Clinical trials in nutrition should explore, test, and validate nutritional solutions to maintain and improve human health. These solutions can come in the form of (micro-)nutrients, bioactives, (functional) ingredients, diets, or supplements. They can address digestive, metabolic, endocrine, immune, cardiovascular, muscle/bone and cognitive health. To render these trials more comparable and translational, traditional, and often non-standardized study designs must be complemented by clinical studies featuring the following characteristics:classical RCTs with group-average comparisons must be complemented by longitudinal, or (nested) n-of-1 studies, in which every subject is its own case and control; enrolled subjects should be clinically and molecularly phenotyped; administered diets, especially when applied under specific terms, should be clearly defined and described; intervention studies should apply safe, well-defined nutritional inputs or challenges and probe the elasticity of the human metabolic system in addition to sampling at homeostasis. Interventions can be betterinformed and designed upfront by bioinformatics and artificialintelligence:considering molecular mechanisms of e.g.metabolic, digestive,or immune health, the biological effects of bioactive ingredients (micronutrients, phytonutrients, pre-/probiotics, bioactive peptides) can be either computationally retrieved from existing literature4, or –to some extent– predicted in silico, thereby limiting the number of compounds or ingredients to be tested5. The best sources for those targeted functional nutritional compounds can be identified by computational mining of the genomes, metabolomes, and proteomes/peptidomes of e.g. plants and foods, thereby fostering both healthy and sustainable diets.