Disclosed is a method for determining an operating flow rate for a chromatographic column (4) in an HPLC system (1). The method comprises: measuring/calculating a pressure of the system (1) without the chromatographic column (4) for one or more flow rates; fitting a function to the flow rate(s) and corresponding pressure(s), calculating from the function and a predetermined recommended flow rate for the chromatographic column (4) a system pressure drop at the predetermined recommended flow rate. An operating flow rate is determined by summing the system pressure drop and a maximal column pressure limit, and determining a contribution of the system pressure drop to the summed pressure. If this contribution exceeds 1% an operating flow rate for the column is determined to a flow rate that corresponds to a pressure at a pressure monitor arranged before the column that is lower than the predetermined maximum column pressure limit.

A method for scientific instrument support includes obtaining a chromatographic data. The method includes one of (a) calculating an intensity score for the chromatographic data and identifying an injection miss when the intensity score is below a score threshold or (b) applying a machine learning model to classify the chromatographic data. The method further includes notifying a user of an injection miss or injection error.

The present invention discloses a method for realizing multi-column continuous chromatography design and analysis based on a chromatography model, and a method for realizing multi-column continuous chromatography design and analysis based on an artificial neural network. The method based on the chromatography model includes the following steps: step 101, experimental breakthrough curve fitting: performing fitting using a chromatography model to obtain model parameters; step 102: breakthrough curve prediction: substituting the model parameters into the chromatography model to obtain a breakthrough curve under different operation conditions; step 103, process analysis of continuous chromatography: substituting the predicted breakthrough curve and the continuous chromatography operation parameters into a continuous chromatography model to obtain performance indexes such as process productivity and resin capacity utilization; and step 104, operation space optimization of continuous chromatography: obtaining the operation space of the continuous chromatography design parameters based on a specific separation target. The method based on the artificial neutral network completes the respective steps above by replacing the chromatography model with artificial neural network.

Aspects of the present disclosure relate to systems and methods for manufacturing biologically-produced pharmaceutical products. Some of the systems described herein comprise an upstream component comprising a bioreactor and at least one filter (e.g., a filter probe) integrated with a downstream component comprising a purification module comprising at least a first partitioning unit and a second partitioning unit. In some embodiments; these integrated biomanufacturing systems may be operated under continuous or conditions and may be capable of efficiently producing pure, high-quality pharmaceutical products.

A method for monitoring an analyzer including a liquid chromatography device (LC) having at least two liquid chromatography (LC) streams, the method including continuously monitoring one or more parameters in measurement data of samples in each of the at least two LC streams, the one or more parameters being independent of an analyte concentration of the respective sample, determining if the one or more monitored parameters show an expected behavior and triggering a response upon detection that the one or more monitored parameters deviate from the expected behavior.

The present invention relates to a liquid chromatography system (90) configured to operate with at least one column and configured for purification of a sample comprising a target product using a predefined process. The liquid chromatography system comprises a controller (91) configured to: control the operation of the chromatography system to run the predefined process; retrieve column data accessible from a data storage, the column data being specific to each column; and adapt at least one process parameter of the predefined process for each column based on column data. Whereby the predefined process is adapted to each column to obtain the target product and maintain the performance of the liquid chromatography system.

A method for applying a heating sequence for a modulator includes, during a first period of time, heating a first heating zone disposed along a length of the modulator without heating a second heating zone to cause a sample trapped from a first transfer line at an entrance of the modulator to move from the first heating zone to the second heating zone. The method also includes, during a second time period, withdrawing the heating of the first heating zone to prevent the sample from entering the modulator from the first transfer line. During a third time period, the method includes heating the second heating zone without heating the first heating zone to reinject the sample into a second transfer line.

A chromatography system includes an electrolytic eluent generator; a first valve configured to switch between an operating position which directs an output of the electrolytic eluent generator to a continuously generated trap column and a waste position which directs the output of the electrolytic eluent generator to waste; the continuously regenerated trap column; a degasser; a sample injector including a sample injector valve assembly, the sample injector valve assembly configured to switch between an operation mode which directs an output of the degasser to a separation column, a load mode which loads a sample onto the separation column, and a regenerant mode which directs the output of the degasser to a regenerant line; the separation column; a suppressor; and a detector.

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 method of performing mass spectrometry includes accumulating, over an accumulation time, ions produced from components eluting from a chromatography column and transferring the accumulated ions to a mass analyzer. During an acquisition, a mass spectrum of detected ions derived from the transferred ions is acquired. An elution profile is obtained from a series of acquired mass spectra including the acquired mass spectrum and a plurality of previously-acquired mass spectra. The elution profile includes a plurality of detection points representing intensity of the detected ions as a function of time. A current signal state of the elution profile is classified based on a subset of detection points included in the plurality of detection points. The accumulation time for a next acquisition of a mass spectrum is set based on the classified current signal state of the elution profile.