Dr Nina Bhardwaj | Director of Immunotherapy Professor of Medicine, Division of Hematology & Oncology
Tisch Cancer Institute

Dr Nina Bhardwaj, Director of Immunotherapy Professor of Medicine, Division of Hematology & Oncology, Tisch Cancer Institute

Dr. Bhardwaj is an immunologist who has made seminal contributions to human dendritic cell biology, specifically with respect to their isolation, biology, antigen presenting function, and use as vaccine adjuvants in humans. She is the Director of Immunotherapy at the Icahn School of Medicine at Mountt Sinai (ISMMS) and holds the Ward Coleman Chair in Cancer Research. Dr. Bhardwaj brings expertise in human immunology and a variety of immune therapies, having developed Toll Like Receptor (TLR) agonist- and dendritic cell-based vaccines for the treatment of both cancer and infection in several Investigator-Initiated studies. Dr. Bhardwaj is an elected member of the American Society of Clinical Investigation and the American Association of Physicians, a recipient of the Doris Duke Distinguished Scientist Award and was named one of the Scientific American Magazine’s Top 50 Researchers, receiving the Award for Medical Research in 2004. She received the Fred W. Alt Award for new discoveries in Immunology in 2015 from The Cancer Research Institute. Dr. Bhardwaj is a senior editor of the AACR Cancer Immunology Research journal, senior editor for Frontiers in Immunology and consulting editor for the Journal of Clinical Investigation. She has also served on NIH Study Sections and multiple advisory councils. Dr. Bhardwaj was formerly chair of the Cancer Immunology Steering Committee of the AACR. Dr. Bhardwaj has also successfully acquired multiple federal and foundation grants and has authored over 200 publications.  


DC Co-conference Day 2 April 4 @ 5:10

Panel Discussion: Tumor neoantigEn SeLection Alliance (TESLA) – discovering the keys to developing personalized cancer vaccines

  • Accurately identifying neo-epitopes
    • What is the diversity of neo-epitope predictions from different groups?
    • How well did these predictions perform in terms of patient sample analysis?
    • Can we identify key parameters that improve the ability to predict neo-epitopes?
  • How do we convert this data into the creation of personalized cancer vaccines?
    • Merits of different vaccines platforms

back to speakers