UAE Oncologists Harness Artificial Intelligence to Decode Why Cancer Treatments Succeed or Fail


This story, titled "UAE doctors turn to AI to explain why cancer treatments work for some but not others" First published on The National and was retrieved from its original source on September 14, 2026.
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Cancer specialists in the UAE are turning to artificial intelligence to understand why identical treatments yield vastly different outcomes for patients with the same type and stage of the disease. Dubai-based Nexomic, established in part by Prof Humaid Al Shamsi, aims to harness next-generation AI to cancer treatment, addressing a major challenge where some patients respond well for years while others deteriorate within months.
Prof Humaid Al Shamsi, who leads cancer care at Burjeel Medical City and serves as chief executive of the Burjeel Cancer Institute, noted that cancer is far more complicated than a single mutation. Patients may share the same diagnosis and biomarkers, yet their tumors behave differently. Among women, breast cancer is the most common form, while colorectal, prostate, and lung cancers are most frequently diagnosed in men.
To tackle this, Nexomic is developing its DeepOmic platform, which combines numerous layers of tumour biology to identify patterns linked to treatment response, resistance, and disease progression. Dr Ghadeer Ghosheh, Nexomic's chief AI officer with a background from New York University Abu Dhabi and the University of Oxford, explained that the multi-omics approach analyzes multiple types of molecular information together, such as gene activity and DNA alterations, moving beyond individual markers like HER2, KRAS, or BRCA.
To ensure its computational tools are rigorously tested, Nexomic has secured a formal data-access agreement in the UK with Genomics England and Cancer Research Horizons, allowing the company to evaluate models using highly governed genomic and clinical information. Dr Mohammad Ghosheh, Nexomic's chief executive, emphasized that the technology is designed to help close the gap between cancer biology and clinical practice, supporting better treatment decisions and bringing more personalized medicine closer to patients.
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