Graphical User Interface

Abstract

The images represented in the image diagrams are interactive graphical user interfaces (GUIs) that visually convey information to a user related to systems for (i) creating and / or modifying and / or analyzing unit operations and data generated therefrom in manufacturing processes, such as cell and gene therapy manufacturing processes, (ii) combining live data from databases with textual information, and (iii) interactive analysis of data (e.g., patient data visualization systems) and analysis of data related to manufacturing processes. (A. Graph-Based Visualization and Interactive Data Views for Pharmaceutical Manufacturing Process Data Reconciliation) For example, in certain embodiments, the images represented in the image diagrams are associated with graph-based visualization tools that enable a user to analyze data related to one or more experiments and / or manufacturing processes used to produce pharmaceutical products and / or variations thereof. In particular, the images for graph-based visualization and data analysis GUI tools represented in the image diagrams can be used in association with GUIs that enable a user to automatically and / or semi-automatically (e.g., in conjunction with user review and / or input) generate visualizations that facilitate the examination of experiments and / or manufacturing processes and reconcile data generated across multiple processes and / or process runs. For example, among other things, the interactive graph-based visualization tools and their images may be provided (e.g., rendered) individually or together via one or more GUIs or windows, sub-windows, panels, etc. Comparing and Reconciling Multiple Processes In certain embodiments, the images represented in the pictorial diagrams are used as GUIs that provide graph-based visualization tools that provide comparison and / or reconciliation of data from multiple experiments and / or manufacturing processes, e.g., in an automated and / or semi-automated manner (e.g., in conjunction with user interactions such as review and selection actions). Among other things, the images represented in the pictorial diagrams include designs that overlay multiple graph processes, structurally compare them, and reconcile them based on data points.For example, images presented in the pictorial diagrams may provide rendering data, missing data, or anomalies created by process comparison and reconciliation tools that (e.g., automatically) identify and address discrepancies and can be used to generate harmonized data sets for further analysis, such as mathematical modeling. Thus, among other things, the graph-based visualization tools provided in the images presented in the pictorial diagrams address the challenges presented by unreconciled data across multiple experiments and / or manufacturing processes and / or within a single process that may be performed under varying conditions. Achieving automated reconciliation of such data is a significant challenge that, if not addressed, hinders effective and accurate analysis, which, in turn, can dramatically impact a user's and / or organization's ability to optimize and / or maintain the quality of their manufacturing processes and / or develop new processes. Among other things, graph-based visualizations and the images presented in the pictorial diagrams may aid in adjusting sampling points to maximize overlay for effective comparisons and / or, in certain embodiments, identify overlapping points in existing data for effective real-time analysis. For example, the pictorial diagrams show examples of multiple levels of data views and clickable / expandable pop-ups. In particular, in some embodiments, the pictorial diagram is associated with a GUI that integrates the ability to collect and link actual data with the process diagram. For example, multiple levels of data can be viewed in an interactive and dynamic manner. For example, the image represented in the pictorial diagram provides a high-level view, and while not all data may be directly visible, it provides clickable / expandable and customized dynamic nodes for each node type, thereby allowing the user to simultaneously inspect and analyze collected and / or input data. In this manner, the image represented in the pictorial diagram facilitates the identification and analysis of differences between processes. In some embodiments, structural differences between different processes indicate variations in conditions (e.g., temperature, duration, chemical concentrations), as well as the order and / or existence of certain steps.While unit operations (basic steps or stages in a process) may be generally similar to other processes, specific conditions and / or sequences can significantly affect the outcome, or the nature of the product or result. Thus, images represented in pictorial diagrams that provide visual display tools can be extremely valuable in process optimization, troubleshooting, and ensuring that a process meets desired specifications. For example, changing the device performing the unit operation and / or specific parameter values ​​within the unit operation (e.g., rotation speed, total volume, duration, etc.) can have a significant impact on the quality, recovery, efficacy, etc. of the output of that unit operation, which in turn can affect characteristics such as product biological / potency, and additionally or alternatively, factors such as cost of production, number of doses produced per manufacturing run, and the like. Thus, among other things, images represented in pictorial diagrams can be associated with and provide GUIs that present generated data, such as automatically generated data (e.g., using ontologies), which can help identify commonalities and / or differences between studies and facilitate analysis to determine, for example, whether device or parameter changes have significant impacts. In particular, as described herein, a graph-based visualization tool represented in a pictorial diagram provides a user with a visual representation of one or more manufacturing processes via a graph-based approach that easily communicates and highlights differences in conditions and unit operations, as well as their nature. For example, the image represented in the pictorial diagram may include visual features that highlight unreconciled data points. This approach facilitates the identification and correction of data reconciliation issues, thereby streamlining data analysis for research and process development conducted in the creation and production of pharmaceuticals, such as cell-based therapeutics and biologic drugs. (i. Process Graph with Interactive Nodes) The pictorial diagram illustrates an example of a graph-based visualization of a manufacturing process. As shown in the pictorial diagram, a manufacturing process can be represented and displayed via a process graph.Each node in a process graph displays a data point corresponding to a unit operation in the particular manufacturing process it (e.g., the process graph) represents. A node may include information about the current data state and content (e.g., in real time) of the data point it represents. Within a graph-based visualization, nodes may be dynamic, such that, for example, user interaction with a particular node (e.g., mouse hover, click, touchscreen tap, or long press) triggers the display of a tooltip indicating the current data state of the displayed data point, including data collected at various stages of the manufacturing process. Process graphs may be rendered and used for experimental design and process execution to visualize and track different stages of a real-time experiment, outlining complex manufacturing experiments over multiple days of a manufacturing procedure. Experimental Summary: In one embodiment, a graph is displayed as an experiment summary, providing a high-level overview of the experiment, including the process steps and (e.g., approximate) order in which they were performed, the days that specific process steps were performed, how the process steps relate to each other, and an overview of the various states / arms evaluated during the experiment and how those states relate to each other. Timeline: In some embodiments, a process graph may include a timeline, displaying multiple time points, such as days, during which a particular experiment or manufacturing process represented by the graph is performed. As shown in the image depicted in the pictorial diagram, the timeline may be displayed along the horizontal axis, with labeled circular icons used to visually represent individual time points (running days 1 through 21). Other ways of visually displaying the timeline may be used, such as using icons of other shapes along the vertical axis and / or other units (e.g., hours, weeks, etc.). Process Unit Operations: In some embodiments, a process graph may visually identify individual process unit operations performed during the manufacturing process.Individual process unit operations may be displayed, for example, via a combination of text labels and icons or markings that convey the specific unit operations performed and, optionally, the time they are performed and / or their (e.g., temporal) relationship with respect to other unit operations. In some embodiments, as shown, for example, in the images depicted in the pictorial diagrams, the text labels also include a numerical component to identify the specific day on which each unit operation is performed, and the text labels are arranged sequentially from left to right along the horizontal axis to mark the order of operations performed over time. Vertical dotted lines extending down from each text label provide a visual guide for the planned schedule for each unit operation and / or a temporal mapping of the manufacturing process. (Data Points (Nodes)) As shown in the images depicted in the pictorial diagrams, data points in the manufacturing process associated with specific unit operations and from which relevant information (measurements and / or recorded observations) is collected are displayed via nodes. Nodes may be rendered as icons, such as filled circles, as shown in the images depicted in the pictorial diagrams. In the image depicted in the pictorial diagram, each circle is a node and is positioned to visually align with a particular unit operation. That is, in the image depicted in the pictorial diagram, it is placed on a vertical dotted line extending downward from a text label identifying a particular unit operation, thereby identifying a data point related to that particular unit operation. (Connectivity) In some embodiments, the process graph may display the dependency or sequence of material and / or data flow from one unit operation to another through rendered connections between various nodes. For example, as shown in the image depicted in the pictorial diagram, node connectivity may be rendered as lines connecting nodes across a timeline. (Data Connection Points) Specific points where data are collected are marked along the process, such as checkpoints important for quality control or measurements required for process evaluation.(Arms) In some embodiments, a process graph may include and / or display one or more (e.g., separate) arms, each representing a different experimental condition and / or variation in a baseline process. For example, in the image shown in the pictorial diagram, the arms are rendered as various smaller graphs positioned below the timeline. Each line in the arms section indicates a different arm / condition as defined by the operator. Labels are provided to help clarify the focus of these steps and / or to distinguish and identify nodes as belonging to a condition so that corresponding data collected from the laboratory is placed in the correct node and we do not confuse data across conditions. In this case, a base process may be a step that follows a standard or control process, while other processes are steps that make experimental changes to that process or supplement the base process (e.g., making media, preparing materials, etc.). (Baseline Process and Base Process Graph) A baseline process may be a control and / or standard procedure and may be rendered as a base process graph. Text labels, color schemes, icon styles, positioning, and the like can be used to visually identify a baseline process, such as in a graph-based visualization. For example, in an image depicted in a pictorial diagram, the baseline process is identified and displayed as a nodal line directly below the timeline. In a process graph depicted in a pictorial diagram, the baseline process may be a standard process against which other variations are compared. (Variations and Outputs / Endpoints) In certain embodiments, a graph-based visualization can include one or more auxiliary subgraphs, each corresponding to and representing variations to experimental conditions and / or baseline versions of a manufacturing process. For example, the image depicted in the pictorial diagram shows auxiliary subgraphs displaying variations labeled as "Ver1.1," "Ver1.2," "Ver2.1," "Ver2.3," etc., and "Condition 1," "Condition 2," "Condition 3," etc., representing different experimental arms or conditions.In this manner, graph-based visualization tools can be used to communicate variations in materials used, process conditions, or specific unit operations being performed. Additionally or alternatively, different process endpoints and / or outputs can also be displayed (e.g., via endpoint graphs). For example, as shown in the image depicted in the pictorial diagram, a series of nodes labeled "Out.1" and "Out.2" represent different endpoints and / or outputs of a process, such as different ways of processing or storing a final product. For example, in the exemplary subgraph shown in the image depicted in the pictorial diagram, lines refer to experimental conditions or interrelated subsets of a process, such as preparing materials (e.g., media) to feed a cell-containing process. Arm / condition sections help orient operators to the specific tasks being performed, and by using descriptive methods to identify various arms, data collected in the laboratory is entered into the corresponding nodes, and numbers / quantities, etc., are not confused between conditions. Thus, process graphs facilitate the visualization and management of complex manufacturing processes. Among other things, they allow researchers to track the progress of experiments, compare different conditions or variations side by side, and ensure that data is systematically collected at designated points throughout the process. The ability to visualize the entire process in this way helps identify bottlenecks, ensure consistency, and facilitate data-driven decision-making.

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