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PK methodology group meeting: Automation and AI applications for Bioanalytical lab

  • 1.  PK methodology group meeting: Automation and AI applications for Bioanalytical lab

    Community Leadership
    Posted 03-19-2025 20:33

    Agenda:

    Automation and AI applications in a Bioanalytical lab. – led by Vimal Patel.

    Friday (May 21st), 12:30-13:30 pm ET.

    ________________________________________________________________________________

    Microsoft Teams meeting

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    Learn More | 19_meeting_NmNiNDEyMWQtMzhlNC00ZTMyLTkzMmMtZGNhZGI2ODQ3OTRi@thread.v2&messageId=0&language=en-US" target="_blank" rel="noopener">Meeting options



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    Mark Ma
    VP. Head of Translational Sciences and Early Development
    Rallybio
    Madison CT
    [email protected]

    Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.
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  • 2.  RE: PK methodology group meeting: Automation and AI applications for Bioanalytical lab

    Posted 05-29-2025 19:29
      |   view attached

    Thanks Vimal Patel from Charles River Lab presented an interesting topic in March AAPS PK methodology discussion group meeting. The presentation title is Automation and AI application in Bioanalytical Lab. Below are high level summary of his presentation. Please see the enclosed presentation for detailed information.

    • The presentation outlines automation integration from pre-lab (scheduling, procurement), to in-lab (sample processing, data collection), to post-lab (analysis, QC, reporting) processes.

    • Tools like Smartsheet streamline project management, scheduling, and resource forecasting. Power BI enables real-time analytics and automated reporting from lab operations.

    • Automation using Hamilton liquid handlers increased consistency, reduced error, and improved turnaround times for LC-MS, immunocapture, and high-throughput assays. Automation reduced analysis time (e.g., 4 experimental days vs. 7 for manual), increased pass rates (98%+), and improved reproducibility across assay types.

    • Automated report generation and AI tools are being implemented to reduce QC effort, enhance data integrity, and enable faster delivery of reports.

    • Design of Experiments (DOE) supports data-driven optimization of assay conditions. Single-well analysis and microsampling methods further reduce resource use and increase efficiency.

    • Adoption of generic ADA assays and microsampling techniques offers ethical and operational advantages, including reduced animal use and simplified validation.

    • Envisions an AI-driven, self-optimizing workflow, where experiment design, execution, and iteration are automated until method development is complete-minimizing manual intervention. Encourages the bioanalytical community to embrace automation and AI, standardize workflows, and collaborate on data sharing to accelerate innovation, ensure compliance, and improve global productivity.



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    Xiaohui Xu Ph.D.
    Director
    Daiichi Sankyo
    Basking Ridge NJ
    [email protected]

    Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.
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    Attachment(s)

    pptx
    Vpatel_PS360_2024_VF_PK working group.pptx   22.33 MB 1 version
    Original Message