Toxicokinetics of Herbal Products

Abstract

Pharmacokinetics (PK) and toxicokinetics (TK) mean essentially the same thing, only the final effect of the studied substance differs. In this chapter, the abbreviation “TK” is usually used to acknowledge the title of the book (toxicology), but also the abbreviation “PK” is used, depending on the context. TK is an essential part of the characterization of a conventional pharmaceutical and, besides its “intrinsic scientific” value, TK constitutes a backdrop for understanding and delineating a substance’s in vivo potency, potential toxicities, and particular clinical conditions. The same TK principles should apply to herbal medicinal products; however, these products are complex chemical mixtures, with tens or hundreds of major and minor components belonging to a variety of chemical groups and classes, making it rather difficult to study their TK, both in theory and in practice. The TK of an herbal product should address both the time course of its active constituents, and the impact of the various components on the TK processing (metabolism and transport) of its own constituents and simultaneously administered pharmaceuticals.

This chapter describes some of the major areas that should be addressed when investigating the PK/TK of herbal medicinal products. Appropriate analytical methods exist to address major TK issues, despite the complex composition of herbal products. However, the success of these studies depends on pharmacodynamic and mechanistic studies to decide which of the many components should be targeted for the ADME (absorption, distribution, metabolism, and excretion) characterization. The prevailing tenet in the area of herbal products is that the “whole product” is responsible for the therapeutic action. However, such a statement is scientifically inadequate and therefore not really helpful. The dissection of contributing components and their interactions with respect to both therapeutic effects and potential toxicities requires the application of advanced analytical and high-content technologies, including “omics” methods, computational modelling and simulation approaches, and, most of all, systems biological thinking.