Population Pharmacokinetics of Clozapine and Norclozapine and Switchability Assessment between Brands in Uruguayan Patients with Schizophrenia

Semi-physiological Pharmacokinetic Model of Clozapine and Norclozapine in Healthy, Non-smoking Volunteers: The Impact of Race and Genetics

BACKGROUND AND OBJECTIVES: Clozapine is the medication of choice for treatment-resistant schizophrenia. However, it has a complex metabolism and unexplained interindividual variability. The current work aims to develop a pharmacokinetic model of clozapine and norclozapine in non-smokers and assess the impact of demographic and genetic predictors.

METHODS

Healthy volunteers were recruited in a population pharmacokinetic study. Blood samples were collected at 30 min and 1, 2, 3, 5 and 8 h following a single flat dose of clozapine (12.5 mg). The clozapine and norclozapine concentrations were measured via high-performance liquid chromatography-ultraviolet method. A semi-physiological pharmacokinetic model of clozapine and norclozapine was developed using nonlinear mixed-effects modeling. Clinical and genetic predictors were evaluated, including CYP1A2 (rs762551) and ABCB1 (rs2032582), using restriction fragment length polymorphism.

RESULTS

A total of 270 samples were collected from 33 participants. The data were best described using a two-compartment model for clozapine and a two-compartment model for norclozapine with first-order absorption and elimination and pre-systemic metabolism. The estimated (relative standard error) clearance of clozapine and norclozapine were 27 L h-1 (31.5 %) and 19.6 L h-1 (30%), respectively. Clozapine clearance was lower in sub-Saharan Africans (n = 4) and higher in Caucasians (n = 9) than Asians (n = 20). Participants with CYP1A2 (rs762551) (n = 18) and ABCB1 (rs2032582) (n = 12) mutant alleles had lower clozapine clearance in the univariate analysis.

CONCLUSIONS

This is the first study to develop a semi-physiological pharmacokinetic model of clozapine and norclozapine accounting for the pre-systemic metabolism. Asians required lower doses of clozapine as compared with Caucasians, while clozapine pharmacokinetics in sub-Saharan Africans should be further investigated in larger trials.

Exploring low clozapine C/D ratios, inverted clozapine-norclozapine ratios and undetectable concentrations as measures of non-adherence in clozapine patients: A literature review and a case series of 17 patients from 3 studies

BACKGROUND

Up to 1/2 of outpatients prescribed clozapine may be partially/fully non-adherent, based on therapeutic drug monitoring (TDM). Three indices for measuring partial/full non-adherence are proposed a: 1) clozapine concentration/dose (C/D) ratio which drops to half or more of what is expected in the patient; 2) clozapine/norclozapine ratio that becomes inverted; and 3) clozapine concentration that becomes non-detectable.

METHODS

These 3 proposed indices are based on a literature review and 17 cases of possible non-adherence from 3 samples: 1) an inpatient study in a Chinese hospital, 2) an inpatient randomized clinical trial in a United States hospital, and 3) and a Uruguayan outpatient study.

RESULTS

The first index of non-adherence is a clozapine C/D ratio which is less than half the ratio corresponding to the patient's specific ancestry group and sex-smoking subgroup. Knowing the minimum therapeutic dose of the patient based on repeated TDM makes it much easier to establish non-adherence. The second index is inverted clozapine/norclozapine ratios in the absence of alternative explanations. The third index is undetectable concentrations. By using half-lives, the chronology of the 3 indices of non-adherence was modeled in two patients: 1) the clozapine C/D ratio dropped to ≥1/2 of what is expected from the patient (around day 2); 2) the clozapine/norclozapine ratio became inverted (around day 3); and 3) the clozapine concentration became undetectable by the laboratory (around days 9-11).

CONCLUSION

Prospective studies should further explore these proposed clozapine indices in average patients, poor metabolizers (3 presented) and ultrarapid metabolizers (2 presented).

Exploring clozapine pharmacokinetics in Tunisian schizophrenic patients: A population-based modelling approach investigating the impact of genetic and non-genetic variables

Clozapine is characterized by a large within- and between-patient variability in its pharmacokinetics, attributed to non-genetic and genetic factors. A cross-sectional analysis of clozapine trough concentration (Clz C0) issued from Tunisian schizophrenic patients was collected and analysed using a nonparametric modelling approach. We assessed the impact of demographic covariates (age, weight and sex), patient's habits (smoking status, alcohol and caffeine intake) and the genetic factors (CYP1A2*1C, CYP1A2*1F and CYP2C19*2 polymorphisms) on each pharmacokinetic parameter. An external validation of this pharmacokinetic model using an independent data set was performed. Fit goodness between observed- and individual-predicted data was evaluated using the mean prediction error (% MPE), the mean absolute prediction error (% MAPE) as a measure of bias, and the root mean squared error (% RMSE) as a measure of precision. Sixty-three CLz C0 values issued from 51 schizophrenic patients were assessed in this study and divided into building and validation groups. CYP1A2*1F polymorphism and smoking status were the only covariates significantly associated with clozapine clearance. Precision parameters were as follows: 1.02%, 0.95% and 22.4%, respectively, for % MPE, % MAPE and % RMSE. We developed and validated an accurate pharmacokinetic model able to predict Clz C0 in Tunisian schizophrenic patients using the two parameters CYP1A2*1F polymorphism and smoking.

Chromatographic Methods for the Analysis of the Antipsychotic Drug Clozapine and Its Major Metabolites: A Review

Clozapine (CLZ), a second-generation antipsychotic, can effectively reduce schizophrenia, bipolar disorder and major depression symptoms. This review provides an overview of all reported chromatographic methods (62 references) for the quantification of CLZ and its two main metabolites, norclozapine and clozapine N-oxide in pharmaceutical formulations, biological matrices and environmental samples.

Validation of Population Pharmacokinetic Models for Clozapine Dosage Prediction

BACKGROUND

Clozapine is unique in its capacity to ameliorate severe schizophrenia but at high risk of toxicity. A relationship between blood concentration and clinical response and evidence for concentration-response relationships to some adverse effects justify therapeutic drug monitoring of clozapine. However, the relationship between drug dose and blood concentration is quite variable. This variability is, in part, due to inductive and inhibitory interactions varying the activity of cytochrome P450 1A2 (CYP1A2), the principal pathway for clozapine elimination. Several population pharmacokinetic models have been presented to facilitate dose selection and to identify poor adherence in individual patients. These models have faced little testing for validity in independent populations or even for persisting validity in the source population.

METHODS

Therefore, we collected a large population of clozapine-treated patients (127 patients, 1048 timed plasma concentrations) in whom dosing and covariate information could be obtained with high certainty. A population pharmacokinetic model was constructed with data collected in the first 6 weeks from study enrolment (448 plasma concentrations), to estimate covariate influences and to allow alignment with previously published models. The model was tested for its performance in predicting the concentrations observed at later time intervals up to 5 years. The predictive performances of 6 published clozapine population models were then assessed in the entire population.

RESULTS

The population pharmacokinetic model based on the first 6 weeks identified significant influences of sex, smoking, and cotreatment with fluvoxamine on clozapine clearance. The model built from the first 6 weeks had acceptable predictive performance in the same patient population up to the first 26 weeks using individual parameters, with a median predictive error (PE) of -0.1% to -15.9% and median absolute PE of 22.9%-27.1%. Predictive performance fell progressively with time after 26 weeks. Bayesian addition of plasma concentration observations within each prediction period improved individual predictions. Three additional observations extended acceptable predictive performance into the second 6 months of therapy. When the published models were tested with the entire data set, median PE ranged from -8% to +35% with a median absolute PE of >39% in all models. Thus, none of the tested models was successful in external validation. Bayesian addition of single patient observations improved individual predictions from all models but still without achieving acceptable performances.

CONCLUSIONS

We conclude that the relationship between covariates and blood clozapine concentrations differs between populations and that relationships are not stable over time within a population. Current population models for clozapine are not capturing influential covariates.

A population pharmacokinetic model to guide clozapine dose selection, based on age, sex, ethnicity, body weight and smoking status

AIMS

Guidance on clozapine dosing in treatment-resistant schizophrenia is based largely on data from White young adult males. This study aimed to investigate the pharmacokinetic profiles of clozapine and N-desmethylclozapine (norclozapine) across the age range, accounting for sex, ethnicity, smoking status and body weight.

METHODS

A population pharmacokinetic model, implemented in Monolix, that linked plasma clozapine and norclozapine via a metabolic rate constant, was used to analyse data from a clozapine therapeutic drug monitoring service, 1993-2017.

RESULTS

There were 17 787 measurements from 5960 patients (4315 male) aged 18-86 years. The estimated clozapine plasma clearance was reduced from 20.2 to 12.0 L h-1 between 20 and 80 years. Model-based dose predictions to attain a predose plasma clozapine concentration of 0.35 mg L-1 was 275 (90% prediction interval 125, 625) mg day-1 in nonsmoking, White males weighing 70 kg and aged 40 years. The corresponding predicted dose was increased by 30% in smokers, decreased by 18% in females, and was 10% higher and 14% lower in otherwise analogous Afro-Caribbean and Asian patients, respectively. Overall, the predicted dose decreased by 56% between 20 and 80 years.

CONCLUSION

The large sample size and wide age range of the patients studied allowed precise estimation of dose requirements to attain predose clozapine concentration of 0.35 mg L-1 . The analysis was, however, limited by the absence of data on clinical outcome and future studies are required to determine optimal predose concentrations specifically in those aged over 65 years.

Association of clozapine and norclozapine levels with patient and therapy characteristics-focus on interaction with valproic acid

PURPOSE

The goal of the study was to examine clozapine (CLZ) and norclozapine (NCLZ) therapeutic drug monitoring (TDM) data and associated sources of pharmacokinetic variability, particularly the impact of valproic acid (VPA) use.

METHODS

This study included 126 patients with psychiatric disorders on mono- or co-therapy with CLZ. Patients' data during routine TDM were collected retrospectively from clinical records. The descriptive and statistical analysis was computed using IBM SPSS Statistics software (version 22, NY, USA). Multiple linear regression, based on the last observations, was used to assess correlation between demographic characteristics, life habits and co-therapy with dose-corrected serum levels (C/D) of CLZ and NCLZ, as well as CLZ/NCLZ.

RESULTS

A total of 295 CLZ concentrations were measured in 126 patients, with a mean of 275.5 ± 174.4 µg/L, while 124 NCLZ concentrations were determined in 74 patients, with a mean of 194.6 ± 149.8 µg/L. A statistically significant effect on ln-transformed CLZ C/D was confirmed for sex and smoking, whereas sex, smoking and VPA therapy were associated with ln-transformed NCLZ C/D. According to the final models, lower values of NCLZ C/D for about 45.9% can be expected in patients receiving VPA. Concomitant use of VPA was the only factor detected to contribute in CLZ/NCLZ variability.

CONCLUSION

The results of this study may help clinicians interpret TDM data and optimize CLZ dosing regimens, especially in patients concomitantly treated with VPA. Our results show that VPA primarily decreases NCLZ levels, while alteration of the parent drug is not statistically significant.

Receptors Involved in Mental Disorders and the Use of Clozapine, Chlorpromazine, Olanzapine, and Aripiprazole to Treat Mental Disorders

Mental illnesses are a global health challenge, and effective medicines are needed to treat these conditions. Psychotropic drugs are commonly prescribed to manage mental disorders, such as schizophrenia, but unfortunately, they can cause significant and undesirable side effects, such as myocarditis, erectile dysfunction, and obesity. Furthermore, some schizophrenic patients may not respond to psychotropic drugs, a condition called schizophrenia-treatment resistance. Fortunately, clozapine is a promising option for patients who exhibit treatment resistance. Unlike chlorpromazine, scientists have found that clozapine has fewer neurological side effects. Additionally, olanzapine and aripiprazole are well-known for their moderating effects on psychosis and are widely used in clinical practice. To further maximize drug efficacy, it is critical to deeply understand the receptors or signaling pathways central to the nervous system, such as serotonin, histamine, trace amines, dopamine, and G-protein coupled receptors. This article provides an overview of the receptors mentioned above, as well as the antipsychotics that interact with them, such as olanzapine, aripiprazole, clozapine, and chlorpromazine. Additionally, this article discusses the general pharmacology of these medications.

Current Status of Therapeutic Drug Monitoring in Mental Health Treatment: A Review

Therapeutic drug monitoring (TDM) receives growing interest in different psychiatric clinical settings (emergency, inpatient, and outpatient services). Despite its usefulness, TDM remains underemployed in mental health. This is partly due to the need for evidence about the relationship between drug serum concentration and efficacy and tolerability, both in the general population and even more in subpopulations with atypical pharmacokinetics. This work aims at reviewing the scientific literature published after 2017, when the most recent guidelines about the use of TDM in mental health were written. We found 164 pertinent records that we included in the review. Some promising studies highlighted the possibility of correlating early drug serum concentration and clinical efficacy and safety, especially for antipsychotics, potentially enabling clinicians to make decisions on early laboratory findings and not proceeding by trial and error. About populations with pharmacokinetic peculiarities, the latest studies confirmed very common alterations in drug blood levels in pregnant women, generally with a progressive decrease over pregnancy and a very relevant dose-adjusted concentration increase in the elderly. For adolescents also, several drugs result in having different dose-related concentration values compared to adults. These findings stress the recommendation to use TDM in these populations to ensure a safe and effective treatment. Moreover, the integration of TDM with pharmacogenetic analyses may allow clinicians to adopt precise treatments, addressing therapy on an individual pharmacometabolic basis. Mini-invasive TDM procedures that may be easily performed at home or in a point-of-care are very promising and may represent a turning point toward an extensive real-world TDM application. Although the highlighted recent evidence, research efforts have to be carried on: further studies, especially prospective and fixed-dose, are needed to replicate present findings and provide clearer knowledge on relationships between dose, serum concentration, and efficacy/safety.

Towards Precision Dosing of Clozapine in Schizophrenia: External Evaluation of Population Pharmacokinetic Models and Bayesian Forecasting

BACKGROUND

Therapeutic drug monitoring and treatment optimization of clozapine are recommended, owing to its narrow therapeutic range and pharmacokinetic (PK) variability. This study aims to assess the clinical applicability of published population PK models by testing their predictive performance in an external data set and to determine the effectiveness of Bayesian forecasting (BF) for clozapine treatment optimization.

METHODS

Available models of clozapine were identified, and their predictive performance was determined using an external data set (53 patients, 151 samples). The median prediction error (PE) and median absolute PE were used to assess bias and inaccuracy. The potential factors influencing model predictability were also investigated. The final concentration was reestimated for all patients using covariates or previously observed concentrations.

RESULTS

The 7 included models presented limited predictive performance. Only 1 model met the acceptability criteria (median PE ≤ ±20% and median absolute PE ≤30%). There was no difference between the data used for building the models (therapeutic drug monitoring or PK study) or the number of compartments in the models. A tendency for higher inaccuracy at low concentrations during treatment initiation was observed. Heterogeneities were observed in the predictive performances between the subpopulations, especially in terms of smoking status and sex. For the models included, BF significantly improved their predictive performance.

CONCLUSIONS

Our study showed that upon external evaluation, clozapine models provide limited predictive performance, especially in subpopulations such as nonsmokers. From the perspective of model-informed prediction dosing, model predictability should be improved using updating or metamodeling methods. Moreover, BF substantially improved model predictability and could be used for clozapine treatment optimization.

Body mass index as a determinant of clozapine plasma concentrations: A pharmacokinetic-based hypothesis

BACKGROUND

Knowledge regarding the impact of body composition measures on pharmacokinetics of antipsychotics is limited.

AIMS

Our aim was to investigate the impact of body weight and body mass index on clozapine pharmacokinetics using a therapeutic drug monitoring database.

METHODS

A large therapeutic drug monitoring dataset of clozapine plasma concentrations considering three patient subgroups was analysed: a control group (CLZ₀, 20-30 kg/m², n=266), a group with high body mass index (CLZ_high, body mass index ⩾30 kg/m², n=162) and with low body mass index values (CLZ_low, body mass index <20 kg/m², n=27). Comparisons of plasma and dose-adjusted plasma concentrations (C/D) of clozapine were based on the Spearman's correlation (rs), Kruskal Wallis and Mann-Whitney-U tests. For percentages we used the Pearson chi-square test (χ²). To assess effects of confounders we used bootstrapping analysis of covariates.

RESULTS/OUTCOMES

Regarding demographic characteristics, groups differed only for sex percentage with more females than males in CLZ_low and CLZ_high compared to CLZ₀ (p=0.001 for χ² test). Plasma and C/D values were positively associated with body mass index (rs=0.108, p=0.022 and rs=0.156, p=0.001 respectively). Intergroup differences were observed for plasma and dose-adjusted concentrations of clozapine (p=0.031 and p=0.029 for Kruskal Wallis respectively): post-hoc pairwise comparisons showed higher plasma concentrations and C/D of clozapine in CLZ_high compared to CLZ₀ (p=0.014 and p=0.007 respectively for Mann-Whitney U-test), by mean 21 and 18%, respectively. Differences for C/D values remained after accounting for sex (p=0.02).

CONCLUSIONS/INTERPRETATION

In obese patients, bioavailability, distribution or elimination of clozapine may be altered due to increased clozapine deposits in fat tissue and hepatic enzyme activity changes.

MRGPRX2 is critical for clozapine induced pseudo-allergic reactions

BACKGROUND

Clozapine is one of the most widely used second-generation antipsychotics in clinic. However, allergy-like symptoms such as rash and angioedema have been reported frequently, and the mechanism is still not clear. Mas-related G protein-coupled receptor X2 (MRGPRX2) expressed on mast cells is a crucial receptor for drug induced pseudo-allergic reactions. Therefore, we explored whether the symptoms induced by clozapine were associated with allergic reaction through MRGPRX2.

METHODS

The effects of clozapine on pseudo-allergic reactions were evaluated by mast cells degranulation and calcium mobilization assay in vitro, and mice hindpaw swelling, serum histamine detection, avidin and H&E staining assay in vivo. The overexpressed MRGPRX2 cells membrane chromatography (MRGPRX2-HEK293/CMC), MRGPRX2-HEK293 cells calcium mobilization assay and molecular docking were applied to research the correlation between clozapine and MRGPRX2.

RESULTS

The study showed that clozapine induced the release of β-hexosaminidase, histamine and monocyte chemoattractant protein-1 (MCP-1), and trigged calcium mobilization in mast cells. In vivo, clozapine induced paw swelling, degranulation and vasodilation. Furthermore, clozapine could activate the calcium mobilization obviously in MRGPRX2-HEK293 cells, not in NC-HEK293 cells. Clozapine also had a good retention characteristic on MRGPRX2-HEK293/CMC column and the K _D value is (2.33 ± 0.21)×10^-01M.

CONCLUSIONS

Our findings demonstrated that clozapine could induce pseudo-allergic reactions and MRGPRX2 might be the critical receptor for it.

Impact of smoking behavior on clozapine blood levels - a systematic review and meta-analysis

OBJECTIVE

Tobacco smoking significantly impacts clozapine blood levels and has substantial implications on individual efficacy and safety outcomes. By investigating differences in clozapine blood levels in smoking and non-smoking patients on clozapine, we aim to provide guidance for clinicians how to adjust clozapine levels for patients on clozapine who change their smoking habits.

METHODS

We conducted a meta-analysis on clozapine blood levels, norclozapine levels, norclozapine/clozapine ratios, and concentration to dose (C/D) ratios in smokers and non-smokers on clozapine. Data were meta-analyzed using a random-effects model with sensitivity analyses on dose, ethnic origin, and study quality.

RESULTS

Data from 23 studies were included in this meta-analysis with 21 investigating differences between clozapine blood levels of smokers and non-smokers. In total, data from 7125 samples were included for the primary outcome (clozapine blood levels in ng/ml) in this meta-analysis. A meta-analysis of all between-subject studies (N = 16) found that clozapine blood levels were significantly lower in smokers compared with non-smokers (Standard Mean Difference (SMD) -0.39, 95% confidence interval (CI) -0.55 to -0.22, P < 0.001, I²  = 80%). With regard to the secondary outcome, C/D ratios (N = 16 studies) were significantly lower in the smoker group (n = 645) compared with the non-smoker group (n = 813; SMD -0.70, 95%CI -0.84 to -0.56, P < 0.00001, I²  = 17%).

CONCLUSION

Smoking behavior and any change in smoking behavior is associated with a substantial effect on clozapine blood levels. Reductions of clozapine dose of 30% are recommended when a patient on clozapine stops smoking. Reductions should be informed by clozapine steady-state trough levels and a close clinical risk-benefit evaluation.

The role of sulpiride in attenuating the cardiac, renal, and immune disruptions in rats receiving clozapine: mRNA expression pattern of the genes encoding Kim-1, TIMP-1, and CYP isoforms

The present study was aimed to explore the cardio-, immuno-, and nephrotoxic effects of the antipsychotic agent clozapine (CLZ) and the alleviative potency of sulpiride (SPD) on these impairments in rats. For this purpose, 40 male rats were divided into four groups and were orally treated with saline (control), CLZ (0.5 mg/kg bw), SPD (28 mg/kg bw), or a combination of CLZ and SPD (CLZ+SPD), daily for 30 consecutive days. At necropsy, blood samples and specimens from the heart, kidneys, and spleen were collected for biochemical, molecular, and histopathological investigations. The results showed that CLZ administration was associated with significantly lower immune status indices and increased serum levels of pro-inflammatory cytokines, lactate dehydrogenase, malondialdehyde, cardiac, and renal tissues injury markers. Moreover, the mRNA expression levels of Kidney Injury Molecule-1 (Kim-1), tissue inhibitor of metalloproteinase-1 (TIMP-1), and cytochrome P450 (CYP) isoforms were markedly upregulated in CLZ-treated rats, compared to the control group. On the other hand, rats treated with SPD alone showed non-significant differences in terms of immune response indices, tissue injury markers, and mRNA expression levels of Kim-1, TIMP-1, and CYP isoforms. Finally, CLZ+SPD co-treatment significantly modulated almost all biochemical indices. Besides, Kim-1, TIMP-1, and CYP2C19 mRNA expression levels were significantly downregulated, while other CYP isoforms showed no modulation, compared with CLZ-treated group. Histopathologically, CLZ-treated rats showed severe lesions in renal, splenic, and cardiac tissues, compared with control rats, which were restored in CLZ+SPD-co-treated rats. Overall, these findings demonstrate that CLZ treatment induces significant cardiac, immune, and nephropathic alterations, which were reduced with CLZ+SPD co-treatment.

Sexual Dimorphism in Drug Metabolism and Pharmacokinetics

Background:

Sex and gender-based differences are observed well beyond the sex organs and affect several physiological and biochemical processes involved in the metabolism of drug molecules. It is essential to understand not only the sex and gender-based differences in the metabolism of the drug but also the molecular mechanisms involved in the regulation of drug metabolism for avoiding sex-related adverse effects of drugs in the human.

Method:

The articles on the sex and gender-based differences in the metabolism of drug molecules were retrieved from the Pub Med database. The articles were classified into the metabolism of the drug molecule, gene expression regulation of drug-metabolizing enzymes, the effect of sex hormones on the metabolism of drug, expression of drugmetabolizing enzymes, etc.

Result:

Several drug molecules are known, which are metabolized differently in males and females. These differences in metabolism may be due to the genomic and non-genomic action of sex hormones. Several other drug molecules still require further evaluation at the molecular level regarding the sex and gender-based differences in their metabolism. Attention is also required at the effect of signaling cascades associated with the metabolism of drug molecules.

Conclusion:

Sex and gender-based differences in the metabolism of drugs exist at various levels and it may be due to the genomic and non-genomic action of sex hormones. Detailed understanding of the effect of sex and related condition on the metabolism of drug molecules will help clinicians to determine the effective therapeutic doses of drugs dependingon the condition of patient and disease.

The relationship between serum clozapine concentrations and hematological parameters by a validated mass spectrometric method

OBJECTIVE

Clozapine is one of the most effective drugs for resistant schizophrenia, but its severe metabolic and hematological side effects limit the use of clozapine. It has been reported that clozapine blood concentrations should be maintained between 350-600 ng/mL. Our aim was to develop a determination method for clozapine and its main metabolites norclozapine and clozapine-N-oxide, to perform validation studies and to investigate the change of various biochemical parameters in patients using clozapine.

METHODS

A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for clozapine measurement. Thus, blood samples were collected from 38 patients with schizophrenia and 32 healthy volunteers. Biochemical and hematological parameters were measured by Beckman-Coulter AU 5800 (Beckman Coulter, Brea, USA) and Beckman Coulter LH 780 analyzer (Beckman Coulter, Miami, FL, USA), respectively. Hormone levels were analyzed using Cobas 6000 analyzer (Roche Diagnostics, Germany).

RESULTS

The LCMS/MS method was linear between 1.22-2500 ng/mL (r² = 0.9971) for clozapine. The retention times of clozapine, norclozapine and clozapine-N-oxide were 0.92, 0.89 and 0.95, respectively. Blood glucose (GLU) (p = 0.025), low density lipoprotein (LDL-cholesterol) (p = 0.015), triglyseride (TG) (p = 0.042) and total cholesterol (TC) (p = 0.024) levels were higher; hemoglobin (HGB) (0.015), mean corpuscular hemoglobin (MCH) (0.036), red blood cell count (RBC) (0.020), neutrophil (NEU) (0.034), and platelet (PLT) (P = 0.005) levels were lower in the clozapine group.

CONCLUSIONS

This LC-MS/MS method was rapid, simple, cost-effective and suitable for the routine clozapine monitoring. Furthermore, norclozapine and clozapine-N-oxide were also determined. Monitoring of metabolic and hematological parameters with clozapine levels is very important. However, the limitations of the study were that the method was not validated for norclozapine and clozapine-N-oxide, so the validation parameters were not evaluated for these two metabolites.

Understanding variability in the pharmacokinetics of atypical antipsychotics - focus on clozapine, olanzapine and aripiprazole population models

Antipsychotic medicines are widely used for the management of psychotic symptoms regardless of the underlying diagnosis. Most atypical antipsychotics undergo extensive metabolism prior to excretion. Various factors may influence their pharmacokinetics, particularly elimination, leading to highly variable drug concentrations between individual patients following the same dosing regimen. Population pharmacokinetic approach, based on nonlinear mixed effects modeling, is a useful tool to identify covariates explaining pharmacokinetic variability, as well as to characterize and distinguish unexplained residual and between-subject (interindividual) variability. In addition, this approach allows the use of both sparsely and intensively sampled data. In this paper, we reviewed the pharmacokinetic characteristics of clozapine, olanzapine and aripiprazole, focusing on a population modeling approach. In particular, models based on a nonlinear mixed effects approach performed by NONMEM^® software in order to identify and quantify sources of pharmacokinetic variability are presented. Population models were identified through systematic searches of PubMed and sixteen studies were selected. Some of the factors identified that significantly contribute to variability in elimination among clozapine, olanzapine, and aripiprazole are demographic characteristics, body weight, genetic polymorphism, smoking and in some cases drug interactions. Scientific research based on pharmacometric modeling is useful to further characterize sources of variability and their combined effect.

ABCB1 and DRD3 polymorphism as a response predicting biomarker and tool for pharmacogenetically guided clozapine dosing in Asian Indian treatment resistant schizophrenia patients

PURPOSE

To investigate association of two single nucleotide polymorphisms (SNPs) ABCB1(rs1045462) and DRD3(rs6280) with clozapine response and the dose in treatment resistant schizophrenia (TRS) patients.

METHODS

200 TRS patients were enrolled in the study during their follow up visit post clozapine initiation. SNP assessment was performed for DRD3 (rs6280) and ABCB1(rs1045462) by sequencing. Blood sample for genotyping was collected with disease and treatment related variables recording on case record form. Patients were classified as responders or nonresponders based upon Andreasen criteria and Positive and Negative Syndrome Scale (PANSS).

RESULTS

Mean clozapine dose, the genotype frequency distribution of ABCB1, DRD3 SNPs were significantly different in clozapine responder and non-responder study population (p < 0.05). CT genotype of ABCB1 and AG genotype of DRD3 were observed to be more prevalent in the responder group. TT genotype of ABCB1 and AG genotype of DRD3 were prevalent in the nonresponder group. Clozapine dosing equations for responder and nonresponder TRS populations were developed through logistic regression analysis. 27% variability in clozapine dose was explained by possible combinations of ABCB1 and DRD3 SNP analysis.

CONCLUSION

Differential ABCB1(rs1045462) and DRD3(rs6280) genotype frequencies among the clozapine responders and non-responders explained clear feasibility of response predictor potential along with clozapine dose variability association. Pharmacogenetically guided clozapine dosing is possible if more SNPs are considered together with ABCB1(rs1045462) and DRD3(rs6280) in TRS patients.

Population Pharmacokinetics of Clozapine: A Systematic Review

Background and Objective

Clozapine is a second-generation antipsychotic drug that is considered the most effective treatment for refractory schizophrenia. Several clozapine population pharmacokinetic models have been introduced in the last decades. Thus, a systematic review was performed (i) to compare published pharmacokinetics models and (ii) to summarize and explore identified covariates influencing the clozapine pharmacokinetics models.

Methods

A search of publications for population pharmacokinetic analyses of clozapine either in healthy volunteers or patients from inception to April 2019 was conducted in PubMed and SCOPUS databases. Reviews, methodology articles, in vitro and animal studies, and noncompartmental analysis were excluded.

Results

Twelve studies were included in this review. Clozapine pharmacokinetics was described as one-compartment with first-order absorption and elimination in most of the studies. Significant interindividual variations of clozapine pharmacokinetic parameters were found in most of the included studies. Age, sex, smoking status, and cytochrome P450 1A2 were found to be the most common identified covariates affecting these parameters. External validation was only performed in one study to determine the predictive performance of the models.

Conclusions

Large pharmacokinetic variability remains despite the inclusion of several covariates. This can be improved by including other potential factors such as genetic polymorphisms, metabolic factors, and significant drug-drug interactions in a well-designed population pharmacokinetic model in the future, taking into account the incorporation of larger sample size and more stringent sampling strategy. External validation should also be performed to the previously published models to compare their predictive performances.