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SUMMARY:"Machine learning in chemistry and beyond" (ChE-651) seminar by Ma
 ria Rodriguez Martinez "AI-driven modelling of T cell-based therapies"
DTSTART:20220405T151500
DTEND:20220405T161500
DTSTAMP:20260603T141814Z
UID:edd4ad61df88c473c0a0a2aba273cc62caecbe35b14781956d896f4a
CATEGORIES:Conferences - Seminars
DESCRIPTION:Maria Rodriguez Martinez\nT cells are major components of the 
 adaptive immune system with primary roles in killing infected abnormal cel
 ls. Because of their cytotoxic role\, T cells are being actively investiga
 ted in several cancer immunotherapy approaches. T cells selectively recogn
 ise foreign antigens through their T cell receptors (TCRs). TCR sequencing
  technologies have generated millions of TCR sequences and have fuelled th
 e development of AI models to predict the binding properties of TCRs from 
 their sequences. However\, while some models achieve good accuracy at pred
 icting TCR binding to a small set of epitopes\, the binding prediction to 
 unseen epitopes\, remains a challenge. In parallel\, the black-box nature 
 of many of these models has resulted in a limited understanding of the rul
 es that govern TCR binding\, preventing us from learning how to engineer r
 eceptors of improved affinity.\nIn this talk\, I will present recent effor
 ts done at IBM Research - Zurich to develop AI models to understand TCR - 
 epitope binding. First\, I will introduce TITAN\, a multimodal neural netw
 ork that allows to study independently the generalisation capabilities to 
 unseen TCRs and epitopes. TITAN exhibits significantly improved performanc
 e on unseen epitopes and\, importantly\, utilises an interpretable context
  attention mechanism that selectively highlights relevant amino acids. Sec
 ond\, I will describe DECODE\, an easy-to-use computational pipeline to ex
 tract the binding rules from any black-box model designed to predict the T
 CR-epitope binding. DECODE offers a range of analytical and visualisation 
 tools to guide the user in the extraction of such rules. Finally\, i will 
 discuss how AI models can facilitate the investigation of current immunoth
 erapeutic challenges\, such as cross-reactive events due to off-target TCR
  binding.\n 
LOCATION:https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUW
 JyQT09
STATUS:CONFIRMED
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