Safety-by-Design Generative Chemistry for Natural Products: Toxicity Boundaries, Interaction Risk, Validation Gates, and Human Oversight

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Generative chemistry offers a means of exploring natural product-inspired chemical space beyond directly isolated compounds, but molecular novelty and predicted activity do not establish safety, developability, or therapeutic utility. This article proposes a safety-by-design framework for integrating safety considerations throughout natural product-inspired molecular generation rather than applying toxicity filters only after candidate production. The framework links research-objective definition, natural product scaffold selection, molecular generation, natural product-likeness assessment, bioactivity hypothesis screening, and multi-objective optimization with explicit toxicity boundaries, ADMET constraints, structural-alert assessment, reactive-group review, off-target evaluation, safety-pharmacology concerns, and metabolism-related risks. Herb–drug and drug–drug interaction risks are treated as independent evidence domains because intrinsic molecular toxicity does not capture risks arising from co-exposure, metabolic interference, transport modulation, or compound-mixture effects. Model reliability is addressed through uncertainty estimation, applicability-domain assessment, out-of-distribution detection, data provenance, bias review, and documentation. Sequential validation gates are proposed to distinguish computationally plausible candidates from hypotheses that warrant in vitro, toxicological, pharmacological, or, where appropriate, in vivo investigation. Expert medicinal chemistry, toxicology, safety pharmacology, and interaction-risk review remain necessary, with human override retained at every advancement decision. The principal contribution is a structured architecture that can reduce unsafe prioritization and improve early-stage decision discipline while maintaining strict no-safety-claim and no-clinical-claim boundaries.