Forensic Validation of Monteverdia ilicifolia Phytotherapeutic Profiles by TLC-CD and Machine Learning: Implications for Public Health
摘要
The species Monteverdia ilicifolia (Mart. ex Reissek) Biral, Celastraceae, commonly known as espinheira-santa, is listed in the National List of Medicinal Plants of Interest to the Unified Health System. Due to its pharmacological properties and cost-effectiveness, herbal medicines derived from M. ilicifolia leaves are recommended by the Brazilian public health system and are widely used as a complementary therapy for conditions such as gastritis and indigestion, among other gastrointestinal disorders. Within the scope of public health, there is an urgent need to develop quality control methods that ensure the integrity of M. ilicifolia–based herbal medicines. This study analyzed 25 samples of M. ilicifolia leaf–based herbal products. The developed method using thin-layer chromatography combined with computational densitometry and machine learning enabled the classification of the samples into four distinct groups, underscoring the ineffective quality control of M. ilicifolia products marketed in Brazil and used as complementary treatments, revealing a pronounced lack of standardization in the plant material, with substances and/or their quantities varying significantly across the analyzed samples, raising serious public health concerns.
Graphical Abstract