That is actually a very good point: likely many different aspects of pharmaceutical development can and will be impacted by AI/ML. Maybe we should consider broader scope........
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Jochem Gokemeijer
Senior Director
Bristol-Myer Squibb R&D CO
Cambridge MA
[email protected]Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.
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Original Message:
Sent: 05-10-2023 08:02
From: Chad Briscoe
Subject: AI Immunogenicity models
The Bioanalytical Community has started a focus group on AI/Machine Learning. @Roy Helmy at Merck is leading the team and I'd encourage you to collaborate with him and that group on this topic as we all try to figure out how AI is going to impact our pharmaceutical research in the future.
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Chad Briscoe PhD
VP of Global Bioanalytical Labs
Celerion
Lincoln NE
[email protected]
Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.
Original Message:
Sent: 05-09-2023 12:34
From: Jochem Gokemeijer
Subject: AI Immunogenicity models
Hi All,
With the current excitement around AI and machine learning I wanted to see what people think the impact of these technologies on the in silico immunogenicity prediction most of us are using.
Some interesting papers have been published recently re the development of these deep learning models that I think can be utilized to assess immunogenicity risk of biotherapeutics.
What do people think of these models?
Should we organize a webinar or workshop around this so we can discuss and learn more?
DeepImmuno : DeepImmuno: deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity
TCR prediction: Can we predict T cell specificity with digital biology and machine learning? - Nature Reviews Immunology
| Nature | remove preview |
| | Can we predict T cell specificity with digital biology and machine learning? - Nature Reviews Immunology | | Koohy and co-workers discuss how we must turn to machine-learning approaches to define the antigen specificity of the many millions of possible T cell receptors. They review the models and methods currently being used to predict cognate antigens for orphan T cell receptors. | | View this on Nature > |
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| OUP Academic | remove preview |
| | DeepImmuno: deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity | | Cytolytic T-cells play an essential role in the adaptive immune system by seeking out, binding and killing cells that present foreign antigens on their surface. An improved understanding of T-cell immunity will greatly aid in the development of new cancer immunotherapies and vaccines for life-threatening pathogens. | | View this on OUP Academic > |
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Jochem Gokemeijer
Senior Director
Bristol-Myer Squibb R&D CO
Cambridge MA
[email protected]
Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.
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