Lack of CYP3A4 inhibition by grapefruit juice and ketoconazole upon clozapine administration in vivo

Interactions between grapefruit juice and psychotropic medications: an update of the literature and an original case series

INTRODUCTION

There is a large body of preclinical data implicating that grapefruit juice (GJ) inhibits many CYP 450 isoforms. The potential of GJ-to-drug is of high relevance to clinical psychiatry, because a wide range of psychotropic medicines undergo CYP 450 metabolism and P-gp transport.

AREAS COVERED

Relevant data were identified by searching the electronic databases up to February 2024. This work constitutes a summary of preclinical and clinical data on GJ impact on CYP 450 metabolism, P-glycoprotein, and organic anion-transporting polypeptides (OATPs), with focus on studies that assessed GJ-to-psychotropic drug interactions. Additionally, an unpublished case series of nine patients is provided.

EXPERT OPINION

The impact of GJ on CYP 3A4 appears to be the critical mechanism for the majority of GJ-to-psychopharmacotherapy interactions described in human studies or case reports. However, there are studies and cases of patients clearly showing that this is not the only route explaining the GJ effect, and at times, this particular is of no relevance and that other CYP 450 isoforms as well as drug transporting proteins might be involved. The risk of GJ-to-psychotropic drugs needs to be further evaluated in a 'real-world' setting and apply not only measures of pharmacokinetics but also treatment effectiveness and safety.

Clinically Relevant Interactions between Atypical Antipsychotics and Anti-Infective Agents

This is a comprehensive review of the literature on drug interactions (DIs) between atypical antipsychotics and anti-infective agents that focuses on those DIs with the potential to be clinically relevant and classifies them as pharmacokinetic (PK) or pharmacodynamic (PD) DIs. PubMed searches were conducted for each of the atypical antipsychotics and most commonly used anti-infective agents (13 atypical antipsychotics by 61 anti-infective agents/classes leading to 793 individual searches). Additional relevant articles were obtained from citations and from prior review articles written by the authors. Based on prior DI articles and our current understanding of PK and PD mechanism, we developed tables with practical recommendations for clinicians for: antibiotic DIs, antitubercular DIs, antifungal DIs, antiviral DIs, and other anti-infective DIs. Another table reflects that in clinical practice, DIs between atypical antipsychotics and anti-infective agents occur in patients also suffering an infection that may also influence the PK and PD mechanisms of both drugs (the atypical antipsychotic and the anti-infective agent(s)). These tables reflect the currently available literature and our current knowledge of the field and will need to be updated as new DI information becomes available.

Antiglucocorticoid and related treatments for psychosis

BACKGROUND

Hypothalamic-pituitary-adrenal (HPA) axis dysregulation has been implicated in the development and relapse of psychotic disorders. Elevated cortisol secretion has been positively linked with symptom severity in people with psychosis. Antiglucocorticoid and related drugs that target the HPA axis may be useful for the treatment of individuals with psychosis.

OBJECTIVES

1. To determine the effects of antiglucocorticoid and related drugs for the treatment of psychosis, when used alone or in combination with antipsychotic medication.2. To determine whether the effects of these medications differs between those in a prodromal phase or first episode of psychosis, and those with more established illness.

SEARCH METHODS

We searched the Cochrane Schizophrenia Group's Trials Register (August 2009 and April 2014).

SELECTION CRITERIA

Randomised controlled trials (RCTs) comparing antiglucocorticoid and related drugs compared to placebo (either as a sole treatment or as an adjunct to atypical antipsychotics, typical antipsychotics, antidepressants or other combination treatment) for people with a primary diagnosis of a psychotic disorder, or for individuals at high risk of developing a psychotic disorder.

DATA COLLECTION AND ANALYSIS

Review authors independently selected trials, assessed methodological quality and extracted data. We used a fixed-effect meta-analysis. We calculated risk ratios (RRs) with 95% confidence intervals (CIs) for dichotomous outcomes, and mean differences (MDs) and standardised mean differences (SMDs) with 95% CIs for continuous measures. We assessed risk of bias for included studies and used GRADE (Grading of Recommendations Assessment, Development and Evaluation) to create a 'Summary of findings' table.

MAIN RESULTS

We included 11 studies that randomly assigned 509 people with schizophrenia, schizoaffective disorder or psychotic depression. No trials were conducted in patients at their first episode of psychotic illness and none included populations at high risk for developing psychosis. Our pre-stated outcomes of interest were mental state, global state, general functioning, adverse effects and quality of life.Two trials compared antiglucocorticoid drugs (mifepristone) versus placebo as sole treatment. Limited data from one trial showed no difference in the proportion responding to mifepristone when mental state was assessed immediately post intervention using the Brief Psychiatric Rating Scale (BPRS) (n = 5, 1 RCT, MD -5.20, 95% CI -17.91 to 7.51; very low-quality evidence); depressive symptoms (Hamilton Rating Scale for Depression (HAMD) total) were also similar between groups (n = 5, 1 RCT, MD 1.67, 95% CI -16.44 to 19.78; very low-quality evidence). However, a significant difference favoured treatment at short-term follow-up for global state (30% reduction in total BPRS, n = 221, 1 RCT, RR 0.58, 95% CI 0.38 to 0.89; low-grade quality evidence). This effect was also seen for short-term positive psychotic symptoms (50% reduction in BPRS positive symptom subscale, n = 221, 1 RCT, RR 0.60, 95% CI 0.43 to 0.84; low-grade quality evidence). Participants receiving mifepristone experienced a similar overall number of adverse effects as those receiving placebo (n = 226, 2 RCTs, RR 0.92, 95% CI 0.77 to 1.09; moderate-quality evidence). No data on general functioning or quality of life were available.One trial compared an antiglucocorticoid, dehydroepiandrosterone (DHEA), as an adjunct to atypical antipsychotic treatment to adjunctive placebo. Data for main outcomes of interest were of low quality, and analysis of useable data showed no significant effects of treatment on mental state or adverse effects. Data on global state, general functioning and quality of life were not available.Data from six trials comparing antiglucocorticoid drugs as an adjunct to combination treatment versus adjunctive placebo showed no significant differences between groups in mean endpoint scores for overall psychotic symptoms (n = 171, 6 RCTs, SMD 0.01, 95% CI - 0.29 to 0.32) or positive psychotic symptoms (n = 151, 5 RCTs, SMD -0.07, 95% CI - 0.40 to 0.25). Data from three trials showed no differences between groups in mean endpoint scores for negative symptoms (n = 94, 3 RCTs, MD 2.21, 95% CI -0.14 to 4.55). One study found improvements in global state that were similar between groups (n = 30, 1 RCT, RR 0.58, 95% CI 0.32 to 1.06; very low-quality evidence). In this comparison, pooled results showed that antiglucorticoids caused a greater overall number of adverse events (n = 199, 7 RCTs, RR 2.66, 95% CI 1.33 to 5.32; moderate quality evidence), but no quality of life data were available.

AUTHORS' CONCLUSIONS

Good evidence is insufficient to conclude whether antiglucocorticoid drugs provide effective treatment for psychosis. Some global state findings suggest a favourable effect for mifepristone, and a few overall adverse effect findings favour placebo. Additional large randomised controlled trials are needed to justify findings.

Clinically significant drug interactions with atypical antipsychotics

Atypical antipsychotics [also known as second-generation antipsychotics (SGAs)] have become a mainstay therapeutic treatment intervention for patients with schizophrenia, bipolar disorders and other psychotic conditions. These agents are commonly used with other medications--most notably, antidepressants and antiepileptic drugs. Drug interactions can take place by various pharmacokinetic, pharmacodynamic and pharmaceutical mechanisms. The pharmacokinetic profile of each SGA, especially with phase I and phase II metabolism, can allow for potentially significant drug interactions. Pharmacodynamic interactions arise when agents have comparable receptor site activity, which can lead to additive or competitive effects without alterations in measured plasma drug concentrations. Additionally, the role of drug transporters in drug interactions continues to evolve and may effect both pharmacokinetic and pharmacodynamic interactions. Pharmaceutical interactions occur when physical incompatibilities take place between agents prior to drug absorption. Approximate therapeutic plasma concentration ranges have been suggested for a number of SGAs. Drug interactions that markedly increase or decrease the concentrations of these agents beyond their ranges can lead to adverse events or diminished clinical efficacy. Most clinically significant drug interactions with SGAs occur via the cytochrome P450 (CYP) system. Many but not all drug interactions with SGAs are identified during drug discovery and pre-clinical development by employing a series of standardized in vitro and in vivo studies with known CYP inducers and inhibitors. Later therapeutic drug monitoring programmes, clinical studies and case reports offer methods to identify additional clinically significant drug interactions. Some commonly co-administered drugs with a significant potential for drug-drug interactions with selected SGAs include some SSRIs. Antiepileptic mood stabilizers such as carbamazepine and valproate, as well as other antiepileptic drugs such as phenobarbital and phenytoin, may decrease plasma SGA concentrations. Some anti-infective agents such as protease inhibitors and fluoroquinolones are of concern as well. Two additional important factors that influence drug interactions with SGAs are dose and time dependence. Smoking is very common among psychiatric patients and can induce CYP1A2 enzymes, thereby lowering expected plasma levels of certain SGAs. It is recommended that ziprasidone and lurasidone are taken with food to promote drug absorption, otherwise their bioavailability can be reduced. Clinicians must be aware of the variety of factors that can increase the likelihood of clinically significant drug interactions with SGAs, and must carefully monitor patients to maximize treatment efficacy while minimizing adverse events.

The effect of grapefruit juice on drug disposition

INTRODUCTION

Since their initial discovery in 1989, grapefruit juice (GFJ)-drug interactions have received extensive interest from the scientific, medical, regulatory and lay communities. Although knowledge regarding the effects of GFJ on drug disposition continues to expand, the list of drugs studied in the clinical setting remains relatively limited.

AREAS COVERED

This article reviews the in vitro effects of GFJ and its constituents on the activity of CYP enzymes, organic anion-transporting polypeptides (OATPs), P-glycoprotein, esterases and sulfotransferases. The translational applicability of the in vitro findings to the clinical setting is discussed for each drug metabolizing enzyme and transporter. Reported AUC ratios for available GFJ-drug interaction studies are also provided. Relevant investigations were identified by searching the PubMed electronic database from 1989 to 2010.

EXPERT OPINION

GFJ increases the bioavailability of some orally administered drugs that are metabolized by CYP3A and normally undergo extensive presystemic extraction. In addition, GFJ can decrease the oral absorption of a few drugs that rely on OATPs in the gastrointestinal tract for their uptake. The number of drugs shown to interact with GFJ in vitro is far greater than the number of clinically relevant GFJ-drug interactions. For the majority of patients, complete avoidance of GFJ is unwarranted.

ABCB1 and cytochrome P450 polymorphisms: clinical pharmacogenetics of clozapine

To examine the genetic factors influencing clozapine kinetics in vivo, 75 patients treated with clozapine were genotyped for CYPs and ABCB1 polymorphisms and phenotyped for CYP1A2 and CYP3A activity. CYP1A2 activity and dose-corrected trough steady-state plasma concentrations of clozapine correlated significantly (r = -0.61; P = 1 x 10), with no influence of the CYP1A2*1F genotype (P = 0.38). CYP2C19 poor metabolizers (*2/*2 genotype) had 2.3-fold higher (P = 0.036) clozapine concentrations than the extensive metabolizers (non-*2/*2). In patients comedicated with fluvoxamine, a strong CYP1A2 inhibitor, clozapine and norclozapine concentrations correlate with CYP3A activity (r = 0.44, P = 0.075; r = 0.63, P = 0.007, respectively). Carriers of the ABCB1 3435TT genotype had a 1.6-fold higher clozapine plasma concentrations than noncarriers (P = 0.046). In conclusion, this study has shown for the first time a significant in vivo role of CYP2C19 and the P-gp transporter in the pharmacokinetics of clozapine. CYP1A2 is the main CYP isoform involved in clozapine metabolism, with CYP2C19 contributing moderately, and CYP3A4 contributing only in patients with reduced CYP1A2 activity. In addition, ABCB1, but not CYP2B6, CYP2C9, CYP2D6, CYP3A5, nor CYP3A7 polymorphisms, influence clozapine pharmacokinetics.

Influence of dose, cigarette smoking, age, sex, and metabolic activity on plasma clozapine concentrations: a predictive model and nomograms to aid clozapine dose adjustment and to assess compliance in individual patients

The measurement of plasma clozapine concentrations is useful in assessing compliance, optimizing therapy, and minimizing toxicity. We measured plasma clozapine and norclozapine (N-desmethylclozapine) concentrations in samples from 3782 patients (2648 male, 1127 female). No clozapine was detected in 291 samples (227 patients, median prescribed dose 300 mg/d). In 4963 (50.2 %) samples (2222 patients); plasma clozapine concentration ranged from 10 to 350 ng/mL.Step-wise backward multiple regression analysis (37 % of the total samples) of log10 plasma clozapine concentration against log10 clozapine dose (mg/d), age (year), sex (male = 0, female = 1), cigarette smoking habit (nonsmokers = 0; smokers = 1), body weight (kg), and plasma clozapine/norclozapine ratio (clozapine metabolic ratio, MR) showed that these covariates explained 48% of the observed variation in plasma clozapine concentration (C = ng/mL x 10-3) (P < 0.001) according to the following equation: log 10 (C) = 0.811 log 10 (dose) + 0.332 (MR) + 69.42 X 10 (-3) (sex) + 2.263 x 10 (-3) (age) + 1.976 x 10(-3) (weight) - 0.171 (smoking habit) - 3.180. This model and its associated confidence intervals were used to develop nomograms of plasma clozapine concentration versus dose for male and female smokers and nonsmokers. Predicted plasma clozapine changes by +48% in nonsmokers, +17% in females, +/-8 % for every 0.1 change in MR (reference 1.32), +/-4% for every 5 years (reference 40 years), and +/-5 % for every 10 kg body weight (reference 80 kg). The nomograms can be used (i) to individualize dosage to achieve a given target plasma clozapine concentration, and (ii) for quantitative evaluation of adherence by estimating the likelihood of an observed concentration being achieved by a given dosage regimen. The model has been validated against published data.