Exploration of Optimal Dosing Regimens of Haloperidol, a D2 Antagonist, via Modeling and Simulation Analysis in a D2 Receptor Occupancy Study

Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: Focus on antipsychotics

BACKGROUND

For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialised tools are used. Three tools have been proven useful to personalise drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging.

METHODS

In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 45 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)).

RESULTS

Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings.

CONCLUSION

All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimise treatment effects, minimise side effects and ultimately reduce the global burden of diseases, personalised drug treatment has not yet become the standard of care in psychiatry.

Recent applications of positron emission tomographic (PET) imaging in psychiatric drug discovery

INTRODUCTION

Psychiatry is one of the medical disciplines that suffers most from a lack of innovation in its therapeutic arsenal. Many failures in drug candidate trials can be explained by pharmacological properties that have been poorly assessed upstream, in terms of brain passage, brain target binding and clinical outcomes. Positron emission tomography can provide pharmacokinetic and pharmacodynamic data to help select candidate-molecules for further clinical trials.

AREAS COVERED

This review aims to explain and discuss the various methods using positron-emitting radiolabeled molecules to trace the cerebral distribution of the drug-candidate or indirectly measure binding to its therapeutic target. More than an exhaustive review of PET studies in psychopharmacology, this article highlights the contributions this technology can make in drug discovery applied to psychiatry.

EXPERT OPINION

PET neuroimaging is the only technological approach that can, in vivo in humans, measure cerebral delivery of a drug candidate, percentage and duration of target binding, and even the pharmacological effects. PET studies in a small number of subjects in the early stages of the development of a psychotropic drug can therefore provide the pharmacokinetic/pharmacodynamic data required for subsequent clinical evaluation. While PET technology is demanding in terms of radiochemical, radiopharmacological and nuclear medicine expertise, its integration into the development process of new drugs for psychiatry has great added value.

Update Lessons from Positron Emission Tomography Imaging Part I: A Systematic Critical Review on Therapeutic Plasma Concentrations of Antipsychotics

BACKGROUND

Positron emission tomography (PET) and single photon emission tomography (SPECT) of molecular drug targets (neuroreceptors and transporters) provide essential information for therapeutic drug monitoring-guided antipsychotic drug therapy. The optimal therapeutic windows for D 2 antagonists and partial agonists, as well as their proposed target ranges, are discussed based on an up-to-date literature search.

METHODS

This part I of II presents an overview of molecular neuroimaging studies in humans and primates involving the target engagement of amisulpride, haloperidol, clozapine, aripiprazole, olanzapine, quetiapine, risperidone, cariprazine, and ziprasidone. The systemic review particularly focused on dopamine D 2 -like and 5-HT 2A receptors. Target concentration ranges were estimated based on receptor occupancy ranges that relate to clinical effects or side effects (ie, extrapyramidal side effects). In addition, findings for other relevant receptor systems were included to further enrich the discussion.

RESULTS

The reported reference ranges for aripiprazole and clozapine align closely with findings from PET studies. Conversely, for haloperidol, risperidone, and olanzapine, the PET studies indicate that a lowering of the previously published upper limits would be necessary to decrease the risk of extrapyramidal side effect.

CONCLUSIONS

Molecular neuroimaging studies serve as a strong tool for defining target ranges for antipsychotic drug treatment and directing therapeutic drug monitoring.

The effects of haloperidol on microglial morphology and translocator protein levels: An in vivo study in rats using an automated cell evaluation pipeline

BACKGROUND

Altered microglial markers and morphology have been demonstrated in patients with schizophrenia in post-mortem and in vivo studies. However, it is unclear if changes are due to antipsychotic treatment.

AIMS

Here we aimed to determine whether antipsychotic medication affects microglia in vivo.

METHODS

To investigate this we administered two clinically relevant doses (0.05 mg n=12 and 2.5 mg n=7 slow-release pellets, placebo n=20) of haloperidol, over 2 weeks, to male Sprague Dawley rats to determine the effect on microglial cell density and morphology (area occupied by processes and microglial cell area). We developed an analysis pipeline for the automated assessment of microglial cells and used lipopolysaccharide (LPS) treatment ( n=13) as a positive control for analysis. We also investigated the effects of haloperidol ( n=9) or placebo ( n=10) on the expression of the translocator protein 18 kDa (TSPO) using autoradiography with [³H]PBR28, a TSPO ligand used in human positron emission tomography (PET) studies.

RESULTS

Here we demonstrated that haloperidol at either dose does not alter microglial measures compared with placebo control animals ( p > 0.05). Similarly there was no difference in [³H]PBR28 binding between placebo and haloperidol tissue ( p > 0.05). In contrast, LPS was associated with greater cell density ( p = 0.04) and larger cell size ( p = 0.01).

CONCLUSION

These findings suggest that haloperidol does not affect microglial cell density, morphology or TSPO expression, indicating that clinical study alterations are likely not the consequence of antipsychotic treatment. The automated cell evaluation pipeline was able to detect changes in microglial morphology induced by LPS and is made freely available for future use.

Nonlinear Mixed-Effects Models for PET Data

OBJECTIVE

The current state-of-the-art for compartment modeling of dynamic PET data can be described as a two-stage approach. In Stage 1, individual estimates of kinetic parameters are obtained by fitting models using standard techniques, such as nonlinear least squares, to each individual's data one subject at a time. Population-level effects, such as the difference between diagnostic groups, are analyzed in Stage 2 using standard statistical methods by treating the individual estimates as if they were observed data. While this approach is generally valid, it is possible to increase efficiency and precision of the analysis, allow more complex models to be fitted, and also to permit parameter-specific investigation by fitting data across subjects simultaneously. We explore the application of nonlinear mixed-effects (NLME) models for estimation and inference in this setting.

METHODS

In the NLME framework, subjects are modeled simultaneously through the inclusion of random effects of subjects for each kinetic parameter; meanwhile, population parameters are estimated directly in a joint model.

RESULTS

Simulation results indicate that NLME outperforms the two-stage approach in estimating group-level effects and also has improved power to detect differences across groups. We applied our NLME approach to clinical PET data and found effects not detected by the two-stage approach.

CONCLUSION

The proposed NLME approach is more accurate and correspondingly more powerful than the two-stage approach in compartment modeling of PET data.

SIGNIFICANCE

The NLME method can broaden the methodological scope of PET modeling because of its efficiency and stability.

Predicting the dopamine D2 receptor occupancy of ropinirole in rats using positron emission tomography and pharmacokinetic-pharmacodynamic modeling

1. The purpose of this study was to measure dopamine D_2/3 receptor occupancy (RO) as a marker of the clinical efficacy of ropinirole in rats via positron emission tomography (PET) using ¹⁸F-fallypride as the radiotracer and to explore the relationship between dopamine RO and the plasma concentration of ropinirole via pharmacokinetic-pharmacodynamic modeling. 2. Plasma was collected from 16 rats treated with one of four doses of ropinirole. For the time-dependent study, the data of 16 rats in the 15 mg/kg dose group at four time points were averaged, and another 24 rats were divided into three dose groups (5 mg/kg, 30 mg/kg and 60 mg/kg) for the dose-dependent study; the animals were assessed via ¹⁸F-fallypride PET scans. The correlation between dopamine RO and the ropinirole plasma concentration was investigated, and a pharmacokinetic-pharmacodynamic (PK-PD) model was established with WinNonlin 6.3 software. Both the plasma concentration and the binding potential changed in a time- and dose-dependent manner, and the plasma concentration that induces 50% RO (EC₅₀) as calculated by the PK-PD model was 1391 ng/mL. 3. ¹⁸F-fallypride appeared to be a suitable radiotracer for ropinirole imaging, and its binding to the dopamine D₂ receptor has time- and concentration-dependent characteristics. A theory-based PK-PD model was developed to describe the relationship between the plasma ropinirole concentration and RO, providing a methodological foundation for noninvasive and in vivo clinical evaluations of ropinirole treatment.

Do doctors agree on doses of antipsychotic medications?

BACKGROUND

The objective of this study was to investigate the concordance in attitudes of psychiatrists towards the doses of antipsychotics given to stable outpatients with schizophrenia and to examine the psychiatrists' estimates of equally potent doses of haloperidol and olanzapine.

METHODS

We asked all 22 doctors serving at the psychiatry department of Jönköping County Hospital if they considered the combined dose of antipsychotics for 20 individual patients to be 'low', 'medium' or 'high'. We also asked each doctor to state the dose of haloperidol that they considered to be clinically equivalent to 20 mg/day of olanzapine.

RESULTS

The inter-rater reliability (Krippendorff's alpha (α)) was 0.50, and the mean estimated dose haloperidol considered clinically equivalent to 20 mg/day of olanzapine was 4.45 mg/day.

CONCLUSIONS

The inter-rater reliability (Krippendorff's α) was low, suggesting lack of agreement. The dose of antipsychotics given to a patient might thus be more influenced by which doctor they meet than the severity of the disease. The respondents in this study considered a mean dose of 4.45 mg/day of haloperidol to be clinically equivalent to 20 mg/day of olanzapine. This is a considerably lower dose than was determined by an international consensus study of antipsychotic dosing, and more in line with the available PET studies measuring central dopamine receptor blockage of optimal clinical doses.

Risk of Mortality Among Patients Treated With Antipsychotic Medications: A Nationwide Population-Based Study in Taiwan

In this nationwide population-based study, we examined whether haloperidol exposure is associated with a higher risk of mortality than are other antipsychotic medications. Patients who newly received monotherapy with chlorpromazine (n = 2133), haloperidol (n = 4454), quetiapine (n = 1513), and risperidone (n = 1046) between January 1, 2001, and December 31, 2011, were selected from a random sample of the 1 million enrollees of the Taiwan National Health Insurance Research Database. The association between antipsychotic prescription and mortality was estimated through Cox proportional hazard regression. To examine the mortality rates of antipsychotics at different exposure durations, we compared the differences among short-term (≤30 days), midterm (31-90 days), and long-term (>90 days) antipsychotic use. The mortality rates during the follow-up among the chlorpromazine, haloperidol, quetiapine, and risperidone groups were 17.4%, 45.5%, 26.8%, and 25.9%, respectively. The mortality risk among patients receiving haloperidol was the highest within 30 days of the prescription, after which the risk reduced rapidly. Compared with the patients receiving chlorpromazine, the mortality risk was higher in short-term (adjusted hazard ratio, 2.11; 95% confidence interval, 1.87-2.39) and midterm haloperidol users (1.86; 1.54-2.25) than in long-term users (0.99; 0.61-1.61). In conclusion, haloperidol use is associated with higher mortality risk than other antipsychotic medications. The mortality risk varies according to the duration of drug exposure. Underlying characteristics and medical conditions may influence the estimation of the mortality risk. Clinicians should pay attention to the mortality risk when prescribing antipsychotic medications, particularly for the elderly and critically ill patients.

Integration of PKPD relationships into benefit-risk analysis

AIM

Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit-risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit-risk assessment. In addition, we propose the use of pharmacokinetic-pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents.

METHODS

A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit-risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile.

RESULTS

A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit-risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit-risk balance before extensive evidence is generated in clinical practice.

CONCLUSIONS

Benefit-risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials.

Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia

Schizophrenia is a severe mental disorder characterized by cognitive deficits, and positive and negative symptoms. The development of effective pharmacological compounds for the treatment of schizophrenia has proven challenging and costly, with many compounds failing during clinical trials. Many failures occur due to disease heterogeneity and lack of predictive preclinical models and biomarkers that readily translate to humans during early characterization of novel antipsychotic compounds. Traditional early-phase trials consist of single- or multiple-dose designs aimed at determining the safety and tolerability of an investigational compound in healthy volunteers. However, by incorporating a translational approach employing methodologies derived from preclinical studies, such as EEG measures and imaging, into the traditional Phase I program, critical information regarding a compound's dose-response effects on pharmacodynamic biomarkers can be acquired. Furthermore, combined with the use of patients with stable schizophrenia in early-phase clinical trials, significant 'de-risking' and more confident 'go/no-go' decisions are possible.