Nature Biotechnology, Published online: 19 August 2025; doi:10.1038/s41587-025-02770-1

A vast landscape of ‘undruggable’ cancer targets remains beyond the reach of conventional therapeutic agents. Recent advances in artificial intelligence (AI), however, are challenging this paradigm. Synthesizing insights from a Cancer Moonshot workshop, we argue that systemically addressing the undruggable target space with AI requires a new conceptual framework. We highlight the failure of current target taxonomies and the need for benchmarking datasets, and re-evaluate clinical validation for novel AI-driven modalities.

Advances in AI and omics enable the creation of AI virtual cells (AIVCs)—multi-scale, multimodal neural network models that simulate molecules, cells, and tissues across diverse states. This vision outlines their design and collaborative development, promising to transform biological research through high-fidelity simulations, accelerating discoveries, and fostering interdisciplinary open science collaborations.