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Sin salvaguardas, la integración IA-Biología corre el riesgo de acelerar futuras pandemias
Dianzhuo Wang1, Marian Huot1,2, Zechen Zhang3
1Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, United States.
Frontiers in microbiology
|February 9, 2026
Resumen
Los modelos de lenguaje de proteínas (pLM) aceleran el diseño biológico para vacunas y terapias. Sin embargo, la ingeniería de proteínas impulsada por IA también presenta riesgos de doble uso, lo que requiere salvaguardas en los sistemas de biología de IA.
Área de la Ciencia:
- Biotecnología La biotecnología es la biotecnología.
- La inteligencia artificial es inteligencia artificial.
- Biología computacional Biología computacional.
Sus antecedentes:
- La inteligencia artificial (IA) está revolucionando el diseño de la materia biológica.
- Los modelos de lenguaje de proteínas (pLM) entrenados en vastos datos de secuencias pueden predecir, generar y optimizar proteínas.
- Los pLM integrados en tuberías experimentales permiten un diseño biológico rápido y de circuito cerrado.
Objetivo del estudio:
- Para mapear el progreso en la optimización de la aptitud de las proteínas impulsada por pLM.
- Evaluar críticamente las aplicaciones de PLM en la evolución viral y los flujos de trabajo de laboratorio.
- Proponer un marco y salvaguardas para los sistemas integrados de IA-biología.
Principales métodos:
- Revisión de los avances recientes en las aplicaciones de PLM para la ingeniería de proteínas.
- Análisis de la integración de PLM con flujos de trabajo experimentales, incluyendo el aprendizaje activo y la automatización.
- Desarrollo de un marco orientado a la capacidad para los sistemas de IA-biología.
Principales resultados:
- pLM acelera significativamente el diseño y la optimización de las proteínas funcionales.
- Los enfoques impulsados por la IA se están aplicando a los estudios de evolución viral.
- Los sistemas actuales de IA-biología presentan riesgos de doble uso que requieren una cuidadosa consideración.
Conclusiones:
- La IA, particularmente los pLM, ofrece una velocidad sin precedentes en el diseño biológico, impactando en áreas como la vacuna y el descubrimiento terapéutico.
- El rápido avance de la IA en biología requiere un marco para evaluar sistemas integrados y abordar posibles preocupaciones de doble uso.
- Se necesita investigación para desarrollar salvaguardas para los sistemas de IA-biología tanto en las etapas de entrenamiento como de inferencia.
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