Residual dopamine receptor desensitization following either high- or low-dose sub-chronic prior exposure to the atypical anti-psychotic drug olanzapine

Dias, Flávia Regina Cruz; Matos, Liana Wermelinger de; Sampaio, Maria de Fátima dos Santos; Carey, Robert J.; Carrera, Marinete Pinheiro

doi:10.1007/s00213-012-2802-1

Cited by 2 publications

(6 citation statements)

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“…Notably, DSP can also occur due to sustained prescription of high doses of antipsychotics (Chouinard et al, 1982) or long-term treatment with FGA (Chouinard and Jones, 1980;Jenner et al, 1983). In contrast, it occurs less commonly following long periods of treatment with SGA that have lower D2 affinity as compared to FGA, such as clozapine (Ekblom et al, 1984;Li et al, 2009;Rupniak et al, 1984;Rupniak et al, 1985;Seeman et al, 2005), olanzapine (Bedard et al, 2013;Dias et al, 2013;El Hage et al, 2015;Llorca et al, 2001) or with partial D2 receptor agonists such as aripiprazole (Tadokoro et al, 2012;Varela et al, 2014). The SGA risperidone long-acting injectable (RLAI) was found to be effective, and well-tolerated against positive and negative symptoms (Kane et al, 2003) with higher therapeutic benefits in patients with DSP switched to RLAI (Kimura et al, 2014).…”

Section: ) Long-term D2 Receptor Blockade Produces Counter-therapeutmentioning

confidence: 99%

Dopamine, the antipsychotic molecule: A perspective on mechanisms underlying antipsychotic response variability

Amato

Vernon

Papaleo

2018

Neuroscience & Biobehavioral Reviews

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All antipsychotics bind to the dopamine D2 receptor. An "optimal" level of D2 receptor blockade with antipsychotics is thought to ameliorate the positive symptoms of schizophrenia. However, persistent D2 receptor blockade is associated with a deteriorating clinical response in a subset of patients. Interestingly, antipsychotics with a weaker D2 receptor binding profile appear somewhat superior in this respect. This evidence challenges the hypothesis that D2 receptor blockade is the sole mechanism of antipsychotic efficacy and points to consistent inter-individual responses to antipsychotic treatment. Here, we hypothesize that clinically effective doses of antipsychotics would lead to the formation of a D2 receptor "reserve" that is likely composed of presynaptic dopamine D2 autoreceptors. The majority of the remaining postsynaptic dopamine receptors are instead occupied by antipsychotics. Endogenous dopamine would then mainly interact with this D2 autoreceptor reserve, thereby reducing the presynaptic synthesis and release of dopamine and resulting in an indirect antipsychotic effect. This new proposal reconciles conceptual and empirical gaps encountered when clinical outcomes are compared to the pharmacology of antipsychotics.

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Section: ) Long-term D2 Receptor Blockade Produces Counter-therapeutmentioning

confidence: 99%

Dopamine, the antipsychotic molecule: A perspective on mechanisms underlying antipsychotic response variability

Amato

Vernon

Papaleo

2018

Neuroscience & Biobehavioral Reviews

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“…Antipsychotic medicines Table 1 outlines the dose, dosing interval and pharmacokinetic parameters utilized in the optimal sampling analysis [3,31,33,35,37,38,48]. The standard dose ranges and regimens for each drug were quite different.…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies investigating population PK/PD of antipsychotic medicines have typically used sparse sampling, but the effectiveness of the sampling schedules of these studies has not been evaluated . The current study recommends the collection of samples at three time points for optimal sampling of each antipsychotic medicine.…”

Section: Discussionmentioning

confidence: 99%

“…Population parameter estimates of clearance, volume of distribution and absorption rates of several antipsychotic medications commonly used in ambulatory patients with schizophrenia or schizoaffective disorder were extracted from published studies in order to conduct the blood sampling optimization analyses. The strategy used, population pharmacokinetic studies accessed and the population models we utilized to analyze the respective data are presented in Supplementary Figure S1 and Supplementary Table S1 [3, [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48].…”

Section: Methodsmentioning

confidence: 99%

“…Table 1 outlines the pharmacokinetic parameters extracted and used for our analyses. As the CATIE data for each antipsychotic drug has been analyzed previously to produce pharmacokinetic models and published in several manuscripts, we selected the most recently published study [3,31,33,35,37,38,48]. Typically, different doses were prescribed to subjects within a study, and therefore the dose we selected in the current analysis was the median prescribed dose.…”

Section: Data Selectionmentioning

confidence: 99%

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Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice

Perera

Bies

et al. 2014

Brit J Clinical Pharma

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AIMTo determine optimal sampling strategies to allow the calculation of clinical pharmacokinetic parameters for selected antipsychotic medicines using a pharmacometric approach. METHODSThis study utilized previous population pharmacokinetic parameters of the antipsychotic medicines aripiprazole, clozapine, olanzapine, perphenazine, quetiapine, risperidone (including 9-OH risperidone) and ziprasidone. D-optimality was utilized to identify time points which accurately predicted the pharmacokinetic parameters (and expected error) of each drug at steady-state. A standard two stage population approach (STS) with MAP-Bayesian estimation was used to compare area under the concentration-time curves (AUC) generated from sparse optimal time points and rich extensive data. Monte Carlo Simulation (MCS) was used to simulate 1000 patients with population variability in pharmacokinetic parameters. Forward stepwise regression analysis was used to determine the most predictive time points of the AUC for each drug at steady-state. RESULTSThree optimal sampling times were identified for each antipsychotic medicine. For aripiprazole, clozapine, olanzapine, perphenazine, risperidone, 9-OH risperidone, quetiapine and ziprasidone the CV% of the apparent clearance using optimal sampling strategies were 19.5, 8.6, 9.5, 13.5, 12.9, 10.0, 16.0 and 10.7, respectively. Using the MCS and linear regression approach to predict AUC, the recommended sampling windows were 16.5-17.5 h, 10-11 h, 23-24 h, 19-20 h, 16.5-17.5 h, 22.5-23.5 h, 5-6 h and 5.5-6.5 h, respectively. CONCLUSIONThis analysis provides important sampling information for future population pharmacokinetic studies and clinical studies investigating the pharmacokinetics of antipsychotic medicines. WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Antipsychotic medicines are widely prescribed for the management of schizophrenia. However there are high rates of discontinuation, drug switching and dose adjustment which in part is due to the large inter-individual variability in response to these medicines.• Pharmacometric approaches to determine pharmacokinetic parameters using sparse sampling strategies are increasing. However the optimal sampling time points which determine the precision and accuracy of these parameters are typically not taken into account.• Aside from clozapine, therapeutic drug monitoring strategies for other antipsychotic medicines are not implemented in hospital settings routinely and this is in part due to the lack of clearly defined exposure-response relationships. WHAT THIS STUDY ADDS• This analysis has utilized pharmacometric tools to provide optimal sampling time points for future population PK/PD studies, guidance for therapeutic drug monitoring and to allow clinicians practical solutions to calculate complex pharmacokinetic parameters when interpreting exposure to antipsychotic medicines. • Bayesian population PK estimates using sparse but optimal time points yield excellent correlations and only small errors when compared with extensive sampling strategies.• Tr...

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Residual dopamine receptor desensitization following either high- or low-dose sub-chronic prior exposure to the atypical anti-psychotic drug olanzapine

Cited by 2 publications

References 39 publications

Dopamine, the antipsychotic molecule: A perspective on mechanisms underlying antipsychotic response variability

Dopamine, the antipsychotic molecule: A perspective on mechanisms underlying antipsychotic response variability

Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice

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