Graphical User Interface
JP1807200SActive Publication Date: 2025-08-28TAKEDA PHARMA CO LTD
View PDF 0 Cites 0 Cited by
Patent Information
- Application Number
- JP2024023072D
- Authority / Receiving Office
- JP · JP
- Patent Type
- Designs
- Current Assignee / Owner
- Priority Date
- 2024-01-24
- Filing Date
- 2024-07-24
- Publication Date
- 2025-08-28
- Estimated Expiration
- 2049-07-24
Smart Images

Figure 0001807200000001
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. (Process Graph) For example, the image diagram illustrates a GUI that provides a visualization of a process graph. In one embodiment, the graph-based visualization tool represented in the image diagram includes generating and / or rendering a process graph that displays an experimental and / or manufacturing process for the production of pharmaceutical products, including biologics such as cell-based therapeutics and biologic drugs. The process graph includes multiple nodes, each representing a data point corresponding to a unit operation in a particular experimental and / or manufacturing process where information is collected and / or an action is performed.The image diagrams further illustrate various approaches for capturing and / or displaying these data points and how users interact with them. (Comparing and Reconciling Multiple Processes) In certain embodiments, the images depicted in the image diagrams are used as GUIs to 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., coupled with user interactions such as review and selection actions). Among other things, the images depicted in the image diagrams include designs that overlay multiple graph processes, structurally compare them, and reconcile them based on data points. For example, the images depicted in the image diagrams may provide rendering data created by process comparison and reconciliation tools that (e.g., automatically) identify and address discrepancies, missing data, or anomalies, which can be used to generate a harmonized data set for further analysis, such as mathematical modeling. Thus, among other things, the graph-based visualization tools provided in the images depicted in the image 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 manufacturing process quality and / or develop new processes. In particular, the images presented in the graph-based visualizations and the graphical representations that present them 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 graphical representations show examples of multiple levels of data views and clickable / expandable pop-ups. In particular, in certain embodiments, the graphical representations are associated with GUIs that integrate the ability to collect and link actual data with process diagrams.For example, multiple levels of data can be viewed in an interactive and dynamic manner. For example, images presented in pictorial diagrams provide a high-level view, and while not all data may be directly visible, they provide clickable / expandable, customized, dynamic nodes for each node type, allowing users to simultaneously inspect and analyze collected and / or input data. In this manner, images presented in pictorial diagrams facilitate 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 sequence and / or presence of certain steps. While unit operations (basic steps or stages in a process) may be generally similar to other processes, unique conditions and / or sequences can significantly affect the outcome, or the nature of the product or result. Thus, images presented in pictorial diagrams that provide visual display tools can be extremely useful in process optimization, troubleshooting, and ensuring that a process meets desired specifications. For example, changing the device that performs a unit operation and / or certain 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 the biological / potency of the product, and additionally or alternatively, factors such as the cost of production, the number of doses produced per manufacturing run, and the like. Thus, among other things, images depicted in pictorial diagrams can be associated with and provided with GUIs that present generated data, such as automatically generated data (e.g., using ontologies), which helps to identify commonalities and / or differences between studies and facilitates performing analyses 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, an image represented in a 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 the process graph displays a data point corresponding to a unit operation in the particular manufacturing process that it (e.g., the process graph) represents. The 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 can be dynamic, such that, for example, a user interaction with a particular node (e.g., a mouse hover, click, touchscreen tap or long press, etc.) triggers the display of a tooltip indicating the current data state for the displayed data point, including data collected at various stages of the manufacturing process. Process graphs can be rendered and used for experiment design and process execution to outline complex manufacturing experiments over multiple days of manufacturing procedures and to visualize and track different stages of a real-time experiment.Experimental Overview: In some embodiments, a graph is displayed as an experimental overview, providing a high-level overview of an experiment, including the process steps and (e.g., approximate) order in which they were performed, the dates particular process steps were performed, how the process steps relate to one another (e.g., the top half of FIG. 1A ), and an overview of the various states / arms evaluated during the experiment and how those states relate to one another (e.g., the bottom half of FIG. 1A ). Timeline: In some embodiments, a process graph may include a timeline, displaying multiple timepoints, such as the days, during which a particular experiment or manufacturing process represented by the graph was 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 timepoints (e.g., days of execution from day 1 through day 21). Other ways of visually displaying the timeline may be used, for example, along the vertical axis and / or using other shaped icons, 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 a manufacturing process. Individual process unit operations may be displayed, for example, through a combination of text labels and icons or markings that convey the particular unit operations performed and, optionally, the time at which they are carried out and / or their (e.g., temporal) relationship with respect to other unit operations. For example, the graph-based visualization shown in the image depicted in the pictorial diagram includes a series of text labels along the top row (of nodes) identifying various unit operations such as "Material Preparation," "Start-Up," "Transduction," and "Compounding." In one embodiment, as shown in the image depicted in the pictorial diagram, for example, the text labels also include a numerical component and identify the particular 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 in which the operations are performed over time.The vertical dotted lines extending downward from each text label provide a visual guide for the expected 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 a particular unit operation and from which pertinent information (measurements and / or recorded observations) is collected are represented via nodes. Nodes may be rendered as icons such as filled circles as shown in the images depicted in the pictorial diagrams. In the images depicted in the pictorial diagrams, each circle is a node and is positioned so as to be visually aligned with a particular unit operation. That is, in the images depicted in the pictorial diagrams, it is located on a vertical dotted line extending downward from a text label identifying a particular unit operation, thereby identifying the 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 via rendered connections between the 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 along the process where data is collected are marked, such as important checkpoints 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 baseline process variation. For example, in the image depicted 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 one condition, so that corresponding data collected from the laboratory are placed in the correct node and we do not mix data across conditions. In this case, the base process may be the step following 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 may be used to visually identify the baseline process, such as in graph-based visualizations. For example, in images presented in pictorial diagrams, the baseline process is identified and displayed as a node line directly below the timeline. In process graphs of images presented in pictorial diagrams, the baseline process may be the standard process against which other variations are compared. Variations and Outputs / Endpoints In some 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 image 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, the graph-based visualization tool can be used to communicate variations in materials used, process conditions, or specific unit operations performed. Additionally or alternatively, endpoints and / or outputs of different processes 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 task being performed, and by identifying various arms in a descriptive manner, data collected in the lab are entered into corresponding nodes, and numbers / quantities, etc., are not mixed between conditions. Process graphs therefore 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.
Need to check novelty before this filing date? Find Prior Art