Generally discussed herein are systems, apparatuses, and methods that relate to detecting an error in a laboratory analyzer. A device may include an average of deltas (AoD) module to receive pairs of consecutive measurement values of an analyte of one or more patients, each pair of consecutive measurement values including a first measurement of an analyte obtained from a patient of the one or more patient at a first time and a second measurement of an analyte obtained from the patient at a second time after the first time, determine a time delta between each pair of consecutive measurement values, determine whether the time delta is within a specified time window, determine a measurement value deltas between each pair of consecutive measurement values that includes a time delta with the specified time window, and determine an AoD using the determined measurement value deltas.

A laboratory automation device (10) comprises a plurality of device components (14, 16), which are controlled by digital control commands (26), the digital control commands (26) being generated by a controller (20) of the laboratory automation device (10) from assay definition data (38) defining an assay procedure for the laboratory automation device (10). A method for monitoring the laboratory automation device (10) comprises: receiving the control commands (26); inputting the control commands (26) into a simulation model (46) of the laboratory automation device (10), the simulation model (46) comprising model components (54) for at least some of the device components (14, 16); updating the simulation model (46) by simulating state changes of the device components (14, 16) based on the control commands (26); determining a desired processing state (60) of the laboratory automation device (10) from the assay definition data (38) and a virtual processing state (62) of the laboratory automation device (10) from the updated simulation model (46); and comparing the desired processing state (60) with the virtual processing state (62) for deciding, whether the assay procedure was correctly executed.

Discussed herein are methods and apparatuses to produce profiles for scientific measurement equipment, and to use those profiles for various purposes in using, designing, calibrating and managing such equipment, such as to carry out critical laboratory testing. In this approach, either the analyzers' quality control data or serial patient data are numerically reduced to generate graphical precision profiles. Precision profiles for serial patient data show increased (im)precision vs time implying increased patient variation over increased time. Precision profiles for quality control data, according to one implementation, can demonstrate three different zones: 1) increased imprecision for quality control determinations that are close spaced (implies the discovery of an error condition and rapid reanalysis, 2) the usual imprecision and 3) a zone of increased imprecision which indicates either a need for a quality control analysis or re-calibration.

Methods and systems for determining a dose of an analyte in an unknown sample on an instrument, such as a nucleic acid analyzer, immunoassay analyzer, or clinical chemistry analyzer using a reagent from a selected assay lot are described. The methods and systems use core dose-response information based on measurements of response values to a set of calibrators on a plurality of other instruments and assay lot-specific response information to calibrate the instrument.

A method for classifying a specific pipetting procedure of a laboratory automation device comprises: determining a plurality of pressure curves of a plurality of pipetting procedures, which are equivalent to the specific pipetting procedure; determining a median curve from the plurality of pressure curves, wherein for each time point of the median curve, a median value of the values of the plurality of pressure curves at this time point is calculated; determining a median curve range containing the median curve; controlling the laboratory automation device to perform the specific pipetting procedure and measuring a specific pressure curve during the specific pipetting procedure; determining a deviation value of the specific pressure curve with respect to the median curve range, wherein the deviation value is indicative of the specific pressure curve leaving the median range; and classifying the specific pipetting procedure as erroneous, when the deviation value is greater than a threshold.

A method for performing quality control on a diagnostic analyzer includes receiving control measurement values from each of a plurality of diagnostic analyzers. A quality control measurement value is received from a target diagnostic analyzer. The quality control measurement value is compared with statistical criteria associated with the plurality of quality control measurement values received from the plurality of diagnostic analyzers. A comparison result is communicated to a user interface associated with the target diagnostic analyzer.

The present invention is a comprehensive method and related system comprising software, instrumentation, consumables and services (calibration, training, and repair) in a platform system for management of handheld pipettes and automated liquid handling systems (ALBS). The system optimizes confidence in test results, control of liquid handling processes, productivity, and simplicity in operation, by significantly improving the experience in ownership, usage, and service of liquid handling instruments. The system is a turnkey solution integrating multiple technology approaches to provide real-time on-line feedback to the devices and to device users, as well as real-time connection to Electronic Lab Notebooks (ELN), Laboratory Information Management Systems (LEVIS) and training databases.

A computer-implemented method of calibrating an in-vitro diagnostic analyzer is disclosed. The method comprises executing a multi-point calibration procedure comprising measuring a plurality of calibrator levels and thereby obtaining a plurality of respective calibration points. The method further comprises calculating a result of the multi-point calibration procedure and determining failure or passing of the multi-point calibration procedure based on the calculated result. In case of failure of the multi-point calibration procedure, the method comprises determining if failure is related to one or more individual failed calibration point(s), and in the affirmative, triggering a repetition of measuring the calibrator level(s) only with respect to the failed calibration point(s) and re-calculating the result of the multi-point calibration procedure after replacing only the failed calibration point(s) with the newly obtained calibration point(s).

A method for performing quality control on a diagnostic analyzer includes receiving control measurement values from each of a plurality of diagnostic analyzers. A quality control measurement value is received from a target diagnostic analyzer. The quality control measurement value is compared with statistical criteria associated with the plurality of quality control measurement values received from the plurality of diagnostic analyzers. A comparison result is communicated to a user interface associated with the target diagnostic analyzer.

A method for performing quality control on a diagnostic analyzer includes receiving control measurement values from each of a plurality of diagnostic analyzers. A quality control measurement value is received from a target diagnostic analyzer. The quality control measurement value is compared with statistical criteria associated with the plurality of quality control measurement values received from the plurality of diagnostic analyzers. A comparison result is communicated to a user interface associated with the target diagnostic analyzer.