Evaluating Configuration Process Optimization for TruLab

The TruLab team is highly satisfied with the quality of work completed and the professional manner in which the project was conducted.

Executive Director

Background

Client Overview

TruLab provides technology for sample management and tracking for clinical sites to pharmaceutical companies and is a world leader in biological sample tracking. Founded by professionals in biopharma and technology, the company provides mobile guides configured to study protocol, including the most up-to-date amendments, to ensure proper processes are followed and data integrity is maintained.

Project Overview

Delivery of this service requires the configuration of the TruLab platform for each study using the Protocol and Lab Manual for each study. The current process involves an analyst completing a configuration spreadsheet which is then uploaded into the system with a script. The challenges of the current process are

  • The config spreadsheet is currently designed from a database perspective and makes it difficult for new analysts to become proficient in setting up a configuration
  • Some of the data points have to be entered repeatedly
  • Larger studies take a long time to set up and the config setup is becoming a bottleneck in scaling the delivery of the service to clients

 

TruLab was looking to cut the time to set up a study to less than 1 week and wanted to evaluate if investing in a self-configuration platform enabled with artificial intelligence for data extraction was the right call. 

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    Our Approach

    Discovery and Planning

    We began by conducting extensive interviews with the analysts currently working on the configurations of the study to understand the process and the key pain points. With our understanding, we then defined and proposed different phases for the evaluation.

    Preliminary Phase

    We continued with more discovery, working through the configuration tools ourselves, with additional research to deepen our understanding of the domain. We had weekly check-ins with the client to update them of our progress and validate our assumptions.

    Solution Design

    We then designed mock UIs for the proposed solution, eliminating redundant steps in the configuration process. We explored different UI layouts that made the experience easier to navigate and intuitive without overwhelming the user. We researched options for tools to support an in-app preview experience which was a highly desired features for analysts.

    AI Extraction Research

    We evaluated technologies from Microsoft, Google and AWS to determine the right extraction tool for the requirements, looking at the key features, strengths and limitations. We ran sample data extractions to see how well each performed for the required use case.

    Solution Presentation

    Finally we presented TruLab with a detailed solution design complete with UI Mocks, results of AI extractions, and pricing to help them decide if this was the right path, if the cost was worth it, and if it should be done in-house or outsourced.

    Value Delivered

    • UI Design Mocks: Interactive UI mock designs of a self-configuration tool that when implemented will reduce the learning curve for analysts to configure a study and also reduce the time to configure a new study.
    • Solution Design Document: Detailed solution architecture diagrams and solution design document that provided insights into the components that will be required to develop and launch the new configuration tool
    • OCR and AI Research: Evaluated different AI capabilities to determine the feasibility of extracting the desired data from the study documents.
    • Pricing and Investment Requirements: Detailed cost requirements and estimated timeline for the development and ongoing support of the solution.

    By providing TruLab with the information and experience of what the automated solution would look like and it’s associated costs, they were able to make an informed decision on if this was the right investment to make at the time.

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