Cannabinoids in Diabetes: Integrating Scientometric Trends with Mechanistic, Pharmacokinetic, and Clinical Evidence

Cannabinoid signaling has attracted increasing interest in diabetes because the endocannabinoid system regulates energy balance, glucose and lipid metabolism, inflammation, and tissue homeostasis. However, its therapeutic relevance remains uncertain. This study combined scientometric mapping with a critical synthesis of mechanistic, pharmacokinetic, and clinical evidence on cannabinoids and diabetes published between 2004 and 2024. A structured search of the Web of Science Core Collection identified 459 original research articles, which were analyzed using Bibliometrix and complementary visualization tools. Scientific production increased markedly after 2016 and became progressively more diversified, with growing prominence of inflammation, oxidative stress, cannabis exposure-related themes, and broader mechanistic and population-level research questions. Mechanistic evidence strongly implicates excessive peripheral CB1 signaling in hepatic lipogenesis, adipose dysfunction, impaired insulin responsiveness, and related metabolic abnormalities, whereas CB2-mediated effects remain context-dependent. Cannabidiol is supported mainly by preclinical evidence of anti-inflammatory, antioxidant, and tissue-protective activity rather than consistent glucose-lowering effects. Clinical translation is further constrained by formulation-dependent oral exposure, extensive first-pass metabolism, food effects, broad tissue distribution, drug-interaction potential, and interindividual variability. Clinical evidence remains limited: brain-penetrant CB1 blockade improved selected metabolic outcomes but was restricted by psychiatric toxicity, while cannabidiol has not demonstrated consistent glycemic efficacy. Overall, cannabinoid research in diabetes shows substantial mechanistic development but limited clinical convergence. Future progress will require compound- and target-specific strategies, peripheral or tissue-selective modulation, standardized formulations, exposure–response characterization, appropriate patient stratification, and clinically meaningful outcome assessment.