Brief Report - (2025) Volume 10, Issue 1
Received: 29-Jan-2025, Manuscript No. jidm-25-162513;
Editor assigned: 31-Jan-2025, Pre QC No. P-162513;
Reviewed: 12-Feb-2025, QC No. Q-162513;
Revised: 19-Feb-2025, Manuscript No. R-162513;
Published:
26-Feb-2025
, DOI: 10.37421/2576-1420.2025.10.387
Citation: Evgeny, Talik. "The Science behind Immunotherapy: A New Hope for Cancer Patients." J Infect Dis Med 10 (2025): 387.
Copyright: © 2025 Evgeny T. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
CAR-T cell therapy, another groundbreaking approach, involves genetically modifying a patient's T cells to better recognize and fight cancer. This personalized therapy has shown incredible success, particularly in blood cancers like leukemia and lymphoma. Monoclonal antibodies, on the other hand, are lab-engineered molecules that target specific proteins on cancer cells, marking them for destruction by the immune system. Cancer vaccines represent another promising development, aiming to stimulate the immune system to recognize and attack cancer cells. Unlike traditional vaccines that prevent infectious diseases, cancer vaccines are designed to target existing cancer cells and prevent recurrence [3]. Despite its promise, immunotherapy is not without challenges. Some patients experience severe immune-related side effects, as an overactive immune system may attack healthy tissues. Moreover, not all cancers respond equally to immunotherapy and ongoing research aims to expand its effectiveness across different cancer types.
Nevertheless, immunotherapy represents a transformative advancement in cancer treatment, offering new hope for patients with previously untreatable cancers. As research and technology continue to evolve, immunotherapy is poised to become an even more effective and widely accessible weapon against cancer, potentially leading to higher survival rates and improved quality of life for patients worldwide [4]. Artificial intelligence and big data are playing an increasingly important role in immunotherapy development. AI-powered algorithms can analyze vast amounts of genomic and clinical data to identify biomarkers, predict treatment responses and optimize drug discovery. Machine learning models are also being used to simulate immune system behavior, enabling researchers to design more effective therapies with reduced trial-and-error. AI-driven diagnostics, such as liquid biopsies that detect cancer biomarkers in blood samples, are also improving early detection and monitoring of treatment responses [5].
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