{
  "id": 2204402,
  "title": "AI Identifies Pre-existing Antimicrobial Antibody Profile That May Predict Immune Response to Vaccination",
  "url": "https://urgent.news/2026/08/20/ai-identifies-pre-existing-antimicrobial-antibody-profile-that-may",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-20T18:53:21.000Z",
  "source": {
    "name": "GEN Biotechnology",
    "slug": "gen-biotechnology",
    "url": "https://www.genengnews.com/topics/infectious-diseases/ai-identifies-pre-existing-antimicrobial-antibody-profile-that-may-predict-immune-response-to-vaccination/"
  },
  "original_language": "en",
  "account": "A team of researchers at Arizona State University has discovered a potential way to predict how well someone will respond to a vaccine. The study, published in Cell Press Blue, analyzed antibody profiles of 4,000 individuals, both healthy and immunosuppressed, before and after COVID-19 vaccination. The researchers used artificial intelligence to identify \"sentinel antibodies\" that consistently predicted strong or weak vaccine responses. These sentinel antibodies are pre-existing antibodies to common microbes that may represent biomarkers of immune responsiveness to vaccination. Lead researcher Joshua LaBaer stated that the findings suggest some individuals may be more immune-ready than others, providing a potential biomarker for vaccine response before immunization.",
  "summary": "Researchers analyzing antibody profiles in thousands of individuals have discovered that pre-existing antibodies to common microbes can predict the strength of new vaccine responses. The post AI Identifies Pre-existing Antimicrobial Antibody Profile That May Predict Immune Response to Vaccination appeared first on GEN - Genetic Engineering and Biotechnology News .",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}