Abu Dhabi: AI aids in identifying at-risk cancer individuals, drug development

There has been a paradigm shift from cancer diagnosis through external observations to molecular-based classifications, focusing on the genetic makeup of cancers

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Ashwani Kumar

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Image used for illustrative purposes. File Photo
Image used for illustrative purposes. File Photo

Published: Wed 15 May 2024, 6:55 PM

Artificial intelligence, particularly machine learning, stands as a powerful ally in cancer care, a medical expert said during the Abu Dhabi Global Healthcare Week.

Dr Faek El Jamali, staff physician, colorectal surgeon, Digestive Disease Institute at Cleveland Clinic Abu Dhabi (CCAD), noted that AI contributes to the detection and prevention of cancer.


“AI accelerates drug discovery by deciphering the complexities of protein structures, vital for developing targeted therapies. AI aids in identifying at-risk individuals through a comprehensive analysis of health records, enabling clinicians to personalise prevention strategies. By leveraging AI’s predictive capabilities, we can proactively address potential cancer risks and optimise preventive measures,” Dr Jamali, who was also the chair of the Cleveland Clinic Global Summit on innovations in cancer, told Khaleej Times.

Dr Faek El Jamali. Photo: Supplied
Dr Faek El Jamali. Photo: Supplied

Dr Jamali noted that cancer is fundamentally a genetic disease, where errors occur at the genetic level within the cancer cells themselves.


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“Genetic testing becomes pivotal in two scenarios. Firstly, it helps identify inherited patterns of cancer within families, guiding tailored treatments and management strategies. Secondly, genetic testing aids in prevention efforts, particularly at a population level. Emerging blood tests hold promise for early cancer screening, potentially revolutionising routine check-ups by providing insights into individual cancer risks.”

Talking about the latest developments in cancer prediction and detection, Dr Jamali underlined that there has been a paradigm shift from cancer diagnosis through external observations to molecular-based classifications, which focuses on the genetic makeup of cancers.

Dr Jamali added: "This precision approach allows for tailored treatments that specifically target cancer-causing mutations, sparing healthy cells. Additionally, advancements in immunotherapy and understanding the body’s immune response further enhance cancer treatment strategies. Integrating these modalities marks a transformative era in cancer therapy, driving towards precision medicine and improved patient outcomes.”

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