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  • Perspective
  • Open Access

How the Immune System Learns

Arup K. Chakraborty1,2,3,4,5,*, Anupama Jayaraman1,4, and Daniel P. Newton4,6

  • *Contact author: arupc@mit.edu
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PRX Life 4, 021001 – Published 13 May, 2026

DOI: https://doi.org/10.1103/znt6-6n38

Abstract

The adaptive immune system can mount pathogen-specific responses against a vast world of evolving pathogens (antigens). The humoral immune system is a part of adaptive immunity. It has the remarkable ability to learn about an antigen after exposure to it through a mutation-selection evolutionary process, resulting in more potent responses than those that emerge initially. Recent studies have revealed that upon reexposure to antigens, feedback regulation mediated by past responses steers the evolutionary learning algorithm to generate new responses. This feature enables the immune system to learn to generalize responses to target unseen variants of the original pathogen upon “training” with a limited number of samples. We summarize these new findings and suggest new questions that emerge from them. This is the right time to address these questions by bringing together statistical physics, machine learning, immunology, and evolutionary biology.

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PRX Life 4, 021001– Published 13 May, 2026
  • Received 28 January 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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