Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 2 appraisals
Food & function
Application of artificial intelligence in synbiotic and functional food development for precision nutrition
Synbiotic and functional food formulations modulate gut microbiota, SCFA production, immune signalling and metabolic pathways, yet current development pipelines remain largely empirical and constrained by nonlinear trade-offs among probiotic viability, prebiotic functionality and sensory acceptance. Artificial Intelligence (AI) and machine learning (ML) approaches offer data-driven strategies to support formulation, multi-objective optimization and functional assessment. This review systematically identified and critically synthesized literature published between 2020 and 2025 across five thematic domains: (i) formulation and ingredient selection; (ii) viability and shelf-life modelling; (iii) functional and antioxidant bioactivity assessment; (iv) sensory and consumer prediction; and (v) personalization and precision nutrition. Studies were identified through database searches and screened for relevance to synbiotics, functional foods, microbiome modulation and nutrition outcomes, following PRISMA 2020 guidelines. Current evidence indicates that AI can assist ingredient pairing, viability forecasting, sensory modelling and functional property prediction, often complementing conventional statistical tools such as Response Surface Methodology in multivariate design spaces. However, most implementations remain computational or pilot-scale, with minimal integration of microbiome-informed personalization, clinical endpoints or adherence outcomes. Major translational gaps include data heterogeneity, model interpretability, regulatory substantiation and scarcity of longitudinal evidence. AI should therefore be considered a complementary decision-support tool that can accelerate hypothesis generation and formulation refinement rather than substitute mechanistic validation or human trials. Bridging computational modelling with microbiome science and nutritional evidence may enable precision synbiotic strategies and next-generation functional food innovation.
6 July 2026
Read appraisal →Philosophical transactions of the Royal Society of London. Series B, Biological sciences
A meta-analysis of gut microbiome research in malnourished African populations: a natural language processing approach
Malnutrition still affects millions of children in Africa. Changes in the gut microbiome have been implicated in malnutrition, but there has been inconsistent nomenclature of microbes. This meta-analysis reviews the microbiome literature using natural language processing (NLP) methods. We searched PubMed for gut microbiome studies of undernourished children living in low- and middle-income countries (LMICs). The primary analysis focused on continental coverage and study characteristics of microbiome research in sub-Saharan Africa (ss-Africa). We also used an NLP tool for normalizing primary data from full-text publications in ss-Africa compared with other LMICs, and between diseased and healthy children. We identified 16 studies. Most studies were conducted in Malawi and characterized the faecal microbiome using 16S rRNA sequencing. For comparison, 18 studies conducted in Bangladesh, India, Pakistan and Peru were included. With this, we identified frequently reported microbes that were distinctly identified in ss-Africa and highlighted possible signatures of an undernourished faecal microbiome across the globe. The consistent associations between elevated Pseudomonadota levels and severe acute malnutrition provide new insights into host-microbiome interactions in African contexts. However, the overlap between taxa associated with healthy and stunting underscores the need for further research to better inform potential targeted interventions in Africa. This article is part of the theme issue 'Biological, biomedical and environmental drivers of stunting'.
15 May 2026
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