in an objective space. In the objective space, the intensity of one of the two compounds A or B are plotted against the intensity of the other compound. Thus, for example, point 210 on the graph 200 shows that the intensity of compound B is 0.8 for an intensity of 0 for compound A.

[0061] FIGS. 3 and 4 include graphs 300 and 400 illustrating the generation of the objective space (both graphs are provided alongside the graph 100, representing the temperature parameter space from which the objective space is generated). As can be seen in FIG. 3, a first point 322 of intensity for compound A is identified in the parameter space graph 100. That point, corresponding to an intensity of approximately 0.5 for compound A, corresponds to atemperature of 550°C. It is to be noted that in the example illustration discussed herein, the temperature parameter may represent the controllable temperature in the ion source section of the mass spectrometer. However, the temperature parameter could, in other illustrative scenarios, represent the temperature in some other chamber / section of the system such as the column holder or auxiliary gas of the system. The adjustable parameter may also include other parameters such as pressure, gas flow rate, or voltage. As further illustrated in FIG. 3, compound B has an intensity of approximately 1.0, at a point 324, corresponding to the temperature of 550°C. Thus, the two points 322 and 324 on the separate plots for compounds A and B in the temperature parameter space are converted / mapped to a single point, 310, in the objective space represented by the graph 300. FIG. 4 shows another example of converting two points from the parameter space to a single point in the objective space. Here, the minimum intensity value of compound A, which is 0, is identified (at point 422). Compound A’s intensity becomes 0 at a temperature of approximately 700°C. At that temperature, compound B has an intensity of approximately 0.85 (as indicated at point 424 within the rectangular box 420). The two points 422 and 424 are mapped to a single point, 410, in the graph 400 representing the objective space, with that point, marking the intensity value of compound B versus the intensity value of compound A, being associated with the temperature 700°C.

[0062] The mapping / conversion of points on the separate plots 110 and 120 (shown in FIG. 1) for the compounds A and B in the parameter space can be repeated for all other plot points in the parameter space, resulting in the generation of the objective space intensity plot shown in FIG. 4 (of which point 410 is one plot point). The objective space plot provides a graphic representation of the behavior of the two compounds relative to each other in the intensity dimension (which is one of multiple possible detectability dimensions).

[0063] FIG. 5 is a graph 500 that includes the intensity objective space for the compounds A and B, and includes regions of non-optimal objective space points within which are objective space points that represent inefficient tradeoffs between the intensity of compound A and compound B. For example, the point 510, corresponding to a temperature of 600°C for which compound B’s detectable intensity is 0.95 and compound A’s detectable intensity of 0.3, is considered to be a non-optimal point because selection of that point (and thus selection of the temperature operating parameter value of 600°C will not provide reliable detection of compoundA), and moreover, up or down adjustments of the temperature parameter value from 600°C will not result in appreciable changes in the detectability values for the compound A (i.e., the rate of change in the detectability value for compound A, per a unit change in temperature, at around the area of point 510 is relatively low)

[0064] On the other hand, the objective space plot constructed for compounds A and B indicates that there several points, or areas of points, that provide more optimal tradeoffs in terms of the intensity levels of the two compounds relative to each other. FIG. 6 includes a graph 600 that includes the objective space plot of FIGS. 2-5. The plot includes a region of points 610 that represent more optimal tradeoffs between the intensity of compounds A and B for points selected in that region. The points within the region 610 correspond to detectable intensity values that are not only reliable, but also represent reasonable tradeoff in the resultant level of change for the intensity level of one compound when the intensity level of the other compound is changed. In other words, the rate of change of intensity values for one compound relative to the other is more efficient than for other regions of the objective space plot. The region 610 shown in FIG. 6 defines the Pareto front for the intensity detectability parameter for the temperature operating parameter. The Pareto front of FIG. 6 defines the area of efficient choices of detectability. It is noted that the Pareto front in this example is for one dimension only, and involves two compounds. What is considered an efficient choice, or efficient tradeoff, becomes more difficult to determine for multi-objective problems involving numerous compounds and many different objectives (e.g., different operating parameters). The present disclosure proposes a robust framework and methodology for dealing with problems involving multiple objectives associated with many items (in this case chemical compounds).

[0065] While the points identified within the region 610 (defining a Pareto front / curve) represent efficient selections, one or more of those points may represent, depending on evaluation criteria and evaluation conditions, more optimal selections than some of the other points within the region 610. One way to control what optimal means is through importance information. The importance information can be specified through assignment of importance weights to the compounds (specifying the level of importance of various compounds can be done at a first stage when information about the compounds of interest, and respective required levels of detectability for one or more of the compounds are provided). For example, and withreference to FIG. 7, showing a graph 700 illustrating selection of an optimal point for a mass spectrometry multi-objective situation, consider a scenario in which compounds A and B are weighed equally (i.e., in tradeoffs between A and B, both compounds are of equal importance). In this scenario, it can be seen graphically that the point 710 of the graph 700 can be considered to be the optimal point, in which sacrificing intensity detectability for compound B will result in approximately the same improvement in the intensity detectability of compound A, and vice versa. As can be seen from FIG. 7, the slope representing the tradeoff between compounds A and B is approximately -1. On the other hand, and with reference to FIG. 8 showing a graph 800 illustrating selection of another optimal point for a mass spectrometry multi-objective situation, consider a scenario in which compound A is weighed more heavily than compound B (i.e., compound A is more important and is favored in tradeoffs). Here it can be seen that the point 820 in the Pareto front may be selected (instead of point 810, which corresponds to the point 710 of FIG. 7). As can be seen at around the point 820, tradeoffs in intensity detectability favor compound A (the slope in the objective space, in which the y-axis corresponds to compound B and the x-axis to compound A, is steeper than it was in the vicinity of the point 710 of FIG. 7). Thus, for the point 820 (and other points on the Pareto front near it) a small sacrifice in the intensity detectability for compound B will result in a more significant improvement in the intensity detectability of compound A, and vice versa.

[0066] As noted, the proposed framework described herein applies a similar analysis to much more complex systems involving hundreds of compounds of interest in an assay, and multiple operating parameters (controlling operation of a mass spectrometer) that define multiple objectives (and thus multi-dimensional objective space). The proposed framework uses various constraints, evaluation conditions, and criteria to find possible combinations of operating parameters for an MS system that would theoretically allow detectability of all (or most of) the compounds of interest. If the determination of such possible combinations yields more than one solution (i.e., there are multiple Pareto points representing different combinations of operating parameters values), selection of one of those possible solutions (that will be considered the optimal solution) can be done according to some scoring methodology / approach (examples of such scoring approaches are discussed below) or through an analysis similar to that discussed in relation to FIGS. 7 and 8 (e.g., finding the most efficient solution, from amongst severalsolutions, offering the most efficient tradeoffs of various detectability parameters for the various compounds of interest).

[0067] Before discussing in more detail additional features of the proposed framework to determine optimal (or near optimal) operating parameter values, an example MS system on which the proposed framework may be implemented will briefly be described. Thus, and with reference to FIG. 9, a schematic diagram of a triple quadrupole mass spectrometry system 900 is shown. It should be noted that implementations of the proposed framework are not restricted to the MS system of FIG. 9 but may be implemented with any type of mass spectrometer. As depicted in FIG. 9, the MS system 900 includes an ion source 902 for generating a plurality of ions. A variety of ion sources can be employed in the practice of the present teachings. Some examples of suitable ion sources can include, without limitation, an electrospray ionization device, a nebulizer assisted electrospray device, a chemical ionization device, a nebulizer assisted atomization device, a chemical ionization device, an atmospheric pressure chemical ionization (APCI) device, a heated nebulizer device, a thermal desorption ion source, a matrix- assisted laser desorption / ionization (MALDI) ion source, a photoionization device, a laser ionization device, a thermospray ionization device, an inductively coupled plasma (ICP) ion source, a sonic spray ionization device, a glow discharge ion source, and an electron impact ion source, among others. The operation of the ion source 902 can be controlled (e.g., via a processor-based controller such as the controller 917 depicted in FIG. 9) to adjust, for example, the types of compounds (molecules) formed, the charge of those compounds, etc. An example of a controllable feature (i.e., operating parameter) of the ion source is the ion source voltage. The ion source 902 may be associated with detectability data for different compounds, with that data stored locally (e.g., at a storage device forming part of the controller 917) or remotely at a server 950 storing a comprehensive catalog of detectability data for different compounds, different operating parameters, and for different mass spectrometer systems. The server 950 can communicate with the controller 917 via a wired or wireless network link.

[0068] With continued reference to FIG. 9, the generated ions pass through an aperture 904a of a curtain plate 904 and an orifice plate 906, which is positioned downstream of the curtain plate 904 and is separated from the curtain plate 904 such that a gas curtain chamber is formed between the orifice and the curtain plate 904. A curtain gas supply (not shown) can provide acurtain gas flow (e.g., of N2) between the curtain plate 904 and the orifice plate 906 to help keep the downstream sections of the mass spectrometer clean by declustering and repelling large neutral particles. The curtain chamber can be maintained at an elevated pressure (e.g., a pressure greater than the atmospheric pressure) while the downstream sections of the mass spectrometer can be maintained at one or more selected pressures via evacuation through one or more vacuum pumps (not shown). Operating parameters affecting the behavior of the curtain gas chamber may include the gas flow rate, the pressure formed within the curtain gas chamber, the temperature in the chamber, etc. Here too, the curtain gas chamber’s operating parameters may be associated with detectability data for various compounds. The ions pass through the orifice plate 906 to be received by an ion optic Qjet, which includes four rods (two of which are shown in FIG. 9) arranged in a quadrupole configuration to which RF voltages can be controllably applied to generate a quadrupolar electric field in the space between the rods. The Qjet optic can capture and focus the ions using a combination of gas dynamics and radio frequency fields. Here too, the Qjet may have one or more controllable operating parameters (e.g., gas pressure, gas flow rate, DC and RF voltage levels and / or profiles) that may be associated with detectability data for various compounds.

[0069] The ions are then transmitted via an ion lens IQ0 into an ion guide Q0, which comprises four rods 908 (two of which are visible in this figure) that are arranged in a quadrupole configuration to form an ion beam for transmission to downstream components of the mass spectrometer. The ion beam exits the Q0 ion guide and is focused through an ion lens IQ1 and a quadrupole prefilter lens STI into a subsequent ion mass filter QI, which includes four rods 910 (two of which are visible in this figure) that are arranged in a quadrupole configuration and to which RF voltages as well as a DC resolving voltage can be applied for radially focusing the ions and selecting ions having a target m / z ratio (herein referred to as precursor ions) as they pass through the QI mass filter. In other embodiments, other multipole configurations, such as a hexapole or an octupole configuration, can be utilized. For example, the quadrupole rod set of QI can be operated as a conventional transmission RF / DC quadrupole mass filter for selecting ions having an m / z value of interest or m / z values within a range of interest. By way of example, the quadrupole rod set of QI can be provided with RF / DC voltages (controlled, for example, by the controller 917) suitable for operation in a mass-resolving mode. For example, parameters of the applied RF and DC voltages can be selected so that QIestablishes a transmission window of chosen m / z ratios, such that these ions can traverse QI largely unperturbed. Ions having m / z ratios falling outside the window, however, do not attain stable ion trajectories within the quadrupole and can be prevented from traversing the quadrupole rod set of QI. It should be appreciated that this mode of operation is but one possible mode of operation for QI. In this embodiment, the QO ion guide and the QI mass filter are disposed in differentially pumped vacuum chambers 951 and 952, respectively. By way of example, the vacuum chamber 951 can be maintained at a pressure in a range of about 3 to about 12 mTorr, and the vacuum chamber 952 can be maintained at a pressure in a range of about 1 to about 50 pTorr. The RF / DC voltage levels for the quadrupole rod set of QI may also be controllable operating parameters for the MS system 900 that are associated with detectability data for different compounds.

[0070] The ions passing through the QI mass filter are focused via a quadrupole pre-filter lens ST2 and an ion lens IQ2A into a collision cell Q2. The Q2 collision cell includes four rods 912 (two of which are visible in this figure) that are arranged in a quadrupole configuration and to which RF voltages can be applied for providing radial confinement of the ions. The rods 912 are disposed within an enclosure 913 such that the pressure within the collision cell can be increased relative to the other stages, e.g., via introduction of a gas (e.g., nitrogen or an inert gas) into the enclosure. While in some embodiments the Q2 collision cell is employed to cause fragmentation of the ions received by the collision cell, in other embodiments, the Q2 collision cell is not utilized for ion fragmentation, but rather for causing, for example, collisional cooling of the ions. Here too, the behavior of the Q2 collision cell is controlled via adjustable operating parameters (e.g., voltage levels of the rods 912, gas flow rate of the N2 gas into the chamber 913, ion energy entering the Q2 region, temperature within the chamber 913, etc.), with one or more of those operating parameters optionally being associated with detectability data (for different compounds and different detectability parameters).

[0071] The fragment ions exiting the Q2 collision cell are received, in some embodiments, by a downstream Q3 quadrupole mass analyzer 916 and are separated based on their m / z ratios to be detected via an ion detector 918. The Q3 quadrupole mass analyzer includes four rods that are arranged in a quadrupole configuration and to which RF and DC voltages can be applied. An analysis module 919 is in communication with the ion detector 918 to receive ion detectionsignals (e.g., electrical pulses) generated by the ion detector 918, and to process those signals to generate a mass spectrum of the detected ions. In some embodiments, the analysis module may also be configured to perform, at least in part, optimal parameter values analysis (based on detectability data for compounds of interest) that would allow detectability of a maximum number (and preferably all of) the compounds of interest. In some embodiments, the analysis module 919 may participate in the implementation of operating parameter values determination framework in concert with the controller 917 and / or remote servers, such as the server 950, that may have more computing resources needed to perform the analysis.

[0072] An RF voltage source 915a and a DC voltage source 915b operating under the control of the controller 917 can apply the requisite RF and DC voltages to various components of the mass spectrometry system 900, including the rods of Qjet, Q0, QI (the mass filter, including the stubbies), Q2 (collision cell), and the Q3 mass analyzer (while FIG. 9 shows electrical connections between the RF and DC sources and just one of the rods of each of the mass spectrometry system’s components, the RF and DC voltage sources may be connected to all the various electrodes of the components of the mass spectrometry system 900). In some embodiments, the QI mass filter, Q2 collision cell, and Q3 mass analyzer may be capacitively coupled to the rods of the Q0 ion guide to receive RF voltages via such capacitive coupling. The RF voltages applied to the rods of the Q0 ion guide, the QI mass filter and the Q2 collision cell provide an electromagnetic field for causing radial confinement of the ions and / or selecting ions with desired m / z ratios to pass through the quadrupole rods. The DC voltage source 915b can apply a DC discriminating voltage to the quadrupole rods of the QI mass filter for selecting ions having m / z ratios of interest. Although only one RF and DC sources are shown in FIG. 9, multiple RF sources and DC sources may be used in embodiments of the mass spectrometry system 900. For example, each of the various sections of the mass spectrometry system 900 may have its own dedicated RF and DC source (as well as, optionally, a dedicated controller) to implement independent voltage control for each of those sections (e.g., the rods of the Qjet, Q0, QI, Q2, and Q3). In yet further embodiments, some sections of the mass spectrometry system 900 may share a pair of independent RF and DC voltage sources, while the remaining sections of the mass spectrometry system 900 may share one or more other (different) pairs of RF and DC sources.

[0073] As further illustrated in FIG. 9, the MS system may further include a user-interface 954, that would typically include an input user interface (such as a keyboard, a mouse, dedicated controls and buttons to set specific operating parameters of the MS system 900, a barcode reader, a camera to capture information such as QR codes, etc.) and an output user interface (such as a display device). The user interface 954 is typically coupled to one of the controller devices of the MS system, such as the processor-based controller 917, and may also be in communication (directly, or indirectly via the controller 917) with the analysis module 919 and / or the remote server 950. A user of the MS system 900 can interact with the system via the user interface 954 to, for example, manually set certain operating parameters of the MS system, to specify assay information (e.g., assay ID number) so that the controller can access (from local storage or from remote storage) any pre-determined operating parameter values that were determined to be optimal (or near-optimal) for analyzing that specific assay, or to run a fresh analysis for a new assay with a new combination of compounds of interest. Typically, if a user wishes to run an analysis for a previously designed assay, it is not necessary to re-determine the optimal parameters values that would result in the greatest number of detection and data acquisition for the compounds of interest. Instead, an identifier or indicator associated with the assay can be submitted (via the user interface), and the corresponding, previously determined operating parameter values associated with that assay can be retrieved from local or remote storage.

[0074] Further details regarding the framework and approaches described herein will now be discussed with reference to FIG. 10, showing a flowchart for an example procedure 1000 of operating a mass spectrometry (MS) system (such as the system 900 depicted in FIG. 9, but the procedure 1000 can be used in conjunction with any mass spectrometry system). The procedure 1000 includes obtaining 1010 compound analysis data for multiple compounds of interest to be analyzed. The analysis data can specify what compounds of interest are provided in the sample, and may optionally include such information as MRM transitions, required limits of quantification (LOQ) (i.e., minimal acceptable detectable compound quantities, such as concentration) for the various compounds, relative ionization efficiencies, and importance weights (e.g., how important is detectability of one compound over another, if any detectability tradeoff needs to be made). In some embodiments, the analysis data may simply be an identifier or indicator that identifies a pre-designed assay with the pre-determined compound information.

[0075] Continuing with FIG. 10, the procedure 1000 further includes obtaining 1020 compound detectability data for each of the multiple compounds of interest over a plurality of sets of operating parameters of the MS system. In some examples, the compound detectability data for each of the multiple compounds of interest represents detectability characteristics for that compound with respect to a set of operating parameters of the MS system. As noted, that set of operating parameters can include any controllable feature of the MS system that affects its behavior and operation, and thus impacts detectability of compounds. For instance, by controlling the voltages applied at different quadrupole rods of different section of an MS system (such as the system 900), different compounds can be removed from the ion stream, while other compounds are allowed to continue down the ion path. Additional examples of the controllable operating parameters include one or more of temperature (e.g., in one or more of the sections of the MS system), gas flow rate (in one or more sections of the MS system), electrospray ionization (ESI) source voltage, atmospheric pressure chemical ionization (APCI) source voltage, source current, LC elution rate, column temperature, column type, solvent type, solvent gradient, and any other slow-changing MS system parameter.

[0076] The detectability data may include experimental data that provides, for particular compounds, detectability levels for different detectability parameters, and for different combinations of operating parameters of a given MS system. This information can be provided in the form of comprehensive charts or tables, in the form of heat maps, calibrations curves (for the MS system), and so on. As noted above, the detectability data may include data for different types of detectability parameters that may be outputted by a particular MS system. Examples of detectability parameters may include one or more of intensity levels (also discussed in relation to the examples of FIGS. 1-8), ionization efficiency levels, limit of quantification (LoQ) levels, signal-to-noise ratio (S / N) levels. The detectability data may be made available by manufacturers of MS systems, and may be accessed from large repositories of experimental data that provides detectability parameter values for various compounds and for different combinations of operating parameter values of the MS system. Repositories of detectability data may be accessed through network connections, and may be downloaded to a system (such as the system 900) that executes the procedures for determining optimal parameter values in the manner described herein. Accordingly, in some embodiments, obtaining the compound detectability data may include accessing a data repository in communication with the MS system, with thedata repository storing detectability data for a plurality of compounds over the plurality of sets of operating parameters of the MS system, and retrieving detectability data records from the data repository for the multiple compounds of interest, with the detectability data records containing the detectability data for the multiple compounds of interest over the plurality of sets of operating parameters.

[0077] In some embodiments, prior to commencing the procedure to determine optimal operating parameter values based on the detectability data, at least some of the detectability data can be eliminated or excluded to thus simplify the parameter value determination procedure (i.e., in that there will be less data to process and analyze, and in that no resources will need to be spent on processing records that do not contribute to the solution). For example, when examining the accessed detectability data, a determination can be made whether, for a certain compound of interest, the detectability value, for a certain combination of operating parameter values, is below some minimal threshold. For example, with respect to the example illustration of FIGS. 1-8, the expected intensity level for compound A for temperature values over 620°C falls under 0.2. If an intensity threshold value of 0.2 is established when accessing or downloading the detectability data parameter value for compound A, all detectability data records that are associated with a temperature of 620°C can be removed from consideration (because the resultant intensity level for compound A at those temperature will be below the threshold value). Thus, in such embodiments, obtaining the compound detectability data may include excluding one of the plurality of sets of operating parameter values as a possible candidate for the optimal operating parameter values in response to a determination that for at least one of the multiple compounds of interest, a respective detectability value for a particular detectability parameter for the at least one of the multiple compounds of interest is below a target threshold associated with the particular detectability parameter.

[0078] Turning back to FIG. 10, the procedure 1000 further includes determining 1030, based on at least the detectability data and one or more evaluation conditions, at least one set of optimal operating parameter values for one or more operating parameters of the MS system to analyze the multiple compounds of interest in the sample. Thus, having accessed detectability data relevant to the compounds of interest (and optionally removing non-germane data, such as data clearly not meeting basic criteria, such as being below some minimal threshold), the detectability data can be analyzed using various evaluation conditions (criteria and constraints). Here, examples of evaluation conditions refers, among other things, to incompatibility betweendetectability values chosen for a first compound (with such detectability values associated with corresponding one or more operating parameter values) and resultant detectability values for another compound, using the same combination of operating parameter values. For example, Compound B has an intensity level value of 0.95 at 600°C. At that operating temperature, compound A has an intensity level od 0.3, which may be deemed to be too low to be a reliable measurement for compound A. Accordingly, this particular detectability data record can be removed from further consideration.

[0079] In some examples, determining the optimal operating parameter values for the one or more operating parameters of the MS system based on at least the detectability data and the one or more evaluation conditions may include determining the optimal operating parameter values for the one or more operating parameters subject to one or more pre-defined constraints that may include, for example, a) excluding operating parameter values, for a first operating parameter from the one or more operating parameters, in a value range associated with a drop-off rate in signal intensity, for a first compound of the multiple compounds of interest, that exceeds a predetermined drop-off threshold, and / or b) excluding parameters values, for a second operating parameter from the one or more operating parameters, that result in signal intensity, for a second compound from the multiple compounds, being lower than a pre-determined signal intensity threshold. Thus, in some situations, operating values combinations that are associated with an intensity level (or some other detectability parameter value) that, while it exceeds some threshold, is located in a range where the detectability values drop off quickly for changes in operating values, and may need to be excluded. In other words, if a detectability tradeoff needs to be made between a first compound and another, having the first compound in an area where such a change in operating parameter value can cause its detectability to drop off precipitously makes selection of that combination of operating values and detectability values non-desirable, and the combination may need to be excluded. In another example, selection of operating values associated with a first compound, that cause a second compound to have detectability levels below a corresponding threshold may also need to be excluded.

[0080] Accordingly, the framework for determining optimal operating parameter values seeks to eliminate many combinations (e.g., because of unreliable detectability levels that are below some threshold). Eventually, a data set including feasible combinations of operationparameter values is identified, and the task turns to determining optimal combinations. As discussed above, there are several procedures or techniques to determine optimal parameter values. In one example technique, the detectability parameters values of the compounds of interest at the particular combination of operating parameter values are combined in some manner. For example, the detectability parameter values (be it intensity level parameter, S / N, ionization efficiency level, or any other detectability parameter) can be multiplied by each other (to form a product of all the detectability parameter values corresponding to the particular combination of operating parameter values). Use of a product of intensity has the advantage that for compounds associated with low detectability values (or even a detectability of 0), the resultant product score will result in a 0 (or very low score) for the respective combinations of operating parameters, in effect removing that combination from further consideration. Other scoring formulations (e.g., one dependent on weights, or one using more complex formulations) may be used. The scored combinations can then be ranked, and the combination of operating parameter values associated with the highest ranking score can be selected as the combination of optimal operating parameter values. In some embodiments, other selection schemes to determine an optimal combination of operating parameter values can be used instead of or in addition to the scheme discussed above. For example, the A highest ranking combinations of operating parameter values can be evaluated to find a combination that is most tradeoff efficient (e.g., in the manner discussed in relation to FIGS. 6-8). In such examples, tradeoff efficiencies for various compounds and for various detectability parameters are evaluated (optionally taking any importance weights assigned to different compounds into account). For example, if, as in the example of FIGS. 7-8, two compounds are considered, and compound A is assigned a weight of 75%, while compound B is assigned a weight of 25% (i.e., compound A is 3 times more important than compound B), then the point 820 of FIG. 8 is considered to be the most efficient since the tradeoffs between compounds A and B’s intensity levels is such that, at around the point 820, a sacrifice of one unit of intensity of compound B will result in an increase of intensity for compound A of about 3 units. As noted, the examples of FIGS. 6-8 represent simple situations, but follow similar principles (on a much larger scale) as finding optimal operating parameter values for multi-compound, multi-objectives situations.

[0081] It is to be noted that one or more combinations of optimal (or near optimal) operating parameters may not be an optimal setting for particular individual compounds (although theparameters may be optimal for some of the multiple compounds, and may be optimal in the aggregate for the multiple compounds of interest). Rather, selected combinations of optimal parameter may simply represent a satisfactory combination (which may be the best of what can be achieved in terms of detectability of compounds) of operating parameters that allows detection of as many of the compounds in the assay as possible at acceptable detection levels. Thus, in some embodiments, for at least one particular compound, from the multiple compounds of interest, at least one of the determined optimal one or more operating parameters is sub-optimal for detecting the at least one particular compound.

[0082] In some situations, it may be necessary to make an adjustment of the compound characteristics parameters if, for example, the procedure to find a good solution is converging to non-optimal solution (as may be determined by a user monitoring progress of the procedure, or as may be determined automatically by the framework). As noted, during the data analysis obtaining stage, various characteristics of the compounds of interest may be specified. These include, for example, a desired limit of quantitation (LOQ) analyte concentration for the at least one compound, signal response factors for the at least one compound, multiple reaction monitoring (MRM) transition parameter for the at least one compound, etc. By changing compound characteristics of the one or more of the compounds of interest, the framework can nudge the emerging solution in a more optimal direction. Thus, in these situations, the procedure 1000 may further include analyzing the sample using the determined optimal operating parameters of the MS system, and, prior to completion of the analysis, adjusting at least one of the compound characteristic parameters, re-computing the optimal operating parameter values based, in part, on the adjusted at least one of the compound characteristic parameters, and completing the analysis of the sample using the re-computed optimal operating parameter values.

[0083] More generally, there may be other circumstances where the framework produces a non-optimal solution, or determines that there are no optimal solutions based on the detectability data for the given set of compounds of interest and for the evaluation conditions being used. For example, consider a situation where upon completing an analysis of the data, it is discovered that at least one of the expected detectability data for one of the compounds is below a threshold value (and therefore, the reliability of solution is reduced). In such situations, the procedure 1000 may further include performing one or more mitigation operations in response to a determination that at least one of the multiple compounds of interest has a detectability value, fora respective detectability parameter, that is below a detectability threshold using any combination of detectability data values for the multiple compounds of interest and the one or more evaluation conditions. The one or more mitigation operations may include one or more of, for example, a) triggering a system exception condition, b) relaxing at least one of the one or more evaluation conditions, and re-executing the determining step, and c) presenting on a userinterface (e.g., a user interface such as the user interface 954 of the MS system 900) multiple sub-optimal proposals of operating parameter values for the one or more operating parameters of the MS system, presenting for each of the sub-optimal proposals a respective number of non- detectable compounds, and receiving user input representative of selection of one of the multiple sub-optimal proposals.

[0084] Upon completion of the optimal parameter values determination stage, the framework described herein (and implemented by the system setup of FIG. 9) will have, in various examples, completed determining combinations of tested values for the one or more operating parameters of the MS system, including generating for each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters, for each of the multiple compounds of interest, that would result from setting the one or more operating parameters to the tested values of the each combination, and determining the optimal setting values based on the respective scores computed for each combination of the tested values for the one or more operating parameters. In some embodiments, the procedure 1000 may then further include presenting on a user- interface (such as the user- interface 954 of the MS system 900) one or more of, for example, a) at least some of the determined combinations of the tested values for the one or more operating parameters of the MS system, and the respective computed scores for the at least some of the determined combinations, b) at least some of detectability data for one or more of the multiple compounds, and c) a graphic representation of optimal output data (also referred to as pareto front or curve) comparing detectability data for two or more of the multiple compounds (as was illustrated in FIG. 6-8).

[0085] A procedure to determine optimal parameter values (in the manner described according to stages 1010-1030 of the procedure) 1000 may be carried out during analysis time (i.e., when an assay is to be analyzed) for small to medium sized assays that do not include a lot of compounds of interests. For large assays, comprising hundreds of compounds of interest, theprocedure is more complex, and requires more processing time. In some cases, the procedure is run offline and / or at a remote server with more computing resources. Once the procedure is completed for a particular assay, the determined optimal parameter values may be stored (locally or remotely) along with an identification number that identifies the particular assay (and thus the compounds of interest) and / or the particular MS system on which the assay is to be analyzed.

[0086] Thus, turning back to FIG. 10, the procedure 1000 further includes storing 1040 the optimal operating parameter values corresponding to the sample.

[0087] At some later point (or immediately after determination of the optimal operating parameters) the assay is to be analyzed by the MS system. A user may enter (through the user interface 954) the assay identifier, and the set of optimal operating parameters for the MS system is retrieved (from remote storage, such as the server 950, or from local controller storage of the controller 917). The controller next automatically controllably adjusts the various control circuitries controlling the operating parameters according to the optimal operating parameter values, and the assay in question is then analyzed. Accordingly, in some embodiments, the procedure may include retrieving the stored optimal operating parameter values determined for the multiple compounds of interest, controllably adjusting the one or more operating parameters of the MS system according to the optimal operating parameter values, and analyzing the sample using the determined optimal operating parameter values for the one or more operating parameters of the MS system. It will be appreciated that if the assay is analyzed immediately before running the analysis, the storing operation (1040) and retrieval operation do not need to be performed.

[0088] With reference next to FIG. 11, a flowchart of another procedure 1100 of operating a mass spectrometry (MS) system to analyze a sample is shown. The procedure 1100 includes receiving 1110 a sample containing a plurality of compounds, and identifying 1120 one or more compounds of interest from the sample. The identification of samples could include providing an assay ID number that represents the content of the sample, namely, the compounds of interest as well as compound characteristics (e.g., concentration, etc.) In some examples, a user may manually enter through a user interface the compounds of interest and / or any compound characteristic.

[0089] The procedure 1100 further includes obtaining 1130 previously computed optimal operating parameter values (e.g., through the framework, approaches, and procedures discussed in relation to FIGS. 1-10), associated with the one or more compounds of interest, for the one or more operating parameters of the MS system, and controllably adjusting 1140 the one or more operating parameters of the MS system to the optimal operating parameter values. The procedure 1100 additionally includes analyzing 1150 the sample using the determined optimal operating parameters values for the one or more operating parameters of the MS system. The optimal operating parameter values, associated with the one or more compounds of interest, are determined based on at least compound detectability data for each of the one or more compounds of interest over a plurality of sets of operating parameters of the MS system and one or more evaluation conditions.

[0090] In some cases, there may not be a set of previously determined optimal parameter values associated with a set of compounds of interest that is to be analyzed. In such circumstances a procedure similar to that discussed in relation to FIGS. 1-10 would need to be executed. Alternatively and / or additionally, a determination may be made as to whether there is a similar, previously analyzed assay to that is similar to the assay that is to be analyzed (e.g., do the previously analyzed assay and the current assay share some threshold number or percentage, e.g., 95% commonality, of compounds of interest?). If there are such previously analyzed assays that are similar in composition to the current assay, the sets of optimal operating parameter values for those assays are retrieved. For each retrieved set of optimal parameter values, further analysis is conducted to determine which compounds are present in the current sample, but are missing from the previously-analyzed assays identified. Subsequently, detectability data associated with compounds in the current assay but not in the previously analyzed assay is retrieved, and a determination is made of whether the operating parameter values for the previously analyzed assay would allow detectability of all (or a substantial number) of the compounds in the current assay. If, after considering all the likely candidates, there is no one candidate with operating parameters values that would still allow analysis and detectability of all the compounds in the current assay, a previous analyzed assay that is most similar to the current assay is selected and its associated optimal operating parameter values are retrieved. The user can then make adjustments to various compound characteristic (e.g., required LOQ) of the compounds in the current assay that are missing from the previously analyzed assay to nudge thecompounds in the current assay towards complete detectability. As noted, in situations where no optimal parameter values solution can be found that would detect all the compounds of interest, it may become necessary to split the assay into two assays to be run separately. The formation of two (or more) assays can be guided based on optimization criteria such as that the two (or more) assays would provide the largest (possibly maximum) average detectability levels for the respective compounds in each of the split assays.

[0091] In some embodiments, obtaining previously computed optimal operating parameter values may include retrieving, from a storage device in communication with the MS system, the stored optimal operating parameter values determined for the multiple compounds of interest. In some embodiments, the procedure 1100 may further include presenting on a user-interface (such as the user interface 954 of FIG. 9) one or more of, for example, at least some of the optimal operating parameter values for the one or more operating parameters of the MS system, and / or sample analysis results including output data representative of detected compounds from the one or more compounds of interest, and detectability levels associated with the detected compounds (subject to all other evaluation conditions, such as the condition regarding minimal detectability threshold for respective compounds).

[0092] Depending on certain implementation requirements, embodiments of the invention can be implemented in hardware and / or in software. The implementation can be performed using a non-transitory storage medium such as a digital storage medium, for example a floppy disc, a DVD, a Blu-Ray, a CD, a ROM, a PROM, and EPROM, an EEPROM or a FLASH memory, having electronically readable control signals stored thereon, which cooperate (or are capable of cooperating) with a programmable computer system such that the respective method is performed. Therefore, the digital storage medium may be computer readable.

[0093] While various embodiments have been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; embodiments of the present disclosure are not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing embodiments of the present disclosure, from a study of the drawings, the disclosure, and the appended claims.

[0094] In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single processor or other processing unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measured cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope.

[0095] Those having ordinary skill in the art will appreciate that various changes can be made to the above embodiments without departing from the scope of the present teachings.

Claims

What is claimed is:

1. A method of operating a mass spectrometry (MS) system to analyze a sample, the method comprising: obtaining compound analysis data for multiple compounds of interest to be analyzed; obtaining compound detectability data for each of the multiple compounds of interest over a plurality of sets of operating parameters of the MS system; determining, based on at least the detectability data and one or more evaluation conditions, at least one set of optimal operating parameter values for one or more operating parameters of the MS system to analyze the multiple compounds of interest in the sample; and storing the optimal operating parameter values corresponding to the sample.

2. The method of Claim 1, further comprising: retrieving the stored optimal operating parameter values determined for the multiple compounds of interest; controllably adjusting the one or more operating parameters of the MS system according to the optimal operating parameter values; and analyzing the sample using the determined optimal operating parameter values for the one or more operating parameters of the MS system.

3. The method of Claim 1, wherein the compound detectability data for each of the multiple compounds of interest represents detectability characteristics for that compound with respect to a set of operating parameters of the MS system.

4. The method of any one of Claims 1 to 3, wherein obtaining the compound detectability data comprises: excluding one of the plurality of sets of operating parameter values as a possible candidate for the optimal operating parameter values in response to a determination that for at least one of the multiple compounds of interest, a respective detectability value for a particular detectability parameter for the at least one of the multiple compounds of interest is below a target threshold associated with the particular detectability parameter.

5. The method of any one of Claims 1 to 3, wherein obtaining the compound detectability data comprises: accessing a data repository in communication with the MS system, the data repository storing detectability data for a plurality of compounds over the plurality of sets of operating parameters of the MS system; and retrieving detectability data records from the data repository for the multiple compounds of interest, the detectability data records containing the detectability data for the multiple compounds of interest over the plurality of sets of operating parameters.

6. The method of Claim 1, wherein determining the optimal operating parameter values for the one or more operating parameters comprises: performing one or more mitigation operations in response to a determination that at least one of the multiple compounds of interest has a detectability value, for a respective detectability parameter, that is below a detectability threshold using any combination of detectability data values for the multiple compounds of interest and the one or more evaluation conditions; wherein the one or more mitigation operations comprises one or more of: a) triggering a system exception condition; b) relaxing at least one of the one or more evaluation conditions, and re-executing the determining step; or c) presenting on a user-interface multiple sub-optimal proposals of operating parameter values for the one or more operating parameters of the MS system, presenting for each of the sub-optimal proposal a respective number of non-detectable compounds, and receiving user input representative of selection of one of the multiple sub-optimal proposals.

7. The method of any one of Claims 1 to 3, wherein obtaining the compound detectability data comprises obtaining a respective mass spectrometer (MS) compound data set for the each of the multiple compounds of interest, wherein the MS compound data set for a particular compound comprises one or more detectability values associated with respective one or more detectability parameters, for different values for the one or more operating parameters of the MS system.

8. The method of Claim 7, wherein the one or more detectability parameters comprise one or more of: intensity level, ionization efficiency level, limit of quantification (LoQ) level, or signal-to-noise ratio (S / N) level.

9. The method of Claim 7, wherein each of the one or more detectability parameters is associated with a set of operating parameters comprising one or more of: temperature, pressure, gas flow rate, electrospray ionization (ESI) source voltage, atmospheric pressure chemical ionization (APCI) source voltage, source current, LC elution rate, column temperature, column type, solvent type, solvent gradient, and any other slow-changing MS system parameter that requires multiple reaction monitoring (MRM) cycles of the MS system.

10. The method of Claim 1, further comprising: setting desired compound characteristic parameters for at least one of the multiple compounds of interest, the compound characteristic parameters include one or more of: a desired limit of quantitation (LOQ) analyte concentration for the at least one compound, signal response factors for the at least one compound, or multiple reaction monitoring (MRM) transition parameter for the at least one compound; wherein determining the optimal operating parameter values for the one or more operating parameters of the MS system comprises determining optimal setting values for the one or more operating parameters of the MS system based further on the desired compound characteristic parameters for the at least one of the multiple compounds.

11. The method of Claim 10, further comprising: analyzing the sample using the determined optimal operating parameters of the MS system; and prior to completion of the analysis: adjusting at least one of the compound characteristic parameters, re-computing the optimal operating parameter values based, in part, on the adjusted at least one of the compound characteristic parameters, and completing the analysis of the sample using the re-computed optimal operating parameter values.

12. The method of any one of Claims 1 to 3, wherein determining the optimal operating parameter values for the one or more operating parameters of the MS system based on at least the detectability data and the one or more evaluation conditions comprises: determining the optimal operating parameter values for the one or more operating parameters subject to one or more pre-defined constraints including: a) excluding parameter values, for a first operating parameter from the one or more operating parameters, in a value range associated with a drop-off rate in signal intensity, for a first compound of the multiple compounds of interest, that exceeds a pre-determined drop-off threshold; and b) excluding parameters values, for a second operating parameter from the one or more operating parameters, that result in signal intensity, for a second compound from the multiple compounds, being lower than a pre-determined signal intensity threshold.

13. The method of any one of Claims 1 to 3, wherein determining the optimal operating parameter values for the one or more operating parameters comprises: determining combinations of tested values for the one or more operating parameters of the MS system, including generating for each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters, for each of the multiple compounds of interest, that would result from setting the one or more operating parameters to the tested values of the each combination; and determining optimal setting values based on the respective scores computed for the each combination of the tested values for the one or more operating parameters.

14. The method of Claim 13, wherein generating for the each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters comprises: computing a product of expected detected signal intensity of the one or more compounds of interest that would result from setting the one or more operating parameters of the MS system to the tested values of the each combination.

15. The method of Claim 13, further comprising presenting on a user-interface one or more of: a) at least some of the determined combinations of the tested values for the one or more operating parameters of the MS system, and the respective computed scores for the at least some of the determined combinations; b) at least some of detectability data for one or more of the multiple compounds; or c) a graphic representation of pareto front curves comparing detectability data for two or more of the multiple compounds.

16. The method of Claim 1, wherein for at least one particular compound, from the multiple compounds of interest, at least one of the determined optimal one or more operating parameters is sub-optimal for detecting the at least one particular compound.

17. A mass spectrometry (MS) system comprising: a mass analyzer; an ion lens assembly to receive ions and direct the received ions along an ion path into the mass analyzer; and a controller to control operation of the MS system, the controller configured to: obtain compound analysis data for multiple compounds of interest to be analyzed; obtain compound detectability data for each of the multiple compounds over a plurality of sets of operating parameters of the MS system; determine, based on at least the detectability data and one or more evaluation conditions, optimal operating parameter values for one or more operating parameters to analyze the multiple compounds of interest; and store the optimal operating parameter values corresponding to the sample.

18. The system of Claim 17, wherein the controller is further configured to: retrieve the stored optimal operating parameter values determined for the multiple compounds of interest; controllably adjust the one or more operating parameters of the MS system according to the optimal operating parameter values; andanalyze the sample using the determined optimal operating parameter values for the one or more operating parameters of the MS system.

19. The system of Claim 17, wherein the controller configured to obtain the compound detectability data is configured to: exclude one of the plurality of sets of operating parameter values as a possible candidate for the optimal operating parameter values in response to a determination that for at least one of the multiple compounds of interest, a respective detectability value for a particular detectability parameter for the at least one of the multiple compounds of interest is below a target threshold associated with the particular detectability parameter.

20. The system of Claim 17, wherein the controller configured to obtain the compound detectability data is configured to: access a data repository in communication with the MS system, the data repository storing detectability data for a plurality of compounds over the plurality of sets of operating parameters of the MS system; and retrieve detectability data records from the data repository for the multiple compounds of interest, the detectability data records containing the detectability data for the multiple compounds of interest over the plurality of sets of operating parameters.

21. The system of Claim 17, wherein the controller configured to determine the optimal operating parameter values for the one or more operating parameters is configured to: perform one or more mitigation operations in response to a determination that at least one of the multiple compounds of interest has a detectability value, for a respective detectability parameter, that is below a detectability threshold using any combination of detectability data values for the multiple compounds of interest and the one or more evaluation conditions; wherein the one or more mitigation operations comprises one or more of: a) triggering a system exception condition; b) relaxing at least one of the one or more evaluation conditions, and re-executing the determining step; orc) presenting on a user-interface multiple sub-optimal proposals of operating parameter values for the one or more operating parameters of the MS system, presenting for each of the sub-optimal proposal a respective number of non-detectable compounds, and receiving user input representative of selection of one of the multiple sub-optimal proposals.

22. The system method of Claim 17, wherein the controller configured to determine the optimal operating parameter values for the one or more operating parameters of the MS system based on at least the detectability data and the one or more evaluation conditions is configured to: determine the optimal operating parameter values for the one or more operating parameters subject to one or more pre-defined constraints including: a) exclude parameter values, for a first operating parameter from the one or more operating parameters, in a value range associated with a drop-off rate in signal intensity, for a first compound of the multiple compounds of interest, that exceeds a pre-determined drop-off threshold; and b) exclude parameters values, for a second operating parameter from the one or more operating parameters, that result in signal intensity, for a second compound from the multiple compounds, being lower than a pre-determined signal intensity threshold.

23. The system of Claim 17, wherein the controller configured to determine the optimal operating parameter values for the one or more operating parameters is configured to: determine combinations of tested values for the one or more operating parameters of the MS system, including to generate for each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters, for each of the multiple compounds of interest, that would result from setting the one or more operating parameters to the tested values of the each combination; and determine the optimal setting values based on the respective scores computed for the each combination of the tested values for the one or more operating parameters.

24. The system of Claim 23, wherein the controller configured to generate for the each combination of tested values a respective score computed based on expected detectability level of one or more detectability parameters is configured to: compute a product of expected detected signal intensity of the one or more compounds of interest that would result from setting the one or more operating parameters of the MS system to the tested values of the each combination.

25. The system of Claim 24, further comprising a user-interface to present one or more of: a) at least some of the determined combinations of the tested values for the one or more operating parameters of the MS system, and the respective computed scores for the at least some of the determined combinations; b) at least some of detectability data for one or more of the multiple compounds; or c) a graphic representation of pareto front curves comparing detectability data for two or more of the multiple compounds.

26. The system of Claim 17, wherein for at least one particular compound, from the multiple compounds of interest, at least one of the determined optimal one or more operating parameters is sub-optimal for detecting the at least one particular compound.

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