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Related Concept Videos

Tumor Immunotherapy01:27

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
Cancer Vaccines01:30

Cancer Vaccines

Cancer treatment vaccines are a rapidly evolving field that offers a promising approach to immunotherapy. Unlike traditional vaccines that prevent diseases, cancer treatment vaccines are designed to treat existing cancers by stimulating the immune system to recognize and attack cancer cells.
Cancer vaccines come in two categories: preventive (prophylactic) and treatment (active). Preventive vaccines, such as the Human Papillomavirus (HPV) vaccine, protect against viruses that cause certain...
Microorganisms in Medicine and Therapeutics01:29

Microorganisms in Medicine and Therapeutics

Microorganisms play a fundamental role in vaccine development, gene therapy, and therapeutic production. Their biological properties are harnessed to advance medicine and public health. Beyond immunization, microorganisms contribute to gut health, antibiotic synthesis, and genetic disease treatment.Live Attenuated and Inactivated VaccinesLive attenuated vaccines, such as the measles, mumps, and rubella (MMR) vaccine, utilize weakened forms of pathogens to closely resemble natural infections.
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Cytotoxic T Cells-mediated Immune Response01:27

Cytotoxic T Cells-mediated Immune Response

Cytotoxic T cells are a vital component of the immune system. They have the remarkable ability to identify and target antigens on infected or abnormal cells. These antigens often originate from intracellular pathogens such as viruses or abnormal proteins cancer cells produce.
Immunological surveillance is the ability of immune cells to monitor and eliminate infected cells with intracellular pathogens, neoplastically transformed cells, and cells with non-self antigens. Cytotoxic T cells and NK...

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Updated: Jun 16, 2026

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments
07:46

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

Artificial intelligence for optimization of immunotherapy: current applications and transformative potential.

Ali Tarhini1, Palak Dave1, Shari Pilon-Thomas2

  • 1Machine Learning Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States.

Frontiers in Immunology
|June 15, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) optimizes cancer immunotherapy by enhancing drug development and treatment personalization. While AI shows promise, challenges in data quality, patient safety, and ethics must be addressed for widespread clinical use.

Keywords:
agentic AIartificial intelligencecellular therapyfoundation modelsgenerative AIimmune checkpoint inhibitorsimmunotherapymulti-modal data integration

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Last Updated: Jun 16, 2026

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments
07:46

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

Enrich and Expand Rare Antigen-specific T Cells with Magnetic Nanoparticles
09:28

Enrich and Expand Rare Antigen-specific T Cells with Magnetic Nanoparticles

Published on: November 17, 2018

Paramyxoviruses for Tumor-targeted Immunomodulation: Design and Evaluation Ex Vivo
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Paramyxoviruses for Tumor-targeted Immunomodulation: Design and Evaluation Ex Vivo

Published on: January 7, 2019

Area of Science:

  • Oncology and Immunology
  • Computational Biology and Bioinformatics
  • Medical Artificial Intelligence

Background:

  • Artificial intelligence (AI) is revolutionizing cancer treatment, particularly in precision oncology and immunotherapy.
  • Cancer immunotherapy aims to harness the immune system against tumors, a field ripe for AI-driven acceleration and personalization.
  • AI technologies, including machine learning, deep learning, generative AI, and foundation models, are increasingly vital for optimizing immunotherapy.

Purpose of the Study:

  • To review state-of-the-art AI technologies applicable to cancer immunotherapy.
  • To examine current AI applications in immunotherapy, including cell therapies, checkpoint inhibitors, and cancer vaccines.
  • To analyze datasets, performance metrics, limitations, and obstacles to AI's clinical adoption in immunotherapy.

Main Methods:

  • Review of existing literature on AI technologies and their applications in cancer immunotherapy.
  • Analysis of AI's impact on response prediction, patient stratification, and cellular therapy development.
  • Examination of generative AI and foundation models for treatment planning and adverse event prediction.

Main Results:

  • AI, including traditional and advanced methods like generative AI, significantly impacts immunotherapy by improving response prediction and patient stratification.
  • AI applications span cell therapies, checkpoint inhibitors, and cancer vaccines, demonstrating broad utility in drug development and treatment optimization.
  • Emerging AI innovations like agentic AI and MCP promise further efficiency gains, though challenges remain.

Conclusions:

  • AI offers substantial potential to accelerate discovery and personalize cancer immunotherapy regimens.
  • Overcoming challenges related to data quality, patient safety, and ethical considerations is crucial for AI's routine clinical integration.
  • The future of AI in immunotherapy may involve orchestrated multi-agent systems with human oversight for enhanced efficacy and safety.