A chromatographic data system processing apparatus includes a standard sample time table for prestoring a first retention time and a first allowable width of each peak of specific components of a standard sample, a determination unit for determining whether a number of peaks coincides with a specified number when a peak cannot be identified, an alteration unit for altering the standard sample time table by increasing the first allowable width of a specific component to an altered allowable width, an identification unit for identifying the peaks based on the altered standard sample time table when all peaks fall within a range of the altered allowable width, and a setting unit for acquiring an actually-measured retention time of the peaks, and setting a measurement sample time table based on the actually-measured retention time and a second allowable width when the peaks are identified based on the altered standard sample time table.

A program for assisting in determining a combination of parameter values of analysis conditions suitable for an intended analysis, makes a computer operate as: a graph-displaying section which displays, on a screen, a graph created based on data collected with a chromatograph device, to show a relationship between the parameter values and an analysis result obtained with the chromatograph device or a result of analytical processing based on the analysis result; an input-receiving section which receives a user's input of a constraint condition which specifies the upper/lower limit or range of a numerical value representing the analysis result or analytical-processing result; a search-conducting section which conducts a search for a combination of the parameter values which yields the analysis result or analytical-processing result in which the numerical value satisfies a predetermined search condition under the constraint condition; and a search-result-displaying section which displays a search result on the graph.

An operational condition of a liquid chromatography (LC) system (2110) is detected and displayed without user intervention. A plurality of pressure measurements over time are received from a pressure sensor (2119) of the LC system. A processor (2140) calculates values from the measurements for six parameters including a beginning pressure (P.sub.B), an ending pressure (P.sub.E), an average pressure (T.sub.1) for a first half of the separation, an average pressure (T.sub.2) for a second half of the separation, a ratio T.sub.1/P.sub.B, and a ratio T.sub.2/P.sub.B. The values of the six parameters are classified as one of one or more operational conditions of the LC system using a machine learning model. The machine learning model is created from values of the six parameters calculated from known separations for each of the one or more operational conditions. The operational condition found from the classification is displayed on a display device (2141).

A data storage part (2) that stores responses, which are a plurality of analysis results obtained by a plurality of analyses executed under a plurality of analysis conditions, and factors, which are a plurality of parameters included in the analysis conditions, in a manner that the responses and the factors are associated with each other, a data processor (4) configured to use at least one of the factors as a variable and to create an approximate expression indicating a relationship between the variable and the responses, and an information input device (6) for a user to input information to the data processor (4). The data processor (4) is configured to execute a variable setting step of causing the user to set at least one of the factors to be the variable, a structure setting step of causing the user to optionally set a structure of a model expression that is a basis of the approximate expression using the variable set in the variable setting step, a model expression determination step of determining the model expression based on the structure set by the user in the structure setting step, and an approximate expression determination step of determining a coefficient of each term constituting the model expression determined in the model expression determination step by regression analysis, and thereby determining the approximate expression.

An analysis assistance device includes an estimator that estimates a distribution of measurement quality indicator data using a regression analysis by using a plurality of analysis condition data pieces provided to an analysis device and a plurality of measurement data pieces obtained by the analysis device based on the plurality of analysis condition data pieces, an analysis assistance information displayer that displays the distribution on a display, and a saver that saves an analysis condition data piece of a point of interest designated in the distribution in a storage device in response to a saving operation.

In a method for facilitating selection of chromatography parameters for manufacturing a therapeutic protein, one or more process parameter values associated with a hypothetical chromatography process, and one or more molecular descriptors descriptive of the therapeutic protein, are received. The method also includes predicting a performance indicator for the hypothetical chromatography process at least by analyzing the one or more process parameters and the one or more molecular descriptors using a machine learning model. The machine learning model is a regression tree model, an extreme gradient boost model, or an elastic net model. The method also includes causing the predicted performance indicator, and/or an indication of whether the predicted performance indicator satisfies one or more acceptability criteria, to be presented to a user via a user interface.

An automated method of monitoring a state of an analyzer is provided including a mass spectrometer (MS) with an electrospray ionization (ESI) source coupled to a liquid chromatography (LC) stream, including monitoring an electrospray ionization current of the ESI source and identifying a condition of multiple conditions of the analyzer based on the monitored ionization current of the ESI source, one of the conditions being a presence of a dead volume in a liquid chromatography stream of the analyzer downstream of an LC column of the LC stream.

A non-transitory computer readable medium (CRM) storing computer readable program code for monitoring a state of a chromatography apparatus embodied therein that: receives one or more monitoring conditions that each include a determination condition for parameters related to measurements taken using the chromatography apparatus; and displays, in parallel and using a combination operational expression: a first conditional expression based on at least one of the monitoring conditions that make up a first combined conditional expression, wherein the first combined conditional expression is based on a first combined monitoring condition that combines all of the received monitoring conditions, and a second conditional expression based on at least one of the monitoring conditions associated with the first conditional expression.

The disclosure generally relates to methods and systems for determining multi-column chromatography process configuration for capturing antibodies. Conventional approaches for design of MCC configuration are limited to rule based, either driven by UV spectroscopic measurements or by performing number of experiments, which involves a lot of material costs and time utilization. The present disclosure solves the technical problem of identifying the operational conditions that optimized the MCC process and the MCC configuration. A multi-objective optimization function defined with one or more decision variables associated with the operating conditions is considered to determine the optimal MCC configuration, while satisfying purification goals. The one or more key performance measures of the MCC process comprises a productivity, a capacity utilization, a product yield, and a product purity. The significant amount of time and the material cost invested for designing the optimum MCC configuration is decreased by the present disclosure.

An analysis assistance device includes an estimator that estimates distribution of measurement quality index data using a plurality of analysis condition data to be provided to an analysis device and a plurality of measurement data obtained in the analysis device based on the plurality of analysis condition data, a calculator that calculates the measurement quality index data from the measurement data obtained from the analysis device, and a comparison outputter that compares and outputs for display the measurement quality index data estimated by the estimator and the measurement quality index data calculated by the calculator.