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BEIJING, May 7, 2026 — DeepoMe Limited today announced the release of a new preprint introducing SEWO — the Steerable Medicine World Model — a framework designed to shift the conversation from bigger biomedical predictors toward trustworthy, auditable, and steerable world models.The manuscript, "World Models for Biomedicine: A Steerability Framework," published on Preprints.org by MDPI, argues that the next generation of biomedical AI should not only predict biological trajectories, but also allow clinicians and researchers to guide them through explicit, inspectable, and biologically meaningful directional signals.
At the center of the work is a simple question: Can you steer it?
"Everyone is building bigger engines. We are asking whether anyone has checked the steering system — or whether the vehicle even has one," said Jianghui Xiong, lead author of the preprint. "A world model for medicine should not merely forecast what may happen next. It should allow a clinician or researcher to ask, 'What if we move in this direction instead?' — and then provide a reliable, auditable answer."
The SEWO Framework: From Black-Box Prediction to Steerable Guidance
The SEWO framework challenges the dominant assumption that biomedical AI progress should be measured primarily by model size, data scale, or benchmark accuracy. Instead, it proposes steerability as a foundational property of trustworthy biomedical world models.
DeepoMe describes the concept through a metaphor: the rider and the horse. A rider does not micromanage every muscle of the horse. The rider provides directional signals through the reins, while the horse maintains balance, adapts to terrain, and moves forward with its own embodied robustness.
Five Structural Constraint Points
The preprint outlines five core constraint points that any candidate biomedical world model can be evaluated against:
1. State Representation — Biological states should be represented through modular and interpretable components, including modular Intrinsic Capability (mIC) vectors.
2. Capability Quantification — SEWO introduces the Capomics Index (CI = 1 minus PAI) to estimate how far a biological system is from functional breakdown.
3. Input-Response Semantics — Perturbations should be mapped into computationally tractable inputs with explicit biological meaning.
4. Counterfactual Transition Modeling — A valid biomedical world model should simulate plausible "what-if" trajectories under different intervention scenarios.
5. Five-Gate Quality Control Loop — A reasoning scaffold organized as State to Input to Response to delta-mIC to Phenotype, allowing each step to be independently inspected and falsified.
Together, these constraint points form what the authors call a deductive constraint framework: a structural chain of reasoning in which each link is explicit, auditable, and less vulnerable to silent failures.
Steering, Not Merely Predicting
A central claim of the SEWO preprint is that biomedical systems are dynamic, adaptive systems that respond to signals — not passive targets of prediction. SEWO extends this logic into biomedical AI: instead of asking AI to dictate outcomes from above, the framework asks whether a model can accept biologically meaningful directional input, recompute a coherent trajectory, and make its reasoning inspectable.
This principle is summarized by the project's core phrase: Steering, not predicting.
Launch of steerable.world
DeepoMe also announced the launch of steerable.world as the digital home for the SEWO project. The website serves as a hub for SEWO-related updates, preprint materials, future technical resources, and community discussion.
Availability
The preprint "World Models for Biomedicine: A Steerability Framework" is available at https://doi.org/10.20944/preprints202605.0366.v1 and open for community comment.
Important notice: This manuscript is a preprint and has not yet undergone peer review.
About DeepoMe Limited
DeepoMe Limited is a Beijing-based research company focused on structural, interpretable frameworks for biomedicine and trustworthy AI. Its work includes the Capomics platform for capability-centric biological analysis, the EvoSika initiative for evolutionary systems modeling, and the SEWO project for steerable medicine world models.