The present disclosure discusses a method of separating a sample of tyrosine kinase inhibitors or metabolites of tyrosine kinase inhibitors which includes injecting the sample into the chromatographic system having one or more low-bind coated surfaces along the flow path; flowing the sample through the chromatographic system; separating the sample; and analyzing the separated sample. Consequently, the sample does not bind to the low-binding surface coatings (e.g., alkylsilyl coatings) of the flow path. The applied coating can reduce peak tailing and decrease carryover for tyrosine kinase inhibitor samples during chromatographic analysis.

The present disclosure discusses a method of separating a sample of tyrosine kinase inhibitors or metabolites of tyrosine kinase inhibitors which includes injecting the sample into the chromatographic system having one or more low-bind coated surfaces along the flow path; flowing the sample through the chromatographic system; separating the sample; and analyzing the separated sample. Consequently, the sample does not bind to the low-binding surface coatings (e.g., alkylsilyl coatings) of the flow path. The applied coating can reduce peak tailing and decrease carryover for tyrosine kinase inhibitor samples during chromatographic analysis.

A controller (50) of a liquid chromatograph (1) is configured to execute, as an analysis operation in an analysis unit (3), a sample injection step of bringing a high-pressure valve (10) into a loading state, sucking a sample from a tip of a needle (12) to hold a sample in a sampling channel (2), then connecting the sampling channel (2) to an injection port (16) and bringing the high-pressure valve (10) into an injecting state, and supplying a mobile phase from a liquid supplier (6), thereby injecting a sample held in the sampling channel (12) into an analysis channel (4), and an analysis step of separating components of a sample injected into the analysis channel (4) in a separation column (14) by bringing the high-pressure valve (10) in the loading state and supplying the mobile phase from the liquid supplier (6) after the sample injection step is ended. In a case where at least a predetermined condition is satisfied, after the analysis step is ended, the controller is configured to execute, as the analysis operation, a system cleaning step of cleaning a liquid flowing route from the sampling channel (2) to the analysis channel (4) by connecting the sampling channel (2) to the injection port (16) and bringing the high-pressure valve (10) into the injecting state, and supplying the mobile phase and/or a cleaning liquid from the liquid supplier (6).

Methods, systems and devices that allow independently applied pressures to a BGE reservoir and a sample reservoir for pressure-driven injection that can inject a discrete sample plug into a separation channel that does not require voltage applied to the sample reservoir and can allow for in-channel focusing methods to be used. The methods, systems and devices are particularly suitable for use with a mass spectrometer.

Methods, systems and devices that allow independently applied pressures to a BGE reservoir and a sample reservoir for pressure-driven injection that can inject a discrete sample plug into a separation channel that does not require voltage applied to the sample reservoir and can allow for in-channel focusing methods to be used. The methods, systems and devices are particularly suitable for use with a mass spectrometer.

Techniques and apparatus for evaluating analytical device performance and data quality are described. In one embodiment, for example, an apparatus may include at least one memory, and logic coupled to the at least one memory. The logic may be configured to generate an analysis method to be performed by an analytical device, the analysis method comprising a plurality of method segments comprising at least one performance assessment process and at least one sample analysis process, and link the at least one performance assessment process with the at least one sample analysis process. Other embodiments are described.

Techniques and apparatus for evaluating analytical device performance and data quality are described. In one embodiment, for example, an apparatus may include at least one memory, and logic coupled to the at least one memory. The logic may be configured to generate an analysis method to be performed by an analytical device, the analysis method comprising a plurality of method segments comprising at least one performance assessment process and at least one sample analysis process, and link the at least one performance assessment process with the at least one sample analysis process. Other embodiments are described.

A switching mechanism 110 can perform switching to a pressurized state in which gas is supplied from a pipe 203 to an insertion tube 101, or a derivation state in which gas in a head space 23 that is pressurized is derived from the insertion tube 101 to the pipe 207 via a collection unit 104. The switching mechanism 110 includes a discharge valve 103 that puts the insertion tube 101 and the pipe 207 into a non-communication state in the pressurized state and puts the insertion tube 101 and the pipe 207 into a communication state in the derivation state. A resistance pipe 206 supplies gas to a channel between the collection unit 104 and the discharge valve 103 in the derivation state.

Exemplary embodiments provide methods, mediums, and systems for visualization and advanced data science on information collected in an analytical data system. Embodiments identify correlations and patterns in chromatography metadata around areas of potential user error. Correlations between these data sources may point to compliance risk areas. Metadata from the analytical system may be combined with other data sources and/or analytical data to correlate an analytical outcome with compliance artifacts. Supervised and/or unsupervised machine learning techniques may be used to combine these data source and learn correlations between them and compliance risks. The results of these analyses may be displayed on a dashboard, allowing a user to visualize compliance risks across an entire enterprise or supply chain. Automatic notifications of compliance risks may be generated and presented on a user interface. A system may also use pattern recognition to provide insights around potential compliance risks that have not yet occurred.

Exemplary embodiments provide methods, mediums, and systems for visualization and advanced data science on information collected in an analytical data system. Embodiments identify correlations and patterns in chromatography metadata around areas of potential user error. Correlations between these data sources may point to compliance risk areas. Metadata from the analytical system may be combined with other data sources and/or analytical data to correlate an analytical outcome with compliance artifacts. Supervised and/or unsupervised machine learning techniques may be used to combine these data source and learn correlations between them and compliance risks. The results of these analyses may be displayed on a dashboard, allowing a user to visualize compliance risks across an entire enterprise or supply chain. Automatic notifications of compliance risks may be generated and presented on a user interface. A system may also use pattern recognition to provide insights around potential compliance risks that have not yet occurred.