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Alfonso Valencia and Nuria Oliver participated in the public event organized by the Spanish National Cancer Research Center (CNIO) at CaixaForum Madrid, on the occasion of World Cancer Research Day.

Valencia heads the Department of Life Sciences at the Barcelona Supercomputing Center (BSC-CNS). Oliver, a pioneer in artificial intelligence (AI) research, is director of the ELLIS Alicante Foundation.

"We are experiencing a revolution, and the impact on research is clearly visible," said Valencia. "We have more and higher-quality data than ever before, and the capacity to analyze it."

With CNIO Director Maria A. Blasco, they explained how AI is already changing the diagnosis and treatment of cancer and other diseases.

“In ten years, artificial intelligence is likely to be integrated into clinical decision support systems, which evaluate patient data in real time and allow for dynamic treatment adjustments,” says Alfonso Valencia, a pioneer of computational biology in Spain and an international leader in the field. In the future he envisions, diseases can be prevented with the help of intelligent, individualized and continuous monitoring systems.

For Maria A. Blasco, scientific director of the CNIO, artificial intelligence “is a tool that will greatly support and accelerate research, helping to diagnose and treat cancer.” For the CNIO, AI is already a reality in areas such as genomic and big data analysis; image analysis; protein structure prediction; and anti-tumor drug discovery.

https://www.cnio.es/noticias/la-revolucion-de-la-inteligencia-artificial-en-la-investigacion-del-cancer-ya-ha-comenzado-aseguran-valencia-oliver-y-blasco/ (2025).--

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It is the revolution of AI in medicine. Immunotherapy has exhibited dramatic efficacy in clinical practices especially cancer, nevertheless, substantial clinical benefits of immunotherapy have only been achieved on a minority of patients, limited by high variability in patient response to different immunotherapeutic agents, incidences of adverse events, and high costs. Therefore, reliable biomarkers or robust immune indicators to predict the applicability and side effects of immunotherapy on individuals are urgently demanded. In terms of mechanisms, despite high throughput sequencing and omics techniques could bring a broad perspective in understanding how immunotherapy coordinates with individual immune landscapes, the intratumor heterogeneity varies across individuals and metastatic sites, hampering the development of a comprehensive vision. Artificial intelligence (AI) has been demonstrated with distinct strength in images and big data processing, which could further deepen our understanding of immunotherapy and enable individualized efficacy prediction as well as side effect avoidance.

https://www.nature.com/collections/bceccijdhe?gad_source=1&gad_campaignid=21668541333&gbraid=0AAAAApRec38LVX9uqSoXcgFIBIiDUcbbZ&gclid=CjwKCAjwk7DFBhBAEiwAeYbJsekBY7OOYgfr2qEn1X36p9nsmCypL81A-cK8SRcdw1vIUhwBuf5TNxoChX4QAvD_BwE (2025).--

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