Litcius/Paper detail

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

Rahmad Akbar, Habib Bashour, Puneet Rawat, Philippe A. Robert, Eva Smorodina, Tudor‐Stefan Cotet, Karine Flem‐Karlsen, Robert Frank, Brij Bhushan Mehta, Mai Ha Vu, Talip Zengin, Jose Gutierrez‐Marcos, Fridtjof Lund‐Johansen, Jan Terje Andersen, Victor Greiff

2022mAbs116 citationsDOIOpen Access PDF

Abstract

mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

Topics & Concepts

Monoclonal antibodyComputer scienceArtificial intelligenceMachine learningAntibodyImmunologyBiologyMonoclonal and Polyclonal Antibodies ResearchProtein purification and stabilityvaccines and immunoinformatics approaches