AI and Machine Learning for Antidiabetic Drug Discovery from African Medicinal Plants: A Scoping Review

Diabetes mellitus represents one of the fastest-growing disease burdens in Sub-Saharan Africa, yet drug discovery efforts targeting this population remain largely driven by Western and Asian research pipelines focused on synthetic compounds. African medicinal plants represent an underexplored reservoir of bioactive compounds with demonstrated antidiabetic activity, yet systematic computational investigation of this chemical space remains limited. Recent advances in artificial intelligence and machine learning have transformed drug discovery workflows globally, enabling faster identification, characterisation, and optimisation of bioactive compounds. However, the application of these tools to African medicinal plant research remains fragmented and poorly synthesised. This scoping review aims to map the current landscape of AI and ML applications in antidiabetic drug discovery from African medicinal plants, identify critical gaps, and outline opportunities for advancing this pipeline.