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

Abstract

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.

Figure 1

Mean concentration–time profile (0–6 hours) of midazolam in 19 healthy volunteers following an 8 mg oral midazolam dose given alone (open symbols) or following a 14-day treatment with milk thistle product (solid symbols). Lines denote physiologically based pharmacokinetic model simulations of the midazolam concentration–time profile when given alone (black) or with milk thistle (green). The dotted green line denotes incorporation of reversible inhibition of CYP3A, whereas the dashed green line denotes incorporation of mechanism-based inhibition of CYP3A. Symbols and error bars denote observed means and SDs, respectively, and were obtained from ref. .

Figure 2

Geometric mean concentration–time profile of (a) warfarin, (b) midazolam, and (c) silibinin in 12 healthy volunteers following a 10 mg oral dose of warfarin or 5 mg oral dose of midazolam given alone (open symbols) or following a 7-day treatment with silibinin (solid symbols). Lines in a and b denote physiologically based pharmacokinetic (PBPK) model simulations of the concentration–time profiles when the probe substrates were given alone (black) or with silibinin (green). Blue and orange lines in c denote PBPK model simulations of the concentration–time profiles of silybin A and silybin B, respectively. Symbols and error bars denote observed geometric means and upper limits of the 90% confidence interval, respectively.

Figure 3

Effects of silibinin (1,650 mg/day for 7 days) on (a,c,e) C_max and (b,d,f) AUC of (a,b) (R)-warfarin, (c,d) (S)-warfarin, and (e,f) midazolam in 12 healthy volunteers following oral administration of warfarin (10 mg) and midazolam (5 mg). Open symbols connected by solid lines denote individual values. Solid symbols connected by dashed lines denote geometric means.

Figure 4

Base physiologically based pharmacokinetic model structure. Model structure was modified from the literature. Organ weights and blood flows were obtained from the International Commission on Radiological Protection. Following oral administration, drug transfer from dosing compartment to intestine is driven by the oral absorption rate constant (k_a). Drug clearance (Cl) is mediated by metabolic processes in the intestine and liver. The pancreas and spleen were combined into a hybrid “organ” designated as PSP.