My Chemical Harness: Evolutionary Molecular Design over Synthetic Pathways with Large Language Model Agents
arXiv:2606.11256v1 Announce Type: cross Abstract: Designing molecules with target properties is most useful when candidate structures are accompanied by feasible synthetic routes. We introduce My Chemical Harness, a route-native evolutionary framework for goal-directed molecular design in which the search population consists of executable synthetic pathways rather than isolated molecular graphs. Each route is built from purchasable building blocks and reaction templates, executed by deterministic chemistry tools, and scored through task-specific molecular oracles. Large language models (LLMs)
LLMs have matured to a level where their generative and reasoning capabilities can be effectively applied to complex scientific problems like molecular design, and advancements in computational chemistry tools provide the necessary substrate.
This work represents a step towards fully autonomous and integrated molecular design, significantly accelerating the discovery of new materials and therapeutics by ensuring synthetic feasibility from the outset.
Molecular design will shift from a trial-and-error process with post-hoc synthesis considerations to a more integrated approach where synthetic routes are inherent to the design process, driven by AI agents.
- · Pharmaceutical companies
- · Chemical manufacturers
- · AI platform developers
- · Synthetic biology researchers
- · Traditional drug discovery models
- · CROs focused solely on molecular screening
Molecular design cycles for new drugs and materials will become significantly shorter and more efficient.
The automation of synthetic pathway design will lead to the discovery of previously inaccessible or overlooked chemical compounds.
This could usher in an era of 'on-demand' molecular manufacturing, where precise chemicals are designed and synthesized rapidly for specific applications, transforming multiple industries.
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Read at arXiv cs.LG