Chemical composition and biological effects of kratom (Mitragyna speciosa): In vitro studies with implications for efficacy and drug interactions.

The safety and efficacy of kratom (Mitragyna speciosa) for treatment of pain is highly controversial. Kratom produces more than 40 structurally related alkaloids, but most studies have focused on just two of these, mitragynine and 7-hydroxymitragynine. Here, we profiled 53 commercial kratom products using untargeted LC-MS metabolomics, revealing two distinct chemotypes that contain different levels of the alkaloid speciofoline. Both chemotypes were confirmed with DNA barcoding to be M. speciosa. To evaluate the biological relevance of variable speciofoline levels in kratom, we compared the opioid receptor binding activity of speciofoline, mitragynine, and 7-hydroxymitragynine. Mitragynine and 7-hydroxymitragynine function as partial agonists of the human µ-opioid receptor, while speciofoline does not exhibit measurable binding affinity at the µ-, δ- or ƙ-opioid receptors. Importantly, mitragynine and 7-hydroxymitragynine demonstrate functional selectivity for G-protein signaling, with no measurable recruitment of ß-arrestin. Overall, the study demonstrates the unique binding and functional profiles of the kratom alkaloids, suggesting potential utility for managing pain, but further studies are needed to follow up on these in vitro findings. All three kratom alkaloids tested inhibited select cytochrome P450 enzymes, suggesting a potential risk for adverse interactions when kratom is co-consumed with drugs metabolized by these enzymes.

Physiologically based pharmacokinetic modeling framework for quantitative prediction of an herb-drug interaction.

Herb-drug interaction predictions remain challenging. Physiologically based pharmacokinetic (PBPK) modeling was used to improve prediction accuracy of potential herb-drug interactions using the semipurified milk thistle preparation, silibinin, as an exemplar herbal product. Interactions between silibinin constituents and the probe substrates warfarin (CYP2C9) and midazolam (CYP3A) were simulated. A low silibinin dose (160 mg/day × 14 days) was predicted to increase midazolam area under the curve (AUC) by 1%, which was corroborated with external data; a higher dose (1,650 mg/day × 7 days) was predicted to increase midazolam and (S)-warfarin AUC by 5% and 4%, respectively. A proof-of-concept clinical study confirmed minimal interaction between high-dose silibinin and both midazolam and (S)-warfarin (9 and 13% increase in AUC, respectively). Unexpectedly, (R)-warfarin AUC decreased (by 15%), but this is unlikely to be clinically important. Application of this PBPK modeling framework to other herb-drug interactions could facilitate development of guidelines for quantitative prediction of clinically relevant interactions.CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e107; doi:10.1038/psp.2013.69; advance online publication 26 March 2014.