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Aprovechamiento de la inteligencia artificial y los modelos de lenguaje grandes para la inmunoterapia contra el

Xinchao Wu¹, Mengtao Sun¹, Lusheng Li¹

¹Department of Genetics, Cell Biology, and Anatomy, University of Nebraska Medical Center, Omaha, Nebraska, USA.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)

|February 25, 2026

Resumen

La inteligencia artificial (IA) y el aprendizaje automático (ML) están revolucionando la inmunoterapia contra el cáncer al mejorar la estratificación de pacientes y el descubrimiento de biomarcadores. Esta revisión explora la IA

Área de la Ciencia:

Oncología
Inmunología
Inteligencia Artificial

Sus antecedentes:

La inmunoterapia contra el cáncer ha avanzado en el tratamiento oncológico, pero persisten los desafíos en la predicción de respuestas y resistencia.
La inteligencia artificial (IA) y el aprendizaje automático (ML) ofrecen herramientas poderosas para superar estos obstáculos.
Los marcos de aprendizaje profundo existentes, incluidos los modelos de lenguaje grandes (LLM), se utilizan cada vez más con datos multi-ómicos en la investigación del cáncer.

Objetivo del estudio:

Revisar sistemáticamente y evaluar críticamente las aplicaciones y el potencial traslacional de la IA/ML en la inmunoterapia contra el cáncer.
Examinar los desarrollos actuales y las direcciones futuras en IA para la inmunoterapia contra el cáncer.
Identificar información procesable para integrar la IA/ML en la inmunoterapia de precisión contra el cáncer.

Principales métodos:

Revisión exhaustiva de las aplicaciones de IA/ML en la inmunoterapia contra el cáncer.
Discusión de cuatro áreas clave: estratificación de pacientes, descubrimiento de biomarcadores, optimización de estrategias de tratamiento y modelos fundacionales/LLM.
Evaluación crítica de las limitaciones actuales y las direcciones futuras de los enfoques de IA.

Principales resultados:

Las aplicaciones de IA/ML están permitiendo avances en la estratificación de pacientes y el descubrimiento de biomarcadores.
Se están desarrollando modelos fundacionales y LLM para integrar datos complejos multi-ómicos para la inmunoterapia contra el cáncer.
La revisión identifica áreas clave donde la IA/ML puede acelerar el progreso en la oncología de precisión.

Conclusiones:

La IA/ML tiene una gran promesa para avanzar en la inmunoterapia contra el cáncer al abordar desafíos críticos.
La evaluación sistemática y la integración estratégica de la IA/ML son cruciales para realizar su potencial traslacional completo.
La investigación futura debe centrarse en superar las limitaciones y desarrollar hojas de ruta para la inmunoterapia de precisión contra el cáncer impulsada por IA.

Palabras clave:

inteligencia artificial inmunoterapia contra el cáncer modelo fundacional aprendizaje automático multi-ómicos

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