Summary
This narrative review examines the heterogeneity in conventional probiotic therapy outcomes and identifies biological and environmental drivers of variable efficacy. It synthesises emerging methodological advances in strain mining and engineering, multi-omics data integration, and predictive modelling to support the development of precision-engineered, functionally enhanced probiotics tailored to individual host characteristics. The authors argue that integration of data-driven approaches with personalised microbial therapeutics represents a transformative direction for microbiome-informed nutrition.
Regional applicability
This is a methodological and conceptual review with no specified geography; findings are applicable globally, including United Kingdom clinical and nutritional practice, though implementation would require context-specific validation of personalised prediction models and strain availability within UK healthcare systems.
Key measures
Probiotic treatment efficacy, host metabolic responses, strain functional characteristics, multi-omics prediction models
Outcomes reported
The review examines factors affecting probiotic efficacy and presents emerging frameworks using multi-omics data to predict treatment outcomes and metabolic responses. It synthesises advances in strain engineering and data-driven models for personalised probiotic design.
Topic tags
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