Therapeutic Product Immunogenicity Community

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  • 1.  Use of Red Thread statistical analysis

    This message was posted by a user wishing to remain anonymous
    Posted 07-15-2025 12:15
    This message was posted by a user wishing to remain anonymous

    Hello, 

    I am wondering how the community is utilizing red thread to ensure the Screening cut point is 5%FPR? This approach is being considered as the FPR is grater than 13%.

    Any challenges associated with utilizing the approach? 

    Thank you!



  • 2.  RE: Use of Red Thread statistical analysis

    Posted 07-16-2025 09:35
    Never heard of this statistical analysis, and I've been in this business a long time.
    The 5% FPR is a statistical target which will have a level of uncertainty about it (reflected in your confidence window).  I doubt that any statistical test most don't know about is really needed.  Tweaking a cutpoint a little here and a little there to get exactly 5% is unlikely to impact the clinical relevance of the data obtained as most ADA responses landing near enough to the cutpoint to be effected by such nuanced determinations don't usually effect outcomes.
    But if you're enthused about using red thread statistics, use it and apply it along side a standard CP determination and see what it does to your incidence.  If you already have such data, it's easy enough to do.  Then publish it.






  • 3.  RE: Use of Red Thread statistical analysis

    Posted 07-17-2025 11:32
    Red Thread, to my understanding, is a software program designed to automate calculation of cut point and other measures. I believe it uses the same basic principles of outlier removal and statistical analysis as the industry standard, ie Shankar et al.

    The anonymous poster mentioned having a FPR in excess of 13%. This would signal the need for an in-study cut point. Whether you use Red Thread for that or not is a matter of personal preference.





  • 4.  RE: Use of Red Thread statistical analysis

    Posted 07-17-2025 13:15
    John
    Thanks for that-I just looked it up and indeed part of its function is to support immunogenicity assay development/validation.  It seems to also employ AI, which frankly makes me wary as cutpoint analysis is straightforward enough not to need that, adding AI seems like inserting a black box into the analysis path (having said that, some statistics appear as black boxes to those of us not schooled in the math and stats concepts).  Perhaps the software output is complete enough to that what was done is clear.






  • 5.  RE: Use of Red Thread statistical analysis

    Community Leadership
    Posted 07-17-2025 14:30

    First, full disclosure that I am now employed by BioData Solutions so conflict of interest, but I was a client before I became a consultant.

    The AI behind Red Thread does follow the Shankar approach, and is not the probability based generative AI. Instead it fully automates the process of outlier removal and statistics calculations so that you can have your cut point factor in less than an hour rather than waiting weeks for statistician availability and manual effort. It also has a full audit trail to enable QC and can be repeated by a second individual to demonstrate the same answer. So the advantage of AI in this case is 1) speed and 2) traceability lacking in many statistical software in use.

    That said, I concur with John that the technology isn't the challenge here, it's the difference from the validation population and the in-study population. Evaluating the baseline samples from the study to establish a study-specific cut point factor is likely the best approach. If a very small study, 13% isn't really that much higher than the expected 2-11% range even with a perfect cut point factor, so if testing more samples in confirmatory than expected isn't a great burden, I wouldn't necessarily worry about a higher false positive rate.



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    Joleen White Ph.D.
    AAPS 2024 Global Health Community Chair
    Bioanalytical 101 Course Development
    Senior Advisor
    BioData Solutions LLC
    [email protected]

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