AI for Cancer Treatment

Revolutionizing Management of Cancer Immunotherapy 

Artificial intelligence’s role in the struggle to fight cancer is exciting for a cascade of compelling reasons.

As a father of a cancer surviving son, these days I often find myself investigating any new forms of treatment that may be of value for patients like him.

That’s just one driving force behind my enthusiasm for the growing use of AI in the development and efficacy of immunotherapy.

Immunotherapy—Leveraging the Immune System

AI has the potential to play a transformative role in many areas of medicine, but perhaps none more so than in cancer treatment. AI’s role in enhancing the effectiveness of immunotherapy, a game changing cancer treatment, is particularly exciting and provocative. Unlike traditional cancer treatments such as chemotherapy and radiation, immunotherapy leverages the body’s immune system to fight cancer — a promising approach that has shown significant success in treating various types of cancer.[1]

There’s little doubt that immunotherapy and other forms of newly arrived cancer treatment have their work cut out for them. Currently, overall cure rates for advanced lung, breast, and colon cancer are typically less than 50 percent. That indicates a need for more focused treatment programs, ones that are suited to an individual’s cancer diagnosis and stage. This is where AI steps up to the plate.

Powered by machine learning, AI algorithms can analyze vast amounts of data, including genetic information, medical histories, and imaging scans. These algorithms can pinpoint patterns and correlations, particularly those that might be missed by human observers. This allows AI to predict the likely effectiveness of immunotherapy for individual patients. In turn, that can be used to develop personalized treatment plans and, further, more effective and longer lasting patient outcomes.[2]

For instance, AI can analyze a patient’s genetic data to identify mutations that make the cancer more vulnerable to immunotherapy. This helps oncologists select the most effective treatment strategy for each patient. Moreover, AI can predict potential side effects and adverse reactions, enabling doctors to take preventive measures and manage treatment more effectively without encountering unwanted results.

In one retrospective study published recently in Science Advances, a team of researchers from several health care systems and universities discovered a new artificial intelligence (AI)-derived biomarker.[3]  The new biomarker, quantitative vessel tortuosity (QVT), examines features of blood vessels surrounding tumors, which can influence tumor behavior as well as resistance to particular forms of treatment. Compared with normal blood vessels, tumor-associated vasculature is chaotically arranged and twisted, blocking normal blood flow. These tumors with proximity to blood vessels can effectively control bodily processes for building new blood vessels—in so doing, they can redirect as much blood as possible to tumors, allowing them to grow even faster and spread throughout the body.

The good news is that the QVT biomarker can help pinpoint these problematic tumors. Using routine imaging scans, physicians can now predict with far greater certainty which patients with lung cancer will respond to immunotherapy.

First and foremost, offer guidance for patients and their physicians making critical treatment decisions. In effect, AI can help doctors determine what sort of patient will respond to particular forms of immunotherapy and those who will not.

More Than Just Medical

The advantages are not exclusively medical, as AI protocols can also blunt the financial burden associated with immunotherapy. Given the staggering costs–roughly $200,000 a year per patient– the need to non-invasively identify potentially positive responses before beginning therapy becomes financially essential.[4] AI can help show doctors which patients will get a bang for the buck through immunotherapy and those where the cost will essentially prove a waste of money.

But AI’s use in immunotherapy isn’t limited to just highly individualized patient care. AI can also analyze global cancer research data. By doing so, it can identify new potential targets for immunotherapy, accelerating the development of new forms of treatment. AI’s ability to sift through vast amounts of research data and identify relevant findings is an invaluable tool in the overall fight against cancer.

Many Challenges To Overcome

Not surprisingly, use of AI in immunotherapy is not without challenges. For one thing, as sensitive patient information is used to develop AI algorithms, data privacy and security are significant concerns, including ownership of a patient’s healthcare records and history and whose data will be shared and under what circumstances. The question of the necessity of patient consent also comes up. Additionally, transparency is essential with regard to how AI draws its conclusions and treatment recommendations. That’s particularly problematic, as the possibility exists of systemic and repeated AI-generated mistakes and missteps, possibly due to some form of inherent bias.

An overriding issue with ethical guidelines for AI in cancer treatment is essentially one of precedent. Phrased simply, the question is whether AI fits into existing legal categories or if new ones need to be developed, particularly with regard to liability. Nor is the debate an exclusively ethical one, as lawmakers are becoming increasingly aware of the necessity of drafting guidelines proactively rather than playing catch up with reactionary measures. In one example, in May 2023, the Internal Market and the Civil Liberties Committees of the European Parliament adopted a draft negotiating mandate on its first rules regarding AI.[5] The U.S. Congress is slated to consider bills of its own regrading ethical use of AI.

For patients, ethics are understandably important. But, for cancer patients, use of AI in treatment such as immunotherapy is primarily a matter of effective treatment and quality of life—and a source of growing hope.




[1] Singh, Anna, “Revolutionizing Cancer Treatment: AI’s Role in Immunotherapy Effectiveness,” Fagan Wasanni Technologies, August 1, 2023.

[2] Singh, Anna, “Revolutionizing Cancer Treatment: AI’s Role in Immunotherapy Effectiveness,” Fagan Wasanni Technologies, August 1, 2023.

[3] Alilou, Mehdi; Bera, Kaustav; Darsini, Priya; Fu, Pingfu; Gupta, Amit; Khorrami, Mohammadhadi;  Madabhushi, Anant; Patil, Pradnya Velu; Prasanna, Darsini; Velcheti, Vamsihar; Viswanathan, Vidya Sankar, “A tumor vasculature–based imaging biomarker for predicting response and survival in patients with lung cancer treated with checkpoint inhibitors,” Science Advances, November 25, 2022.

[4] “New AI-based biomarker can help predict immunotherapy response for patients with lung cancer”, Winship Cancer Institute, Emory University, January 4, 2023.

[5] “AI Act: a step closer to the first rules on Artificial Intelligence”, News, European Parliament, May 5, 2023.


This article is based on  REINVENT: Navigating Business Transformation in a Hyperdigital Era by Faisal Hoque (Fast Company Press, 2023), in association with IMD. All rights reserved.

REINVENT debuted as the #1 The Wall Street Journal bestseller and is The 21st Annual American Business Awards®, 2023 Best Business Book of The Year, The The Stevie® Awards Silver Winner.


Copyright (c) 2023 by Faisal Hoque. All rights reserved.

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