Interindividual variation of plasma haloperidol concentrations and the impact of concomitant medications: the analysis of therapeutic drug monitoring data

Drug-drug interactions between antiseizure medications and antipsychotic medications: a narrative review and expert opinion

INTRODUCTION

Antiseizure medications (ASMs) and antipsychotic drugs are frequently coadministered with the potential for drug-drug interactions. Interactions may either be pharmacokinetic or pharmacodynamic, resulting in a decrease or increase in efficacy and/or an increase or decrease in adverse effects.

AREAS COVERED

The clinical evidence for pharmacokinetic and pharmacodynamic interactions between ASMs and antipsychotics is reviewed based on the results of a literature search in MEDLINE conducted in April 2023.

EXPERT OPINION

There is now extensive published evidence for the clinical importance of interactions between ASMs and antipsychotics. Enzyme-inducing ASMs can decrease blood concentrations of many of the antipsychotics. There is also evidence that enzyme-inhibiting ASMs can increase antipsychotic blood concentrations. Similarly, there is limited evidence showing that antipsychotic drugs may affect the blood concentrations of ASMs through pharmacokinetic interactions. There is less available evidence for pharmacodynamic interactions, but these can also be important, as can displacement from protein binding. The lack of published evidence for an interaction should not be interpreted as meaning that the given interaction does not occur; the evidence is building continually. There is no substitute for careful patient monitoring and sound clinical judgment.

The effects of antiepileptic inducers in neuropsychopharmacology, a neglected issue. Part I: A summary of the current state for clinicians

The literature on inducers in epilepsy and bipolar disorder is seriously contaminated by false negative findings. This is part i of a comprehensive review on antiepileptic drug (AED) inducers using both mechanistic pharmacological and evidence-based medicine to provide practical recommendations to neurologists and psychiatrists concerning how to control for them. Carbamazepine, phenobarbital and phenytoin, are clinically relevant AED inducers; correction factors were calculated for studied induced drugs. These correction factors are rough simplifications for orienting clinicians, since there is great variability in the population regarding inductive effects. As new information is published, the correction factors may need to be modified. Some of the correction factors are so high that the drugs (e.g., bupropion, quetiapine or lurasidone) should not co-prescribed with potent inducers. Clobazam, eslicarbazepine, felbamate, lamotrigine, oxcarbazepine, rufinamide, topiramate, vigabatrin and valproic acid are grouped as mild inducers which may (i)be inducers only in high doses; (ii)frequently combine with inhibitory properties; and (iii)take months to reach maximum effects or de-induction, definitively longer than the potent inducers. Potent inducers, definitively, and mild inducers, possibly, have relevant effects in the endogenous metabolism of (i)sexual hormones, (ii) vitamin D, (iii)thyroid hormones, (iv)lipid metabolism, and (v)folic acid.

Human UDP-glucuronosyltransferase isoforms involved in haloperidol glucuronidation and quantitative estimation of their contribution

A major metabolic pathway of haloperidol is glucuronidation catalyzed by UDP-glucuronosyltransferase (UGT). In this study, we found that two glucuronides were formed by the incubation of haloperidol with human liver microsomes (HLM) and presumed that the major and minor metabolites (>10-fold difference) were O- and N-glucuronide, respectively. The haloperidol N-glucuronidation was catalyzed solely by UGT1A4, whereas the haloperidol O-glucuronidation was catalyzed by UGT1A4, UGT1A9, and UGT2B7. The kinetics of the haloperidol O-glucuronidation in HLM was monophasic with K(m) and V(max) values of 85 μM and 3.2 nmol · min⁻¹ · mg⁻¹, respectively. From the kinetic parameters of the recombinant UGT1A4 (K(m) = 64 μM, V(max) = 0.6 nmol · min⁻¹ · mg⁻¹), UGT1A9 (K(m) = 174 μM, V(max) = 2.3 nmol · min⁻¹ · mg⁻¹), and UGT2B7 (K(m) = 45 μM, V(max) = 1.0 nmol · min⁻¹ · mg⁻¹), we could not estimate which isoform largely contributes to the reaction. Because the haloperidol O-glucuronidation in a panel of 17 HLM was significantly correlated (r = 0.732, p < 0.01) with zidovudine O-glucuronidation, a probe activity of UGT2B7, and the activity in the pooled HLM was prominently inhibited (58% of control) by gemfibrozil, an inhibitor of UGT2B7, we surmised that the reaction would mainly be catalyzed by UGT2B7. We could successfully estimate, using the concept of the relative activity factor, that the contributions of UGT1A4, UGT1A9, and UGT2B7 in HLM were approximately 10, 20, and 70%, respectively. The present study provides new insight into haloperidol glucuronidation, concerning the causes of interindividual differences in the efficacy and adverse reactions or drug-drug interactions.

Interactions between Antiepileptic and Antipsychotic Drugs

Antiepileptic and antipsychotic drugs are often prescribed together. Interactions between the drugs may affect both efficacy and toxicity. This is a review of human clinical data on the interactions between the antiepileptic drugs carbamazepine, valproic acid (sodium valproate), vigabatrin, lamotrigine, gabapentin, topiramate, tiagabine, oxcarbazepine, levetiracetam, pregabalin, felbamate, zonisamide, phenobarbital and phenytoin with the antipsychotic drugs risperidone, olanzapine, quetiapine, clozapine, amisulpride, sulpiride, ziprasidone, aripiprazole, haloperidol and chlorpromazine; the limited information on interactions between antiepileptic drugs and zuclopenthixol, periciazine, fluphenazine, flupenthixol and pimozide is also presented. Many of the interactions depend on the induction or inhibition of the cytochrome P450 isoenzymes, but other important mechanisms involve the uridine diphosphate glucuronosyltransferase isoenzymes and protein binding. There is some evidence for the following effects. Carbamazepine decreases the plasma concentrations of both risperidone and its active metabolite. It also decreases concentrations of olanzapine, clozapine, ziprasidone, haloperidol, zuclopenthixol, flupenthixol and probably chlorpromazine and fluphenazine. Quetiapine increases the ratio of carbamazepine epoxide to carbamazepine and this may lead to toxicity. The data on valproic acid are conflicting; it may either increase or decrease clozapine concentrations, and it appears to decrease aripiprazole concentrations. Chlorpromazine possibly increases valproic acid concentrations. Lamotrigine possibly increases clozapine concentrations. Phenobarbital decreases clozapine, haloperidol and chlorpromazine concentrations. Phenytoin decreases quetiapine, clozapine, haloperidol and possibly chlorpromazine concentrations. There are major gaps in the data. In many cases there are no published clinical data on interactions that would be predicted on theoretical grounds.

Establishment of New Cloned Enzyme Donor Immunoassays (CEDIA??) for Haloperidol and Bromperidol

The authors have developed and verified the precision and accuracy of new automated cloned enzyme donor immunoassays (CEDIA) for haloperidol and bromperidol, and cross-validations have been performed with conventional semiautomated EIA kits (MARKIT-M) and high-performance liquid chromatographic (HPLC) methods. The CEDIA method provides a quick (about 10 minutes) assay for haloperidol or bromperidol, requiring no serum/plasma pretreatment or predilution. The CEDIA haloperidol/bromperidol assay showed little or no cross reactivity with either their metabolites or many drugs commonly coprescribed. MARKIT-M revealed considerable cross reactivity values proportional to the spiked amounts of reduced metabolites. Precision, accuracy, recovery, and linearity testing for the CEDIA assay were all sufficient for clinical use. Significant linear correlations were found between CEDIA and HPLC in measuring haloperidol (CEDIA = 1.06 x HPLC + 0.869; n = 44, rs = 0.913, P < 0.001) and bromperidol (CEDIA = 1.06 x HPLC + 0.606; n = 56, rs = 0.914, P < 0.001) concentrations. This study has, therefore, demonstrated that the CEDIA assay has a quick run time with high precision and accuracy, and this method is a useful tool for the TDM of haloperidol or bromperidol.

Poor reliability of therapeutic drug monitoring data for haloperidol and bromperidol using enzyme immunoassay

Therapeutic drug monitoring (TDM) services for plasma concentrations of haloperidol and bromperidol using enzyme immunoassay (EIA) methods are available in Japan, whereas high-performance liquid chromatographic (HPLC) methods are preferred in other countries. To compare these methods, we took 54 plasma samples for haloperidol and 91 plasma samples for bromperidol from schizophrenic patients receiving haloperidol or bromperidol, and the samples were measured using both commercial EIA and HPLC methods. Significant linear correlations were found between the two methods in determining haloperidol (EIA = 1.351 x HPLC + 1.39; r = 0.934, P < 0.001) and bromperidol (EIA = 1.420 x HPLC + 0.712; r = 0.956, P < 0.001) concentrations, but plasma concentrations using the EIA kits were approximately 92% (95% CI; 53-131%) and 62% (54-70%) higher than those using HPLC for haloperidol and bromperidol, respectively. Mean (and range) plasma concentrations of reduced metabolites were 54% (30-92%) and 55% (29-111%) of those of haloperidol and bromperidol, respectively. The present study suggests that reduced metabolites are included to a considerable degree in TDM data using the EIA kits. Therefore, some limitation of TDM data of haloperidol and bromperidol using the EIA kits, ie, high precision but poor accuracy, should be kept in mind.

Haloperidol plasma concentration in Japanese psychiatric subjects with gene duplication of CYP2D6

AIMS

The cytochrome P-450 2D6 (CYP2D6) gene duplication/multiduplication producing an increase in enzyme activity, and the common Japanese mutation, CYP2D6*10A producing a decrease of enzyme activity were screened in a large number of Japanese psychiatric subjects (n = 111) in order to investigate whether these mutated alleles affected the plasma concentration of haloperidol.

METHODS

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was performed to identify the CYP2D6*10A and CYP2D6*2 genotypes in subjects who had been taking haloperidol. For the screening of duplicated active CYP2D6 gene, allele-specific long PCR was performed. Plasma concentration of haloperidol was measured by the enzyme immunoassay, and expressed as "plasma concentration dose ratio" to normalize individual differences.

RESULTS

The plasma concentration-dose ratio showed large interindividual differences of approximately 18-fold. PCR-RFLP methods revealed that 29 (26.1%), 10 (9.0%), 39 (35.1%), 0 (0%), seven (6.3%) and 26 (23.4%) cases possessed the CYP2D6 genotypes *1/*1, *1/*2, *1/*10A, *2/*2, *2/*10A and *10 A/*10A, respectively. Six cases (5.4%) had duplicated CYP2D6 genes. There were no significant differences of plasma concentration-dose ratio between the groups classified by CYP2D6*10A and *2 genotypes (Kruskal-Wallis test; P = 0.37), even in those cases whose daily doses were lower than 20 mg (n = 90, P = 0.91). Subjects having duplicated genes (n = 6) did not show significant differences of plasma concentration-dose ratio by comparison with subjects who had no duplicated genes (Mann-Whitney U-test; P = 0.80).

CONCLUSIONS

Gene duplication, and the common Japanese mutation CYP2D6*10A on CYP2D6 gene are not likely to be the main modulatory factors of plasma concentration of haloperidol in Japanese psychiatric subjects.

Interindividual variation of serum haloperidol concentrations in Japanese patients--clinical considerations on steady-state serum level-dose ratios

OBJECTIVE

Marked interpatient variability in haloperidol (HAL) level-dose (L/D) ratios makes it difficult to use the administered dose for predicting serum concentrations.

OBJECTIVE

To investigate the effect of dose, age, total body weight and co-medication on steady-state HAL L/D ratios.

METHOD

Retrospective analysis of dose and HAL blood level data from 168 patients.

RESULTS

The HAL L/D ratio decreased curvilinearly with increasing daily dose of HAL. The patients treated with concomitant antiparkinsonian drugs showed a mean HAL L/D ratio that was 24.9% higher than those without antiparkinsonian drugs. The patients treated with concomitant antiepileptic drugs showed a mean HAL L/D ratio that was 27.2% lower than those without antiepileptic drugs. The mean HAL L/D ratio of patients treated with concomitant CYP2D6 substrates was not significantly different from those without CYP2D6 substrates.

CONCLUSION

There is a wide interindividual variability in blood levels of HAL in patients given the same dose. Routine monitoring of HAL serum level is useful, especially in patients who require associated antiepileptic and/or antiparkinsonian medication.

Antiepileptic-antipsychotic drug interactions: a critical review of the evidence

The potential for drug-drug interactions in psychiatry and patients with epilepsy is very high. Moreover, antiepileptic drugs are widely used outside epilepsy as psychotropic agents and their spectrum of activity on behavior is of considerable interest to psychopharmacology. In both neurologic and psychiatric practice, pharmacotherapy combinations are commonly used to treat comorbid psychiatric and neurologic disorders, to reduce or control the adverse effects of a medication or to increase its efficacy. This paper focuses on the metabolic pharmacokinetic interactions between two classes of psychotropic drugs: antiepileptic and antipsychotic drugs. The degree of documentation varies for many interactions from clinical case-report experiences to well established research outcomes. The evidence and the clinical significance of these interactions are reviewed. In general, it is better to use as few drugs as possible, as multicolored politherapies increase the possible adverse effects of drug interactions and reduce patient compliance.

Population pharmacokinetics of haloperidol using routine clinical pharmacokinetic data in Japanese patients

OBJECTIVE

To clarify the observed variability of haloperidol disposition in patients with psychiatric disorders.

DESIGN

Retrospective population pharmacokinetic study.

PARTICIPANTS

218 Japanese patients aged 16 to 82 years who provided 391 serum haloperidol concentrations.

METHODS

Routine clinical pharmacokinetic data gathered from patients receiving haloperidol were analysed to estimate population pharmacokinetic parameters with the nonlinear mixed effects model (NONMEM) computer program.

RESULTS

The final pharmacokinetic model was CL = 42.4 * (TBW/60)(0.655) * 0.814(AGE> or = 55) * (DOSE/200)(0.236) * 1.32(ANTIEP) and Vd = 34.4 * TBW * 0.336( AGE> or = 65), where CL is total body clearance (L/h), Vd is apparent volume of distribution (L), TBW is total bodyweight (kg), DOSE is daily dosage (microg/kg/day), ANTIEP = 1 for concomitant administration of antiepileptic drugs (phenobarbital, phenytoin or carbamazepine) and 0 otherwise, AGE > or = 55 = 1 for patient aged 55 years or over and 0 otherwise, and AGE > or = 65 = 1 for patient aged 65 years or over and 0 otherwise. Concomitant administration of haloperidol and antiepileptic drugs resulted in a 32% increase in haloperidol clearance. Patients aged 55 years or over showed an 18.6% reduction in clearance, and elderly patients aged 65 years or over showed a 66.4% reduction in apparent volume of distribution. Inclusion of terms for the concomitant administration of haloperidol and antiparkinsonian drugs (amantadine, bromocriptine, biperiden, trihexyphenidyl or mazaticol) or cytochrome P450 (CYP) 2D6 substrates (levomepromazine, perphenazine, thioridazine, amitriptyline or clomipramine) did not significantly improve the estimate of haloperidol clearance.

CONCLUSION

Application of the findings in this study to patient care may permit selection of an appropriate initial maintenance dosage to achieve target haloperidol serum concentrations, thus enabling the clinician to achieve the desired therapeutic effect.

Lack of impact of CYP1A2 genetic polymorphism (C/A polymorphism at position 734 in intron 1 and G/A polymorphism at position -2964 in the 5'-flanking region of CYP1A2) on the plasma concentration of haloperidol in smoking male Japanese with schizophrenia

The impact of genetic polymorphism of CYP1A2 that are related to the induction of the isozyme on the plasma levels of haloperidol (HAL) in 40 male smokers with schizophrenia was investigated. A point mutation from C to A in intron 1 at position 734 and a point mutation from G to A at position -2964 in the 5'-flanking region of CYP1A2 were identified by polymerase chain-reaction-restricted fragment length polymorphism method. Regarding C/A polymorphism in intron 1 at position 734, no significant difference was found in the plasma concentrations of HAL corrected for dose and weight among the subjects with A/A (n = 21), A/C (n = 14) and C/C (n = 5) genotypes (one-way analysis of variance: 63.1 +/- 18.5, 47.8 +/- 12.5 and 50.8 +/- 15.1 ng/ml/mg/kg, respectively, F(2,37) = 2.556, P = .09). Regarding G/A polymorphism at position -2964 in the 5'-flanking region, no significant difference was found in the plasma concentrations of HAL corrected for dose and weight between subjects with G/G (n = 24) and G/A (n = 15) (two-tailed t test: G/G and G/A = 51.2 +/- 16.6 and 59.0 +/- 17.6 ng/ml/mg/kg, respectively, df = 28, P = .22). The present study suggests that the genotyping of CYP1A2 cannot predict the steady state plasma levels of HAL in male smoking schizophrenics.

Therapeutic drug monitoring databases for postmarketing surveillance of drug-drug interactions

Drug-drug interactions can be associated with patient morbidity due to either increased toxicity or a potentially ineffective concentration. Because interactions cannot always be anticipated during drug development and actual patients receiving a drug for therapeutic use often differ from those included in clinical trials, postmarketing surveillance is essential. Therapeutic drug monitoring (TDM) databases offer a unique opportunity in this respect. Prerequisites for TDM databases to provide valid information in a pharmacoepidemiological perspective include the following: precise description of exposure to the potentially interacting drugs; measurement of parent compound and active metabolites through accurate and precise analytical techniques; documentation of relevant patient characteristics that may act as confounding factors (e.g. gender, age, smoking habits); repeated assessments over time if possible; and sound pharmacokinetic framework for data selection, analysis and interpretation. The contribution of TDM to the documentation of drug-drug interactions takes advantage of different possible study designs, discussed on the basis of recently published studies. The single case report plays an important role as an alert signal. It is illustrated for a patient on long-term treatment, who displayed an unexpectedly high clozapine concentration after the introduction of ciprofloxacin comedication. The prospective on and off comedication panel study shows advantages in terms of carefully selected inclusion criteria and control of treatment modalities. A study of the thioridazine-fluvoxamine interaction is presented, with patients followed on thioridazine monotherapy, after introduction of fluvoxamine and after its discontinuation. The main advantage of the retrospective large-scale TDM database screen is representativeness of patients actually treated, whereas drawbacks are related to quality of data and suitability for valid interpretation. Such an approach is illustrated by a review of data collected over 10 years of routine TDM that allowed documenting induction of nortriptyline metabolism by carbamazepine and inhibition by several phenothiazines. Finally, population pharmacokinetics is well suited to observational data collected for TDM purpose, provided quality is ascertained. Focus is placed on interindividual variability and relationship between pharmacokinetic parameters and patient characteristics, including comedication. The population approach is discussed with respect to a study that documented a 32% increase of haloperidol clearance associated with anticonvulsant comedication, in addition to effects of age and bodyweight. Among factors to consider for improved effectiveness in the use of TDM databases for postmarketing surveillance of drug-drug interactions, integration of efficacy and safety data in future studies and communication of expert recommendations to prescribing physicians are essential.

Epidemiologic investigation of the relative clearance of haloperidol by mixed-effect modeling using routine clinical pharmacokinetic data in Japanese patients

The steady-state trough concentrations of haloperidol were studied to clarify the role of the characteristics of Japanese patients in estimating haloperidol dosing regimens by using routine therapeutic drug-monitoring data. Nonlinear mixed-effects modeling (NONMEM) was used to estimate the effect of a variety of developmental and demographic factors on haloperidol clearance values using 270 serum level measurements obtained from 191 patients during their clinical course. The final model describing haloperidol's relative clearance was CL = 0.74 x TBW(0.594) x DOSE(0.326) x 1.32CO1 x 0.867AGE, where CL is clearance (measured in liters per hour), TBW is the total body weight (in kilograms), DOSE is the daily dose of haloperidol (in grams per kilogram per day), CO1 = 1 for concomitant administration of antiepileptic drugs (phenobarbital, phenytoin, or carbamazepine) and CO1 = 0 otherwise, and AGE = 1 for patients aged 55 years or older and AGE = 0 otherwise. Concomitant administration of haloperidol and antiepileptic drugs resulted in a 32% increase in haloperidol clearance. Patients aged 55 years or older showed a 13.3% reduction in clearance values compared with the younger population.