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 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 images presented in 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 run 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. Among other things, graph-based visualizations and the images presented in pictorial diagrams may aid in adjusting sampling points to maximize overlay for effective comparison and / or, in certain embodiments, identify overlapping points in existing data for effective real-time analysis. 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 greatly 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 valuable in process optimization, troubleshooting, and ensuring that a process meets desired specifications.For example, changing the device performing 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 represented in pictorial diagrams can be associated with and provided as GUIs that present generated data, such as automatically generated data (e.g., using ontologies), to help identify commonalities and / or differences between studies and facilitate analysis to determine, for example, whether device or parameter changes have significant impacts. Among other things, graph-based visualization tools represented in pictorial diagrams, as described herein, provide users with visual representations of one or more manufacturing processes via a graph-based approach that easily communicates and highlights differences in conditions and unit operation, as well as their nature. For example, images represented in pictorial diagrams can include visual features that highlight unadjusted 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 image diagram shows an example of a graph-based visualization of a manufacturing process. As shown in the image diagram, a manufacturing process can be represented and displayed via a process graph. Each node in the process graph represents 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 that it represents.Within a graph-based visualization, nodes can 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 can 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 spanning multiple days of manufacturing procedures. Experimental Overview: In one embodiment, a graph is displayed as an experiment overview, providing a high-level overview of the experiment, including the process steps and (e.g., approximate) order in which they were performed, the dates specific process steps were performed, how the process steps relate to each other (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 each other (e.g., the bottom half of FIG. 1A ). Timeline: In one embodiment, a process graph can include a timeline, displaying multiple time points, such as the days in which a specific experiment or manufacturing process represented by the graph was performed. A 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 representing the timeline may be used, such as along the vertical axis and / or using icons of other shapes, 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 particular unit operations performed and, optionally, the times at which they are performed, and / or their (e.g., temporal) relationship with respect to other unit operations.For example, a graph-based visualization may include 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 some embodiments, for example, the text labels also include a numerical component, identifying 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 over time. Vertical dotted lines extending downward 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)) Data points in the manufacturing process associated with a particular unit operation 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. Each circle is a node and is positioned to visually align with a particular unit operation; that is, it is located 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, a 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, node connectivity may be rendered as lines connecting nodes across a timeline. (Data Connection Points) Distinct 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 different experimental conditions and / or baseline process variations. For example, 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 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 may be used to visually identify the baseline process, such as in a graph-based visualization. For example, the baseline process is identified and displayed as a node line directly below the timeline. In a process graph, the baseline process may be the standard process against which other variations are compared. Variations and Outputs / Endpoints: In certain embodiments, a graph-based visualization may include one or more auxiliary subgraphs, each corresponding to and representing variations to experimental conditions and / or baseline versions of a manufacturing process. Additionally or alternatively, different process endpoints and / or outputs may also be displayed (e.g., via endpoint graphs). Process graphs thus facilitate visualizing and managing complex manufacturing processes. Among other things, they enable researchers to track experimental progress, compare different conditions or variations side-by-side, and ensure that data is systematically collected at specified points throughout the process. The ability to visualize the entire process in this manner helps identify bottlenecks, ensure consistency, and facilitate data-driven decision-making. iii. Comparing and Tuning Multiple Processes: In certain embodiments, a graph-based visualization tool provides a GUI that offers techniques for the automated comparison and tuning of multiple manufacturing processes.Among other things, they visually communicate and compare multiple manufacturing processes in a manner that facilitates understanding the interactions between different manufacturing processes or the same process under different conditions. The pictorial illustration shows an example of comparing multiple manufacturing processes. The pictorial illustration shows multiple (three) overlaid and coordinated process graphs, each displaying a similar sequence of unit operations across a daily timeline. These multiple process graphs may display different experimental runs and / or batches in the manufacturing process. In the image depicted in the pictorial illustration, each graph may display the sequence of unit operations across a daily timeline. These graphs may display different experimental runs or batches in the manufacturing process, allowing for easy comparison and analysis of these separate activities over the same period of time. Comparing multiple graphs in this manner allows a user to, among other things: (i) identify patterns and trends. In some embodiments, overlaying graphs allows a user to easily discern general trends or patterns across different data sets or time periods. (ii) assess consistency and variability. In some embodiments, comparing graphs assesses the consistency of a process or experiment and helps identify any variability or anomalies. (iii) benchmark performance. In some embodiments, graphs can be used to display different batches or experimental runs, allowing a user to compare them and determine which performs better for a certain metric. (iv) Understanding Relationships. In some embodiments, seeing how different variables interact over time can help understand the relationships between them. (v) Making Informed Decisions. In some embodiments, the clear comparisons facilitated through the tool make it easier to make decisions based on empirical data, such as improving a process or replicating a successful experiment. In particular, images depicted in pictorial diagrams provide users with a visual display that facilitates process comparison by overlaying multiple graphs and providing visual cues based on and displaying comparative analysis of their structures and data points.For example, overlaying multiple graphs allows for direct visual comparison of different experimental runs or process batches. In certain embodiments, differences or similarities between one or more processes may be identified (e.g., automatically) and visually highlighted, e.g., as shown in a pictorial diagram. For example, if one process deviates in a unit operation, the process comparison and adjustment tools described herein may detect and flag this variation, e.g., via variations in the type, size, color, etc. of icons used to display nodes. For example, in the image depicted in the pictorial diagram, the process variation is flagged as an enlarged, color-coded (orange) circle.

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