Abstract: A well plate cover includes a base defining a base plane, and a plurality of insertion elements. At least a portion of each of the insertion elements is transparent. Each of the insertion elements is coupled to the base, and extends, in a direction orthogonal to the base plane, from the base to a distal end surface of the insertion element. The distal end surface of each of the insertion elements includes an apex that, when the respective insertion element is inserted into a well of a well plate, extends further into the well than any other portion of the distal end surface. The apex is a point, a line, or a plane having a diameter that is less than one half of a maximum diameter of the distal end surface.

Abstract: A method for monitoring and/or controlling a biopharmaceutical process includes querying, based on a first spectral scan vector of the biopharmaceutical process, an observation database comprising observation data sets associated with past scans. Each of the observation data sets includes spectral data and a corresponding actual analytical measurement. Querying the observation database includes determining first parameters defining a set of distributions for the first spectral scan vector, and selecting as training data, from among the observation data sets, particular observation data sets based on (i) the first parameters and (ii) other parameters defining respective sets of distributions for the observation data sets. The method also includes calibrating, using the selected training data, a local model specific to the biopharmaceutical process.

Abstract: A method for detecting cytopathic effect (CPE) in a well sample includes generating a well image depicting a well containing cells and a medium (and possibly viruses), and pre-processing the well image at least by partitioning the well image into sub-images each corresponding to a different portion of the well. The method also includes, for each of some or all of the sub-images, determining, by analyzing the sub-image using a convolutional neural network, a respective score indicative of a likelihood that any cells in the portion of the well corresponding to the sub-image exhibit CPE. The method further includes determining a CPE status of the cells contained in the well based on the respective scores for the sub-images, and generating output data indicating the CPE status.

Abstract: A method of controlling a cell culture process uses hybrid predictive modeling in a model predictive controller. The method includes, for multiple time intervals, obtaining current values of cell culture attributes associated, and generating a control value for a physical input to the cell culture process. Generating the control value includes predicting future values of the cell culture attributes based on the current values, by using one or more data-driven models to predict future values of a first one or more attributes of the cell culture attributes, and using one or more first principle models to predict future values of a second one or more attributes of the cell culture attributes. Generating the control value also includes determining the control value by optimizing an objective function subject to the predicted future values. The method also includes using the control value to control the physical input to the cell culture process.

Abstract: A method of controlling a cell culture process includes, for each time interval of one or more time intervals during the cell culture process, obtaining current values of one or more cell culture attributes associated with a cell culture, predicting one or more future values of a particular cell culture attribute associated with the cell culture, and controlling one or more physical inputs to the cell culture process. Predicting the future value(s) includes applying the current values of the cell culture attribute(s), and an earlier value of at least one of the cell culture attributes, as inputs to a data-driven predictive model using historical data. Controlling the physical input(s) includes applying the future value(s) as inputs to a model predictive controller.

Abstract: A method of facilitating a growth assessment for a cell line includes generating an image of a well that contains a medium that was inoculated with at least one cell of the cell line. The method also includes generating a down-sampled segmentation map comprising pixels that indicate an inferred presence or absence of a cell colony in corresponding portions of the well image. Generating the down-sampled segmentation map includes inputting the well image to a fully convolutional neural network having a plurality of convolutional layers. The method also includes (i) determining, by inputting colony size information (including the down-sampled segmentation map and/or a pixel count derived therefrom) to a cell growth assessment algorithm, a growth classification or score for the cell line, and causing a display of the growth classification or score, and/or (II) causing a display of the colony size information to facilitate a manual cell growth assessment.

Abstract: A well plate cover includes a base defining a base plane, and a plurality of insertion elements. At least a portion of each of the insertion elements is transparent. Each of the insertion elements is coupled to the base, and extends, in a direction orthogonal to the base plane, from the base to a distal end surface of the insertion element. The distal end surface of each of the insertion elements includes an apex that, when the respective insertion element is inserted into a well of a well plate, extends further into the well than any other portion of the distal end surface. The apex is a point, a line, or a plane having a diameter that is less than one half of a maximum diameter of the distal end surface.

Abstract: A method for detecting cytopathic effect (CPE) in a well sample includes generating a well image depicting a well containing cells and a medium (and possibly viruses), and pre-processing the well image at least by partitioning the well image into sub-images each corresponding to a different portion of the well. The method also includes, for each of some or all of the sub-images, determining, by analyzing the sub-image using a convolutional neural network, a respective score indicative of a likelihood that any cells in the portion of the well corresponding to the sub-image exhibit CPE. The method further includes determining a CPE status of the cells contained in the well based on the respective scores for the sub-images, and generating output data indicating the CPE status.

Abstract: A method for facilitating clone selection includes generating time-sequence images of a well containing a medium, including a first image and a later, second image. The method also includes detecting, by one or more processors analyzing the first image, one or more candidate objects depicted in the first image, and, for each of the candidate objects, determining whether the object is a single cell by analyzing an image of the object using a convolutional neural network. The method further includes detecting, by analyzing the second image with the processor(s), a cell colony depicted in the second image, and determining, by the processor(s), whether the colony was formed from only one cell based at least on whether each candidate object was determined to be a single cell. The method further includes generating, by the processor(s), output data indicating whether the colony was formed from only one cell.