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AI System Tracks Effects The journal Nature Medicine has published a plan for an AI system that tracks the consequences of interventions from molecules to organisms. On August 13, the journal published an article outlining the AIDO system, which connects AI models for different levels of biology. The authors propose linking models of DNA, proteins, cells, tissues, and organism traits to track how a drug or gene modification affects this chain. When a drug or gene modification acts on an organism, it first affects molecules, then may alter the gene network and cell state, and eventually affect tissue and organism traits. The data at these levels are structured differently: DNA is a sequence of symbols, protein importance lies in its three-dimensional form, and tissue importance lies in the arrangement of neighboring cells. Therefore, the authors propose a separate model for each type of data, with AIDO based on specialized base models. These models are first trained on a large array of similar data and then fine-tuned for a specific task, such as reading DNA and RNA sequences, matching protein structure to its properties, or describing cell state or changes in organism metrics over time. The authors then want to connect these models using known biological relationships, such as how cells create RNA from DNA and assemble proteins based on RNA instructions. By linking this network to cell state data, the model gains information about interventions and the pathways they may take to alter cells. The authors propose adjusting connected models together, with organism-level predictions changing the settings of cell and molecule models, and their data refining upper-level predictions. As described in the Nature Medicine, July 2026 article, the system is designed to calculate possible responses through the gene influence network. 🔗 Read original →