Combining Therapeutic Drug Monitoring and Pharmacokinetic Modelling Deconvolutes Physiological and Environmental Sources of Variability in Clozapine Exposure

Overcoming the barriers to identifying and managing treatment-resistant schizophrenia and to improving access to clozapine: A narrative review and recommendation for clinical practice

Clozapine is the only approved antipsychotic for treatment-resistant schizophrenia (TRS). Although a large body of evidence supports its efficacy and favorable risk-benefit ratio in individuals who have failed two or more antipsychotics, clozapine remains underused. However, variations in clozapine utilization across geographic and clinical settings suggest that it could be possible to improve its use. In this narrative review and expert opinion, we summarized information available in the literature on the mechanisms of action, effectiveness, and potential adverse events of clozapine. We identified barriers leading to discouragement in clozapine prescription internationally, and we proposed practical solutions to overcome each barrier. One of the main obstacles identified to the use of clozapine is the lack of appropriate training for physicians: we highlighted the need to develop specific professional programs to train clinicians, both practicing and in residency, on the relevance and efficacy of clozapine in TRS treatment, initiation, maintenance, and management of potential adverse events. This approach would facilitate physicians to identify eligible patients and offer clozapine as a treatment option in the early stage of the disease. We also noted that increasing awareness of the benefits of clozapine among healthcare professionals, people with TRS, and their caregivers can help promote the use of clozapine. Educational material, such as leaflets or videos, could be developed and distributed to achieve this goal. The information provided in this article may be useful to improve disease burden and support healthcare professionals, patients, and caregivers navigating the complex pathways to TRS management.

Magnetic solid-phase extraction-based surface-enhanced Raman spectroscopy for label-free therapeutic drug monitoring of carbamazepine and clozapine in human serum

Determination of antiepileptic drugs and antipsychotics in human serum is significant in individualized drug administration and therapeutic drug monitoring (TDM). In this study, we developed a rapid label-free TDM method for the antiepileptic drug carbamazepine (CBZ) and the antipsychotic clozapine (CLO) in human serum. This detection strategy is based on the combination of surface-enhanced Raman scattering (SERS) and magnetic solid-phase extraction (MSPE). Initially, Fe3O4@SiO2@MIL-101(Fe) nanocomposites were synthesized by the layer-by-layer self-assembly method and characterized using scanning electron microscopy, transmission electron microscopy, X-ray diffraction, Brunauer-Emmett-Teller, ultraviolet-visible, and Fourier transform infrared analyses. Subsequently, CBZ and CLO were detected in human serum using Fe3O4@SiO2@MIL-101(Fe) as the solid-phase extraction adsorbent and Ag nanoparticles as SERS substrates. The potential of the MSPE-SERS method for the label-free TDM of CBZ and CLO was then investigated. Fe3O4@SiO2@MIL-101(Fe) prevents magnetic particle aggregation and demonstrates rapid magnetic separation capability that simplifies the pretreatment process and reduces interference from complex matrices. Its large surface area can effectively enrich targets in complex matrices, thereby improving the SERS detection sensitivity. The linearity between CBZ and CLO was excellent over the concentration range of 0.1-100 µg/mL (calculated as the intensity of the SERS characteristic peaks of CBZ and CLO at 728 cm and 1054 cm-1, respectively), with correlation coefficients (R2) of 0.9987 and 0.9957, and detection limits of 0.072 and 0.12 µg/mL, respectively. The recoveries of CBZ with CLO ranged from 94.0 % to 105.0 %, and their relative standard deviations were <6.8 %. Compared to other assays, the developed MSPE-SERS method has the advantages of simple sample pretreatment, rapid detection, and good reproducibility, which provides a novel approach for the TDM of other drugs.

A retrospective study of clozapine and norclozapine concentration in patients with schizophrenia: Data from the Therapeutic Drug Monitoring Service, 2019-2022

OBJECTIVE

The aim of this research was to assess the therapeutic drug monitoring (TDM) of clozapine (CLO) and norclozapine (NCLO).

METHODS

TDM results of CLO and NCLO in patients obtained from the Xi'an Mental Health Center were retrospectively analyzed.

RESULTS

TDM of CLO and NCLO was typically conducted only once in the majority of patients, particularly those receiving outpatient care. The CLO plasma concentrations were higher in inpatients and female patients. The interquartile (25th-75th) CLO concentrations ranged from 129.83 to 397.53 ng/mL, nearly 68.63% of the samples had subtherapeutic concentrations (<350 ng/mL). Receiver operating characteristic curve analysis showed that inpatients achieved the therapeutic level concentration of 350-600 ng/mL when their daily CLO dose was > 125 mg.

CONCLUSIONS

It was surprising to find such a large number of patients with CLO levels below the therapeutic range, there is still a window of improvement for optimizing pharmacological treatments in clinical practice.

Hematological and Other Cancers in People Using Clozapine: Analysis of Australian Spontaneous Reports Between 1995 and 2020

BACKGROUND

Recent observational study evidence suggests that clozapine, unlike other antipsychotics, may be associated with a small increased risk of hematological malignancy. This study described characteristics of hematological and other cancers in those taking clozapine reported to the Australian Therapeutic Goods Administration.

METHODS

We analyzed public case reports for "clozapine," "Clozaril," or "Clopine" from January 1995 to December 2020 classified as "neoplasm benign, malignant and unspecified" by the Australian Therapeutic Goods Administration. Data on age, sex, dose, clozapine start and cessation dates, Medical Dictionary for Regulatory Activities reaction terms, and date of cancer were extracted.

RESULTS

Overall, 384 spontaneous reports of cancers in people taking clozapine were analyzed. The mean age of patients was 53.9 years (SD, 11.4 years), and 224 (58.3%) were male. The most frequent cancers were hematological (n = 104 [27.1%]), lung (n = 50 [13.0%]), breast (n = 37 [9.6%]), and colorectal (n = 28 [7.3%]). The outcome was fatal for 33.9% of cancer reports. Lymphoma comprised 72.1% of all hematological cancers (mean patient age, 52.1 years; SD, 11.6 years). The median daily dose of clozapine at the time of hematological cancer report was 400 mg (interquartile range, 300-543.8 mg), and the median duration of clozapine use before hematological cancer diagnosis was 7.0 years (interquartile range, 2.8-13.2 years).

CONCLUSIONS

Lymphoma and other hematological cancers are overrepresented in spontaneous adverse event reports compared with other cancer types. Clinicians should be aware of the possible association with hematological cancers and monitor for and report any hematological cancers identified. Future studies should examine histology of lymphomas in people using clozapine and corresponding blood level of clozapine.

A Physiologically Based Pharmacokinetic Model to Predict Determinants of Variability in Epirubicin Exposure and Tissue Distribution

BACKGROUND

Epirubicin is an anthracycline antineoplastic drug that is primarily used in combination therapies for the treatment of breast, gastric, lung and ovarian cancers and lymphomas. Epirubicin is administered intravenously (IV) over 3 to 5 min once every 21 days with dosing based on body surface area (BSA; mg/m²). Despite accounting for BSA, marked inter-subject variability in circulating epirubicin plasma concentration has been reported.

METHODS

In vitro experiments were conducted to determine the kinetics of epirubicin glucuronidation by human liver microsomes in the presence and absence of validated UGT2B7 inhibitors. A full physiologically based pharmacokinetic model was built and validated using Simcyp^® (version 19.1, Certara, Princeton, NJ, USA). The model was used to simulate epirubicin exposure in 2000 Sim-Cancer subjects over 158 h following a single intravenous dose of epirubicin. A multivariable linear regression model was built using simulated demographic and enzyme abundance data to determine the key drivers of variability in systemic epirubicin exposure.

RESULTS

Multivariable linear regression modelling demonstrated that variability in simulated systemic epirubicin exposure following intravenous injection was primarily driven by differences in hepatic and renal UGT2B7 expression, plasma albumin concentration, age, BSA, GFR, haematocrit and sex. By accounting for these factors, it was possible to explain 87% of the variability in epirubicin in a simulated cohort of 2000 oncology patients.

CONCLUSIONS

The present study describes the development and evaluation of a full-body PBPK model to assess systemic and individual organ exposure to epirubicin. Variability in epirubicin exposure was primarily driven by hepatic and renal UGT2B7 expression, plasma albumin concentration, age, BSA, GFR, haematocrit and sex.

Delineating gene-environment effects using virtual twins of patients treated with clozapine

Studies that focus on individual covariates, while ignoring their interactions, may not be adequate for model-informed precision dosing (MIPD) in any given patient. Genetic variations that influence protein synthesis should be studied in conjunction with environmental covariates, such as cigarette smoking. The aim of this study was to build virtual twins (VTs) of real patients receiving clozapine with interacting covariates related to genetics and environment and to delineate the impact of interacting covariates on predicted clozapine plasma concentrations. Clozapine-treated patients with schizophrenia (N = 42) with observed clozapine plasma concentrations, demographic, environmental, and genotype data were used to construct VTs in Simcyp. The effect of increased covariate virtualization was assessed by performing simulations under three conditions: "low" (demographic), "medium" (demographic and environmental interaction), and "high" (demographic and environmental/genotype interaction) covariate virtualization. Increasing covariate virtualization with interaction improved the coefficient of variation (R² ) from 0.07 in the low model to 0.391 and 0.368 in the medium and high models, respectively. Whereas R² was similar between the medium and high models, the high covariate virtualization model had improved accuracy, with systematic bias of predicted clozapine plasma concentration improving from -138.48 ng/ml to -74.65 ng/ml. A high level of covariate virtualization (demographic, environmental, and genotype) may be required for MIPD using VTs.

Individualized Patient Care Through Model-Informed Precision Dosing: Reflections on Training Future Practitioners

Prior to his passing, Dr. Roger Jelliffe, expressed the need for educating future physicians and clinical pharmacists on the availability of computer-based tools to support dose optimization in patients in stable or unstable physiological states. His perspectives were to be captured in a commentary for the AAPS J with a focus on incorporating population pharmacokinetic (PK)/pharmacodynamic (PD) models that are designed to hit the therapeutic target with maximal precision. Unfortunately, knowing that he would be unable to complete this project, Dr. Jelliffe requested that a manuscript conveying his concerns be completed upon his passing. With this in mind, this final installment of the AAPS J theme issue titled "Alternative Perspectives for Evaluating Drug Exposure Characteristics in a Population - Avoiding Analysis Pitfalls and Pigeonholes" is an effort to honor Dr. Jelliffe's request, conveying his concerns and the need to incorporate modeling and simulation into the training of physicians and clinical pharmacists. Accordingly, Dr. Jelliffe's perspectives have been integrated with those of the other three co-authors on the following topics: the clinical utility of population PK models; the role of multiple model (MM) dosage regimens to identify an optimal dose for an individual; tools for determining dosing regimens in renal dialysis patients (or undergoing other therapies that modulate renal clearance); methods to analyze and track drug PK in acutely ill patients presenting with high inter-occasion variability; implementation of a 2-cycle approach to minimize the duration between blood samples taken to estimate the changing PK in an acutely ill patient and for the generation of therapeutic decisions in advance for each dosing cycle based on an analysis of the previous cycle; and the importance of expressing therapeutic drug monitoring results as 1/variance rather than as the coefficient of variation. Examples showcase why, irrespective of the overall approach, the combination of therapeutic drug monitoring and computer-informed precision dosing is indispensable for maximizing the likelihood of achieving the target drug concentrations in the individual patient.

Semi-Automated Therapeutic Drug Monitoring as a Pillar toward Personalized Medicine for Tuberculosis Management

Standard tuberculosis (TB) management has failed to control the growing number of drug-resistant TB cases worldwide. Therefore, innovative approaches are required to eradicate TB. Model-informed precision dosing and therapeutic drug monitoring (TDM) have become promising tools for adjusting anti-TB drug doses corresponding with individual pharmacokinetic profiles. These are crucial to improving the treatment outcome of the patients, particularly for those with complex comorbidity and a high risk of treatment failure. Despite the actual benefits of TDM at the bedside, conventional TDM encounters several hurdles related to laborious, time-consuming, and costly processes. Herein, we review the current practice of TDM and discuss the main obstacles that impede it from successful clinical implementation. Moreover, we propose a semi-automated TDM approach to further enhance precision medicine for TB management.