Current Drug Metabolism - Volume 15, Issue 8, 2014

Drug-drug interaction (DDI) is one important topic in drug discovery, drug development and clinical practice. Recently, a novel approach, in vivo information-guided prediction (IVIP), was introduced for predicting the magnitude of pharmacokinetic DDIs which are caused by changes in cytochrome P450 (CYP) activity. This approach utilizes two parameters, i.e. CR (the apparent contribution of the target metabolizing enzyme to the clearance of the substrate drug) and IX (the apparent effect of a perpetrator on the target CYP) to describe the magnitude of DDI between a perpetrator and a victim drug. The essential concept of this method assumes that at a given dose level, the IX for a given perpetrator remains constant whatever the victim drug is. Usually, this IVIP method is only based on information from clinical studies and does not need in vitro information. In this review, basic concept, application and extension, as well as pros and cons of the IVIP method were presented. How to apply this approach was also discussed. Thus far, this method displayed good performance in predicting DDIs associated with CYPs, and can be used to forecast the magnitude of a large number of possible DDIs, of which only a small portion have been investigated in clinical studies. The key concept of this static approach could even be implemented in dynamic modeling to assess risks of DDIs involving drug transporters.

Pharmacokinetic (PK) drug-drug interactions (DDIs) give rise to adverse events and/or reduced efficacy. Comprehensive, systematic and mechanistic approaches have been applied in the evaluation, propagation and management of the interaction potential of a new drug during its development and clinical use. However, the role of drug metabolite(s) in DDIs was not extensively investigated. Recently, regulatory bodies have proposed that metabolites at ≥25% of the parent drug’s area under the time-concentration curve (AUC) and/or >10% of the total drug-related exposure should be investigated in vitro for DDI potential. This review aimed to identify the drugs and their metabolites meeting the official guidance’s criteria for DDI studies, and to assess whether the eligible drugs caused significant clinical PK DDIs and furthermore whether the metabolites contributed to the observed PK DDIs. Eighty seven drugs were eligible and nearly 45% (39/87) drugs were not reported with clinical PK DDIs. About 78% (68/87) drugs demonstrated inhibitory and/or inducible effects on drug-metabolizing enzymes and/or drug transporters; while the remaining 19 (22%) parent drugs showed no such effects. For 8 drugs (∼9%), their metabolites were able to inhibit and/or induce the drug-metabolizing enzymes and drug transporters. Three drugmetabolite pairs were found to be the perpetrators of the complex PK DDIs. Our retrospective analysis suggested that the PK DDI risks caused by metabolites alone might not be high, which is somewhat different from the conclusions from some other studies on this topic. However, circulating drugs often work as perpetrators of PK DDIs suggesting a need for more efforts to characterize the roles of their metabolites. Our study should be of value in stimulating discussions among the scientific community on this important topic.

Herbal medicines have been widely used for thousands of years, and now are gaining continued popularity worldwide as a complementary or alternative treatment for a variety of diseases, rehabilitation and health care. Since herbal medicines contain more than one pharmacologically active ingredient and are commonly used with many prescribed drugs, there are potential herb-drug interactions. A variety of reported herb-drug interactions are of pharmacokinetic origin, arising from the effects of herbal medicines on metabolic enzymes and/or transporters. Such an alteration in metabolism or transport can result in changes in absorption, distribution, metabolism, and excretion (e.g., induction or inhibition of metabolic enzymes, and modulation of uptake and efflux transporters), leading to changed pharmacokinetics of the concomitantly prescribed drugs. Pharmacokinetic herb-drug interactions have more clinical significance as pharmacokinetic parameters such as the area under the plasma concentration-time curve (AUC), the maximum plasma concentration (Cmax) or the elimination half-life (t1/2) of the concomitant drug alter. This review summarizes the mechanism underlying herb-drug interactions and the approaches to identify the interactions, and discusses pharmacokinetic interactions of eight widely used herbal medicines (Ginkgo biloba, ginseng, garlic, black cohosh, Echinacea, milk thistle, kava, and St. John’s wort) with conventional drugs, using various in vitro, animal in vivo, and clinical studies. The increasing understanding of pharmacokinetic herb-drug interactions will make health care professionals and patients pay more attention to the potential interactions.

Cytochromes P450 enzymes, especially CYP3A4, are responsible for metabolizing a broad range of anticancer drugs. Combination therapy is common in patients with cancer, which may cause potential drug drug interactions (DDIs) leading to increased risk of side-effects/toxicity or decreased effectiveness. The review summarizes CYP3A4-mediated DDIs, with anticancer drugs as CYP3A4 substrates or modulators, in clinical trials during cancer therapy and aims to increase clinicians' awareness to take caution to reduce the risk.

Combination chemotherapy has become the primary strategy for treating cancer; however, the clinical success of combination treatments is limited by the distinct pharmacokinetics (PK) of different drugs, which lead to nonuniform distribution and an inability to coordinate dosing regimes at the site of the tumor. In the first half of this review, we will discuss the recent development of nanoparticlebased combination strategies to overcome these limitations. Nanoparticles are able to co-encapsulate and carry multiple drugs with different hydrophobicities while maintaining precise ratiometric loading and delivery. They can also temporally sequence the release of multiple drugs and reduce undesirable PK interactions. In the second half of this review, we will touch on the key factors that affect nanoparticle stability and distribution. Nanoparticles provide a promising strategy to improve combinatorial cancer treatments by better controlling PK and metabolic differences between drugs.

Sudan I [1-(phenylazo)-2-naphthol, C.I. Solvent Yellow 14] is an industrial dye, which was found as a contaminant in numerous foods in several European countries. Because Sudan I has been assigned by the IARC as a Category 3 carcinogen, the European Union decreed that it cannot be utilized as food colorant in any European country. Sudan I induces the malignancies in liver and urinary bladder of rats and mice. This carcinogen has also been found to be a potent mutagen, contact allergen and sensitizer, and exhibits clastogenic properties. The oxidation of Sudan I increases its toxic effects and leads to covalent adducts in DNA. Identification of enzymatic systems that contribute to Sudan I oxidative metabolism to reactive intermediates generating such covalent DNA adducts on the one hand, and to the detoxification of this carcinogen on the other, is necessary to evaluate susceptibility to this toxicant. This review summarizes the identification of such enzymes and the molecular mechanisms of oxidation reactions elucidated to date. Human and animal cytochrome P450 (CYP) and peroxidases are capable of oxidizing Sudan I. Of the CYP enzymes, CYP1A1 is most important both in Sudan I detoxification and its bio-activation. Ring-hydroxylated metabolites and a dimer of this carcinogen were found as detoxification products of Sudan I generated with CYPs and peroxidases, respectively. Oxidative bio-activation of this azo dye catalyzed by CYPs and peroxidases leads to generation of proximate genotoxic metabolites (the CYP-catalyzed formation of the benzenediazonium cation and the peroxidase-mediated generation of one-electron oxidation products), which covalently modify DNA both in vitro and in vivo. The predominant DNA adduct generated with the benzenediazonium cation was characterized to be 8-(phenylazo)guanine. The Sudan I radical species mediated by peroxidases reacts with the -NH2 group in (deoxy)guanosine, generating the 4-[(deoxy)guanosin-N2-yl]Sudan I product. Sudan I was also found to be a strong inducer of CYP1A1 and its enzyme activity mediated by the aryl hydrocarbon receptor, thereby increasing its own genotoxic potential and the cancer risk for humans.