Explore the vast range of titles available.

As a result of neuro-vascular coupling, the functional effects of antipsychotics in human brain have been investigated in both healthy and clinical populations using haemodynamic markers such as regional Cerebral Blood Flow (rCBF). However, the relationship between observed haemodynamic effects and the pharmacological action of these drugs has not been fully established. Here, we analysed Arterial Spin Labelling (ASL) rCBF data from a placebo-controlled study in healthy volunteers, who received a single dose of three different D2 receptor (D2R) antagonists and tested the association of the main effects of the drugs on rCBF against normative population maps of D2R protein density and gene-expression data. In particular, we correlated CBF changes after antipsychotic administration with non-displaceable binding potential (BPND) template maps of the high affinity D2-antagonist Positron Emission Tomography (PET) ligand [18F]Fallypride and with brain post-mortem microarray mRNA expression data for the DRD2 gene from the Allen Human Brain Atlas (ABA). For all antipsychotics, rCBF changes were directly proportional to brain D2R densities and DRD2 mRNA expression measures, although PET BPND spatial profiles explained more variance as compared with mRNA profiles (PET R2 range = 0.20–0.60, mRNA PET R2 range 0.04–0.20, pairwise-comparisons all pcorrected<0.05). In addition, the spatial coupling between ΔCBF and D2R profiles varied between the different antipsychotics tested, possibly reflecting differential affinities. Overall, these results indicate that the functional effects of antipsychotics as measured with rCBF are tightly correlated with the distribution of their target receptors in striatal and extra-striatal regions. Our results further demonstrate the link between neurotransmitter targets and haemodynamic changes reinforcing rCBF as a robust in-vivo marker of drug effects. This work is important in bridging the gap between pharmacokinetic and pharmacodynamics of novel and existing compounds. [Display omitted]

ABSTRACT Purpose To evaluate the potential usage of D 2 receptor occupancy (D2RO) measured by positron emission tomography (PET) in antipsychotic development. Methods In this randomized, parallel group study, eight healthy male volunteers received oral doses of 0.5 ( n  = 3), 1 ( n  = 2), or 3 mg ( n  = 3) of haloperidol once daily for 7 days. PET’s were scanned before haloperidol, and on days 8, 12, with serial pharmacokinetic sampling on day 7. Pharmacokinetics and binding potential to D 2 receptor in putamen and caudate nucleus over time were analyzed using NONMEM, and simulations for the profiles of D2RO over time on various regimens of haloperidol were conducted to find the optimal dosing regimens. Results One compartment model with a saturable binding compartment, and inhibitory E max model in the effect compartment best described the data. Plasma haloperidol concentrations at half-maximal inhibition were 0.791 and 0.650 ng/ml, in putamen and caudate nucleus. Simulation suggested haloperidol 2 mg every 12 h is near the optimal dose. Conclusion This study showed that sparse D2RO measurements in steady state pharmacodynamic design after multiple dosing could reveal the possibility of treatment effect of D 2 antagonist, and could identify the potential optimal doses for later clinical studies by modeling and simulation.

This study aimed to elucidate the relationship between CYP2D6 genotype and haloperidol pharmacokinetics and induced extrapyramidal symptoms (EPSs). Twenty five healthy subjects were included in this randomized, placebo-controlled, single-dose (5 mg) crossover and double-blind clinical trial, selected according to their CYP2D6 genotype and classified as poor metabolizers (n = 8), extensive metabolizers (n = 10) and ultrarapid metabolizers (n = 7). We confirm that CYP2D6 genotype partially determines haloperidol metabolism and the rate of EPSs measured as wakefulness activity by actigraphy. The best predictor of wakefulness activity was the model including haloperidol area under the plasma concentration-time curve, sex and tranquilization, which explained 48.3% of the total variance. However, other markers need to be identified in order to explain the observed variability of haloperidol response and to develop pharmacogenetic predictors of haloperidol-induced EPSs.

Background Alzheimer’s disease (AD) is the most prevalent form of dementia and represents one of the highest unmet requirements in medicine today. There is shortage of novel molecules entering into market because of poor pharmacokinetic properties and safety issues. Drug repurposing offers an opportunity to reinvigorate the slowing drug discovery process by finding new uses for existing drugs. The major advantage of the drug repurposing approach is that the safety issues are already investigated in the clinical trials and the drugs are commercially available in the marketplace. As this approach provides an effective solution to hasten the process of providing new alternative drugs for AD, the current study shows the molecular interaction of already known antipsychotic drugs with the different protein targets implicated in AD using in silico studies. Result A computational method based on ligand–protein interaction was adopted in present study to explore potential antipsychotic drugs for the treatment of AD. The screening of approximately 150 antipsychotic drugs was performed on five major protein targets (AChE, BuChE, BACE 1, MAO and NMDA) by molecular docking. In this study, for each protein target, the best drug was identified on the basis of dock score and glide energy. The top hits were then compared with the already known inhibitor of the respective proteins. Some of the drugs showed relatively better docking score and binding energies as compared to the already known inhibitors of the respective targets. Molecular descriptors like molecular weight, number of hydrogen bond donors, acceptors, predicted octanol/water partition coefficient and percentage human oral absorption were also analysed to determine the in silico ADME properties of these drugs and all were found in the acceptable range and follows Lipinski’s rule. Conclusion The present study have led to unravel the potential of leading antipsychotic drugs such as pimozide, bromperidol, melperone, anisoperidone, benperidol and anisopirol against multiple targets associated with AD. Benperidol was found to be the best candidate drug interacting with different target proteins involved in AD.

Neuroleptic malignant syndrome, characterized by fever, muscular rigidity, and dysautonomia, occurs with exposure to dopamine-blocking agents. Management, especially in critical care contexts, is described.

The current study provides a novel in-depth assessment of the extent of antipsychotic drugs transport across the blood–brain barrier (BBB) into various brain regions, as well as across the blood–spinal cord barrier (BSCB) and the blood–cerebrospinal fluid barrier (BCSFB). This is combined with an estimation of cellular barrier transport and a systematic evaluation of nonspecific brain tissue binding. The study is based on the new Combinatory Mapping Approach (CMA), here further developed for the assessment of unbound drug neuropharmacokinetics in regions of interest (ROI), referred as CMA-ROI. We show that differences exist between regions in both BBB transport and in brain tissue binding. The most dramatic spatial differences in BBB transport were found for the P-glycoprotein substrates risperidone (5.4-fold) and paliperidone (4-fold). A higher level of transporter-mediated protection was observed in the cerebellum compared with other brain regions with a more pronounced efflux for quetiapine, risperidone and paliperidone. The highest BBB penetration was documented in the frontal cortex, striatum and hippocampus (haloperidol, olanzapine), indicating potential influx mechanisms. BSCB transport was in general characterized by more efficient efflux compared with the brain regions. Regional tissue binding was significantly different for haloperidol, clozapine, risperidone and quetiapine (maximally 1.9-fold). Spatial differences in local unbound concentrations were found to significantly influence cortical 5-HT 2A receptor occupancy for risperidone and olanzapine. In conclusion, the observed regional differences in BBB penetration may potentially be important factors contributing to variations in therapeutic effect and side effect profiles among antipsychotic drugs.

Previous studies suggest that antipsychotic medications may alter cortical inhibition (CI). The current study was designed to determine if typical or atypical antipsychotics indeed alter CI in healthy subjects using three CI paradigms as measured with transcranial magnetic stimulation (TMS): short interval intracortical inhibition (SICI), cortical silent period (CSP) and transcallosal inhibition (TCI). CI was measured before, 6 and 24 h after being randomly assigned to receive a single dose of 2 mg haloperidol (n=8), 10 mg olanzapine (n=10) or placebo (n=9). There was no significant effect on any measure of CI at 6 and 24 h after receiving olanzapine, haloperidol or placebo. Moreover, no significant change in the motor threshold was observed across the three medication groups. Therefore, single administration of an antipsychotic has no effect on CI or resting motor threshold. Whether chronic, repeated administration of antipsychotics has effects on CI requires further investigation.

Abstract An association between antipsychotic drugs and pneumonia has been demonstrated in several studies; however, the risk for pneumonia caused by specific antipsychotics has not been extensively studied. The underlying mechanism is still unknown, and several receptor mechanisms have been proposed. Therefore, using a combined pharmacovigilance-pharmacodynamic approach, we aimed to investigate safety signals of US Food and Drug Administration (FDA)-approved antipsychotics for reporting pneumonia and the potential receptor mechanisms involved. A disproportionality analysis was performed to detect a signal for reporting “infective-pneumonia” and “pneumonia-aspiration” and antipsychotics using reports submitted between 2004 and 2019 to the FDA adverse events spontaneous reporting system (FAERS) database. Disproportionality was estimated using the crude and the adjusted reporting odds ratio (aROR) and its 95% confidence interval (CI) in a multivariable logistic regression. Linear regressions investigated the relationship between aROR and receptor occupancy, which was estimated using in vitro receptor-binding profiles. Safety signals for reporting infective-pneumonia were identified for clozapine (LL = 95% 3.4, n = 546 [aROR: 4.8]) as well as olanzapine (LL = 95% 1.5, n = 250 [aROR: 2.1]) compared with haloperidol, while aRORs were associated with higher occupancies of muscarinic receptors (beta = .125, P-value = .016), yet other anti-muscarinic drugs were not included as potential confounders. No safety signals for reporting pneumonia-aspiration were detected for individual antipsychotics. Multiple antipsychotic use was associated with both reporting infective-pneumonia (LL 95%: 1.1, n = 369 [aROR:1.2]) and pneumonia-aspiration (LL 95%: 1.7, n = 194 [aROR: 2.0]). Considering the limitations of disproportionality analysis, further pharmacovigilance data and clinical causality assessment are needed to validate this safety signal.

Purpose Therapeutic drug monitoring (TDM) of antipsychotics can aid in therapy optimization, explaining adverse effects or non-response. One reason for therapeutic failure or adverse effects is caused by genetic variations in the cytochrome P450 drug-metabolizing genes. The aim of this study was to evaluate the impact of CYP2D6 polymorphisms on steady-state serum concentrations of antipsychotics metabolized by CYP2D6, taking into account the co-medication with CYP2D6 inhibitors. Methods Serum and EDTA samples were collected from 82 psychiatric patients. After a liquid-liquid extraction, serum samples were analyzed using an ultra-high performance liquid chromatography-tandem mass spectrometric (UHPLC-MS/MS) method for quantification of the antipsychotics. CYP2D6 genotyping was performed using the Luminex xTAG® CYP2D6 Kit v3 (Luminex Corporation). Patients were divided into five phenotype subgroups by calculation of the activity score (AS): poor metabolizers (PM; AS 0), intermediate metabolizers (IM; AS 0.5–1), extensive metabolizers with slow activity (EM-s; AS 1–1.5), extensive metabolizers with fast activity (EM-f; AS 2), and ultra-rapid metabolizers (UM; AS >2). The influence of the phenotypes on the concentration-to-dose and metabolite-to-parent ratios was evaluated. Results Overall, 6.1 % UM ( n  = 5), 25.6 % EM-f ( n  = 21), 46.3 % EM-s ( n  = 38), 1.2 % EM-s/EM-f ( n  = 1), 6.1 % IM ( n  = 5), and 14.6 % PM ( n  = 12) were found, taking co-administration of strong and moderate CYP2D6 inhibitors into account (phenoconversion). It was demonstrated that CYP2D6 polymorphisms affect the serum concentrations of aripiprazole ( n  = 18), haloperidol ( n  = 11), risperidone ( n  = 20), and zuclopenthixol ( n  = 6), while no influence was seen on the paliperidone serum concentrations ( n  = 31). Conclusions Even with a small number of patients per antipsychotic, the importance of CYP2D6 genotyping was still clearly stated. This study illustrates the high potential of combining TDM and CYP2D6 genotyping in clinical practice.

The association between anticholinergic load-based Anticholinergic Risk Scale scores and nutritional status is unclear in Japanese patients. The aim of this study was to establish whether anticholinergic load affects the nutritional status of geriatric patients in convalescent stages. Retrospective longitudinal cohort study. Convalescent rehabilitation wards. Of the 1490 patients aged ≥65 years who were discharged from convalescent rehabilitation wards between July 2010 and October 2018, 908 patients met the eligibility criteria. They were categorized according to the presence or absence of increased anticholinergic load from admission to discharge. Demographic data, laboratory data, the Functional Independence Measure were analyzed between the groups. The primary outcome was Geriatric Nutritional Risk Index (GNRI) at discharge. Multiple linear regression analysis was performed to analyze the relationship between anticholinergic load and GNRI at discharge. Multiple linear regression analysis after adjusting for confounding factors revealed that anticholinergic load was independently and negatively correlated with GNRI at discharge. Particularly, the use of chlorpromazine, hydroxyzine, haloperidol, metoclopramide, risperidone, etc. increased significantly from admission to discharge. Increased anticholinergic load during hospitalization may be a predictor of nutritional status in geriatric patients.